food quality: the relevance of food grades

Chapter 14

Food Quality: The Relevanceof Food Grades

PhotoCredit: Grant Heilman, Inc

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INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ........353THE PORK GRADING SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354

USDA Grade Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ....354Changing Public Concerns and Expectations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. ...............355New Technologies and Implications for Pork Grading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ....356Potential Parameters for Alternative Grading System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ......359Options for unimproved Grading System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

THE FRUIT AND VEGETABLE GRADING SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ...366Fruit and Vegetable Production and Consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. ...........366USDA Grade Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ....367Conceptual Considerations of Grade Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. ............369Nutritional Attribute Measurement . . . . . . . . . .Nutrient Attributes Variation . . . . . . . . . . . . . . . .Assessing the Relationship Between NutrientChemicals and the Grading System . . . . . .Chemical Residue Grading Standard . . . . .Options for unimproved Grading SystemConclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

CHAPTER 14 REFERENCES . . . . . . . . . . . . . .

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369and Sensory Characteristics . . . . . . . . . . . . . . . . . . 372. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381

Box14-A. Technology14-B. Technology

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Evaluate Pork Carcasses or Products . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ......362Nutrient Attribute Measurement of Fruits and Vegetables .. .............370

Chapter 14

Food Quality:The Relevance of Food Grades

INTRODUCTIONMany consumers are expressing concerns over the safety

and the quality of food, and these concerns extend to theuse of new agricultural technology in food production.Information about food quality can be provided throughlabeling, brand names, price, and grades. Food grades,for example, are used to classify products according tocertain quality characteristics.

The objective of a grading system is to sort a pop-ulation with heterogeneous characteristics (i. e., a groupof foods) into lots of more uniform or homogeneouscharacteristics. An effective grading system uses per-sonal observation and testing to provide informationthat reduces user-perceived risks associated with prod-uct quality. Grading also aims to improve product uni-formity within a particular grade and serves as the basisfor price. Grading facilitates an equitable incentivesystem stimulating farmers to produce commodities inresponse to consumer preferences. As a consequence,grading transaction costs are lowered and overall mar-keting efficiency is enhanced. Sorting via grades alsofacilitates trade because many consumers are likely tolack the expertise or time to identify meaningful qualit ycharacteristics from heterogeneous lots of any partic-ular commodity.

Grades for beef, fruits, and vegetables are usedthroughout the marketing system, i.e., by farmers, pro-cessors, wholesalers, retailers, and consumers. How-ever, grades for some commodities (i.e,, pork) are usedalmost entirely at the producer-processor level. At least70 percent of pork is cured, smoked, or further pro-cessed before it reaches the consumer, whereas mostbeef reaches the consumer in the fresh form; this canexplain the greater need for beef quality grades at theconsumer level. Pork is also more uniform from a qual-ity point of view than beef. Most hogs are marketedat about the same age after being fed a high-concentratediet. Beef cattle, on the other hand, may be marketedas ‘‘grass fat” or after being fed high-concentrate ra-tions for varying lengths of time, and are slaughteredat a wide range of ages. Both factors influence ten-derness and appearance of fresh beef.

The use of grades as a proxy for quality is criticizedheavily for at least two reasons. First is the concern

about the usefulness of current grading systems, es-pecially for the livestock industries. The criticism fo-cuses on the relevance of the criteria used and on theaccuracy of measurement, and the value differentiationfor users.

Second is the concern about the attributes on whichgrading is based and resulting economic incentives.For example, fruit and vegetable grades are based oncharacteristics that affect consumers’ senses, such astouch, sight, and taste, and on shelf-life considerationsor some combination of these factors. These currentsensory-based grade attributes, critics argue, indirectlymay encourage the use of chemicals during the pro-duction process. For example, when the top grade ofa fruit or vegetable is based on sensory characteristics,it provides economic incentive to apply chemicals soas to ensure minimal blemishes and vibrant skin color.If the standards were shifted away from sensory char-acteristics, fewer chemicals probably would be usedbecause less economic incentive would exist to usechemicals.

Consumers are increasingly aware of and dubiousabout the use of chemicals, or chemically based in-gredients, in the production and preservation of thefood supply. In addition to concern that chemicals usedin the production process may be deleterious to theenvironment, concern exists that chemical ingredientsin or on food maybe injurious to human health, perhapsin ways yet unknown to the scientific community.

However, grading standards and the process of grad-ing should not be confused with food safety. Foodsafety is a question of determining whether or not theingestion of a particular food or food ingredient maybe injurious to human health. Only food items alreadydetermined to be safe are graded.

This chapter focuses on two concerns 1) the useful-ness of current grades and 2) the potential for alter-native grade attributes. An exhaustive analysis of allgrading systems is beyond the scope of this report.Instead, a case approach is used to focus on theseissues. The first case study focuses on the livestockindustry —specifically pork. The second focuses on thefruit and vegetable industry.

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354 . A New Technological Era for American Agriculture

THE PORK GRADING SYSTEM1

USDA Grade Standards

Background

Grade standards for pork were established by the U.S.Department of Agriculture (USDA) in the early 1930s.Barrows and gilts are the primary market animals. Gradesfor barrow and gilt carcasses, i.e., U.S. No. 1, No. 2,No. 3, and No. 4 are based on two general considerations:1) quality—which includes characteristics of lean andfat, and 2) expected yield (i.e., in proportion to totalweight) of the four lean cuts (ham, loin, picnic shoulder,and Boston butt).

Two general levels of quality are recognized: 1) ac-ceptable and 2) unacceptable. Presently, the quality oflean cuts is best evaluated by a direct observation of itscharacteristics on a cut surface. Standards indicate thatwhen a cut surface of a major muscle is available, qualitydetermination shall be based on the characteristics of theloin eye muscle at the 10th rib. When this surface is notavailable, other exposed major muscle surfaces can beused for comparable quality determinations. Generally,packers do not elect to reduce the value of a loin bycutting the loin at the 10th rib or to expose any of themajor muscle surfaces. When a major muscle cut surfaceis not available, the quality of the lean is to be evaluatedindirectly based on quality-indicating characteristics ofthe carcass. These include firmness of the fat and lean,amount of feathering (fat streaking in tissue) between theribs, and color of the lean. While current standards em-ploy feathering as a quality indicator, there is no scientificevidence that feathering is related to quality.

A barrow or gilt carcass with acceptable lean qualityand belly thickness is placed in one of four grades, de-pending on the backfat thickness over the last rib, andthe degree of muscling (thickness of muscling in relationto skeletal size). These two factors together indicate theexpected carcass yields of the four lean cuts. These yieldsare based on cutting and trimming methods used by theU.S. Department of Agriculture in developing the stan-dards (table 14-1). Other cutting and trimming methodsmay result in different yields.

Adoption of USDA Grades

Use of USDA grade standards is voluntary. However,if a packing plant decides to use grade standards and

designate the U.S. grade on a package label, they mustuse USDA’s grade standards.

A USDA study of 12 packers in 1981 and 1982 foundthat none of the plants used the USDA grading system(66). This may be attributable in part to the fact thatUSDA grade standards had not changed since 1968,whereas the characteristics of the market hog populationhad changed significantly. In 1981–82, 71.7 percent ofthe market hogs were graded U.S. No. 1, and 24.4 per-cent were graded U.S. No. 2; these USDA standardswere not effectively discriminating among hogs varyingsignificantly in value. Most packers developed their owngrading systems in order to differentiate among porkcarcasses (one plant had no grading system). Becauseeach packer’s grade and evaluation system was individ-ually designed, grade criteria, descriptive terms used forgrades, and evaluation methods varied among packers.Among the factors used to determine grading standardswere backfat, muscling, percentage of carcass weightconsisting of primal cuts, and conformation. Packer em-ployees primarily used visual appraisal for grading. In1985 the USDA changed the backfat standards for itsgrades (table 14-1), but a study of market hog charac-teristics from five plants in the South and Midwest pre-dicted that 98 percent of the pigs would be in the U.S.No. 1 or No. 2 grade (52). Thus, USDA grades still donot adequately differentiate carcass quality. Overall, porkcarcass characteristics have improved to where most meetthe standards for the top USDA grades.

Packer grading and evaluation systems also have evolvedover the past decade and now have little in common withthe USDA grading system. A 1990 Iowa State Universitysurvey of 12 of the largest pork slaughter firms foundthat all large packers now are using carcass weights intheir evaluation procedure. Four of the largest packersindicated that actual backfat measurements were the pri-mary basis for their internal evaluation system and theircarcass merit buying systems (though the grade could bemodified by extremes in muscling noted by visual eval-uation). Where backfat measurements were employed,the top grades often had much lower backfat thresholdsthan USDA grades currently do, with one at 0.6 inchesof backfat or less, and two at 0.8 in. or 0.75 in. or less.Seven firms reported currently using or switching soonto the use of the Fat-o-Meter, which calculates percentlean in the carcass from the backfat measurement (taken2½ inches off the midline of the carcass at the 10th rib)

l~i~ analysis is based on the OTA commissioned background Paper “An Analysis of the Pork Grading System: Needed Adjustments, ” byJames Kieibenstein, Marvin Hayenga, Lauran Christian, Kenneth Prusa, Robert Rust (all associated with Iowa State University); and John Forrest,AlIan Schinckel and Max Judge with Purdue University (31).

Chapter 14—Food Quality: the Relevance of Food Grades ● 355

Table 14-1—Expected Yields of the Four Lean Cuts,by Grade, Based on Chilled Carcass Weighta

Grade Yield

U.S. No 1 . . . . . . . . . . . . . . . . . . . . . . . . 60.4 percent and over.U.S. No 2 . . . . . . . . . . . . . . . . . . . . . . . . 57.4 to 60.3 percent.U.S. No 3 . . . . . . . . . . . . . . . . . . . . . . . . 54.4 to 57.3 percent.U.S. No 4 . . . . . . . . . . . . . . . . : . . . . . . . less than 54.4 Percent.

*These yields will be approximately 1 percent lower if based on hot carcassweight.

SOURCE: U.S. Department of Agriculture.

and the loin muscle depth at that location. The percentlean in the carcass then serves as the basis for grading.

In summary, the current USDA pork carcass gradingsystem already is significantly out of step with industrysystems: changes in pork carcass composition broughton by new growth promotant technologies may causefurther divergence of government and industry gradingsystems. The USDA pork grades are primarily employedin Federal-State market news and price reporting for livehogs rather than in packing plants. This contrasts withthe USDA beef grading system, which is used exten-sively by beef packing plants for price reporting. In 1989,the American Meat Institute reported that 56 percent ofthe beef produced was quality-graded, and 65 percentwas yield-graded using USDA standards.

Changing Public Concerns and Expectations

Annual per capita consumption of red meat has beendeclining (figure 14-1) as poultry and fish have beensubstituted for red meat. The dramatic increase in poultryconsumption reflects the aggressive marketing of poultry

Figure 14-1—Per Capita Pork, Beef, and PoultryConsumption, United States, 1970-1989

100Pounds per personI

products, their lower relative price, and the response ofconsumers to fat and cholesterol concerns. Consumptionof all meat has trended upward overtime. Total per capitaconsumption of red meat and poultry reached a recordlevel in 1989 of 220 lbs. per capita, compared with 200lbs. in 1970 and 170 lbs. in 1960 (figure 14-1). Whileannual per capita consumption of pork varies cyclicallyin the United States, there has been little change in porkconsumption levels over the long term. Annual per capitaconsumption of beef, however, has declined dramati-cally; from 94.2 lb. in 1976 to 71.0 lb. in 1989.

Consumer preferences and attitudes regarding meatproducts have a major influence on meat and meat prod-uct demand. Consumer perceptions of product qualityand healthfulness, product convenience, cultural or eth-nic background, household age composition, lifestyle,and price all impact purchase decisions. Health concernsrelated to fat and cholesterol levels can affect some con-sumers’ attitudes and preferences regarding pork and beef.These have likely led to changes in demand for meatproducts. These shifts are difficult to measure accurately,and their impact on purchase patterns are not well doc-umented; it seems likely, however, that health and dietissues will be major factors influencing the future demandfor pork and beef. In addition, the need for better nutri-tional labeling on food products is receiving attention.Healthfulness of food products may be a major drivingforce in future food policy and consumer purchasingdecisions.

A series of Food Marketing Institute ( 18, 19, 20) con-sumer surveys document the evolution of factors influ-encing consumer food purchases. Taste is clearly theleading factor, with 90 percent of consumers surveyedin 1991 considering it very important, and 8 percentsomewhat important. Nutrition, product safety, and priceranked high, with 71 to 75 percent of shoppers consid-ering each very important.

At various times nutrition has not been so importantto consumers. In 1983, 64 percent of supermarket shop-pers were very concerned about nutrition, whereas in1987, 54 percent indicated this level of concern, and 40percent were somewhat concerned. In 1991, 75 percentof shoppers surveyed considered nutrition very impor-tant, with 22 percent considering it somewhat importantin food selection. In food selection decisions, concernabout overall nutritional issues is being replaced by con-cern for specific nutritional components, such as (in orderof decreasing importance) fat content, cholesterol level,salt content, calories, vitamin/mineral content, and pre-


servatives (20). Some of those specific concerns wereevident in the 1983 survey as well.

Preservatives and chemical additives used in foodpreparation have emerged as a major consumers concernin recent years. In 1991, 80 percent of shoppers surveyedconsidered chemical residues in foods a serious hazard(20). The presence of antibiotics and hormones in poultryand livestock feeds was ranked as the second most serioushazard (56 percent). Irradiation was viewed as a serioushazard by 42 percent of the respondents, closely followedby nitrites at 41 percent.

A recent National Research Council report indicatesthat Americans consume too much fat with consequentialnutrition-related health problems (41). A common methodto reduce fat in meat products is trimming. Perhaps amore efficient method is the production of leaner animals(41). The pork industry has attempted to reduce the fatcontent in fresh pork significantly through selectivebreeding (genetics) and diet and management practices(58). Technological advancements, such as growth prom-otants and application of genetic engineering, offer theopportunity to markedly improve body composition ofpigs before slaughter.

Consumers also are increasingly desirous of productuniformity. While level of desired quality varies amongconsumers, an individual consumer typically prefersproducts of uniform quality, as exemplified by the suc-cess of many fast-food establishments such as Mc-Donald’s, Wendy’s, Kentucky Fried Chicken, etc. Avisit to the local meat counter, on the other hand, illus-trates the lack of uniformity in pork products—presentgrading systems do not directly reflect product quality.

New Technologies and Implicationsfor Pork Grading

A young animal develops lean muscle more rapidlythan fat; but as the animal matures, fat accumulates morerapidly than lean. With increasing consumer concernsabout fat, it is advantageous for pork producers to shiftthe growth pattern away from fat accumulation to leantissue accumulation, particularly during the finishing phasesof production. In pork production, recombinant porcinesomatotropin (pST) and beta-agonist administration (dis-cussed in ch. 3), shifts the growth response from fataccumulation in pigs to deposition of lean tissue.

Porcine Somatotropin

As discussed earlier, carcass characteristics such asbackfat thickness and carcass weight currently determine

Table 14-2—influences of pSt or Ractopamine onProduction and Carcass Characteristics of Pigsa

pSTb Ractopamine c

(in percent) (in percent)Feed efficiency . . . . . . . . . . . +21 .1 + 12.7Average daily gain . . . . . . . . + 15.2 + 8.4Average backfat . . . . . . . . . . – 24.8 – 15.3Loin eye area . . . . . . . . . . . . . + 18.5 + 16.3Muscle mass . . . . . . . . . . . . . + 9.9 + 9.3Carcass yieldd . . . . . . . . . . . . -2 .4 + 1.4

‘Expressed as an increase or decrease as compared with controls,bSummary of 20 research trials.cSummary of up to 17 research trials.dHot carcass weight divided by live weight X 100.

SOURCE: D. Zimmerman, “Growth Enhancers,” Proceedings on New SwineGrowth Enhancers, lowa State University, 1989.

USDA carcass grade. Thus, changes in the carcass com-position that result from use of pST or beta agonists canimpact the present grading standards.

Zimmerman (70) summarized the available studies thatevaluated the impact of pST administration on lean meatproduction and feed efficiency (table 14-2). The mag-nitude of response of pST administration varies fromstudy to study and depends on frequency of administra-tion, pST dose level, time of administration, genotype,gender, energy intake, and protein and amino acid intake.

In 20 research trials evaluated by Zimmerman, pSTwas injected daily at dosages from 15 to 100 ug/kg bodyweight. Pigs weighed 40 kg or more at the beginning ofthe treatment period and were fed a diet containing atleast 16 percent protein. In many cases diets were sup-plemented with additional lysine. The average daily gainof pST-treated pigs was 15.2 percent higher than that ofcontrols. Feed efficiency was 21.1 percent higher.

The use of pST has a positive impact on most carcasscharacteristics. Average backfat thickness decreased by24.8 percent, loin eye area increased by 18.5 percent,and quantity of muscle mass increased by 9.9 percentwith pST administration. In general, the carcass percentlean, which was 52 percent for control pigs, was 64percent for pST pigs (4); the actual differential dependedon the level of pST administered. Studies have shownpercent lean increases of 15 to 25 percent. Dressing per-centage (carcass yield) decreased by 2.4 percent whenpST-treated pigs were compared with controls.

A rapidly accumulating body of data indicates thatadministration of pST to finishing pigs alters the yieldand distribution of wholesale cuts in the carcass. Weightand percentage of lean cuts are significantly increased(ham, 12 percent; loin, 11 percent; Boston butt, 12 per-


Photo credit: Terry Etherton, Pennsylvania State University

Comparison of pork loins that show the effect of pigs treated with porcine somatotropin (pST). Theloin-eye area of the loin treated with pST is 8 square inches; the control is 4.5 square inches.

cent; picnic, 9 percent) whereas weight and percentageof fatty cuts are reduced significantly (belly, 13 percent;jowl, 32 percent) (6, 12).

Proximate composition of the skeletal muscle exhibitsa dose-dependent decrease in lipid concentration and asmall but significant increase in protein concentrationwith pST administration (5, 6, 39, 47, 48). Cholesterolconcentration of the loin muscle is not altered, and onlyminor increases in percentage of polyunsaturated fattyacids are observed in the subcutaneous or intramuscularfat of pST-treated pigs (6).

Although data are sparse, little indication exists of anychange in mineral concentrations (22) or vitamin contentof muscle (46) with administration of pST. Therefore,the most significant effects of pST on nutrient compo-sition of edible tissues is reduction of neutral lipid con-centration. Several investigations indicate that cookingloss and sensory characteristics of fresh pork are notadversely affected by pST administration, unless veryhigh doses are administered (5, 6, 15, 22, 47, 64).

In a study that evaluated consumer reaction to pork frompigs treated with pST, nearly 1,200 consumers sampledbroiled loin chops from pST-treated and control pigs. Porkfrom pST-treated pigs was favored by 58.8 percent of theparticipants for its tenderness, by 60.6 percent for its juici-ness, and by 53.7 percent for flavor (49).

In another study, members of 114 Des Moines house-holds (414 people) compared boneless loin roasts frompigs treated with and without pST (17). Overall, no dif-

ference was noted in how individuals liked the two roasts.Roasts from pST-produced pigs were judged larger andleaner than control roasts.

pST On-Farm Study

Most studies of pST’s effects on pork production andcarcass characteristics have been conducted within anexperimental and control setting. The expected produc-tion responses to pST under normal farm conditions werestudied on 15 Iowa pork production operations (50) atIowa State University. Some pigs were grown to thenormal market weight (109 kg) while others were takento 131 kg before marketing.

The administration of pST had a dramatic positiveeffect on packer-determined carcass grades (table 14-3).Only 18 percent of control carcasses graded No. 1, whereas41 percent of the pST (109 kg) group and 69 percent ofthe pST (131 kg) group graded No. 1. Over 90 percentof the pigs administered pST graded a No. 3 or better,versus only 75 percent of the control hogs. Even thoughallowances were made for increased backfat with heavierweight pigs a substantial improvement in grade was notedwith pST use. However, dressing percentage (hot carcassweight as a percent of live weight) was depressed slightlydue to pST administration (table 14-4).

Beta-Agonists

Zimmerman (70) also summarized the large numberof research trials that have involved the use of ractopa-mine in finishing pigs (table 14-1). As with pST, re-

358 ● A New Technological Era for American Agriculture

Table 14-3—Effect of Porcine Somatotropin (pST)Administration on Pig Growth Performance

Control/109 kg pST/109 kg ST/131 kg

Treatment a (n = 15) (n = 12) (n = 13)

Start weight (kg) . . . . 69.3 69.0 69.3Final weight (kg) . . . . 109.3 111.5 126.3Gain (kg) . . . . . . . . . . . 40.0 42.6 57.4Feed (kg) . . . . . . . . . . 144.3 125.6 173.5Feed/Gain . . . . . . . . . . 3.6 3.0 3.0Average daily feed

( k g ) . . . . . , , . . , , . . 2 . 7 2.4 2.4Average daily gain

(kg) . . . . . . . . . . . . . 0.76 0.81 0.79acontrol/109 kg targeted for slaughter at 109 kg, a summary of 15 farmsaveraged over 533 pigs; pST/109 kg targeted for slaughter at 109 kg, asummary of 12 farms averaged over 373 pigs; pST/131 kg, targeted forslaughter at 131 kg, a summary of 13 farms averaged over 437 pigs.

SOURCE: K. Prusa et al., ‘Influence of Porcine Somatotropin (pST) onCarcass Characteristics of Pigs—A Summary of 15 ProducerTrials,” Journal of Animal Science 69:344, 1991.

sponses were found to vary from study to study. In generalthe trials utilized 20 ppm of ractopamine and at least 15percent protein in the diet, and all experiments werebased on starting weight of approximately 60 kg andending weights of 105 kg body weight. Averaged overall trials, ractopamine increased average daily gain by8.4 percent and feed efficiency by 12.7 percent whencompared with control pigs. Research of Veenhuizen etal. (67) and Anderson et al. ( 1 ) shows feeding beta-agonists increases growth rate and feed efficiency, de-creases backfat, and increases loin muscle size of pigs.

The use of ractopamine also has a positive effect oncarcass characteristics. Backfat was decreased by 15.3

percent, loin eye area increased by 16.3 percent, andmuscle mass increased by 9.3 percent. In general, carcasspercent lean increased from 51 percent to 57 percentwhen 20 ppm of ractopamine were administered (69).When lower levels were administered, response rateswere lower. Similarly to pST, ractopamine increases theweight and percentage yield of trimmed wholesale cuts(ham, 7 percent; loin, 6 percent) (36).

In contrast to pST, ractopamine increased carcass yieldby 1.35 percent; and beta-agonist use did not significantlyreduce the amount of intramuscular fat in lean tissue.Animals fed cimaterol (68) or ractopamine (36) had thesame intramuscular fat contents in their loin muscle ascontrol pigs. Lee et al. (33) found that ractopamine feed-ing had only a minor effect on fatty acid profiles inadipose tissues of finishing pigs, and Walker et al. (68)found no differences due to cimaterol treatment in thetotal saturated-unsaturated fatty acid ratio of the subcu-taneous fat. These researchers also reported that cima-terol had no affect on carcass fat firmness scores orintramuscular fatty acid profiles.

Little information about the sensory quality of porkfrom beta-agonist-supplemented pigs is available. GreaterWarner-Bratzler shear values (toughness) of the loin in-creased in pigs that received cimaterol treatment in therange of 0.50 to 1.0 mg/kg (28, 68). Effects of beta-agonists on pork quality may be compound specific (36)because ractopamine feeding had no effects on the ten-derness, juiciness, or flavor of fresh or cured pork.

In summary, pST and beta-agonist administration im-proves feed efficiency and average daily gain reduces

Table 14-4-Effect of Porcine Somatotropin (pST) Administration on Carcass Grades at a MajorCommercial Packer

Control/109 kg PST/109 kg pST/131 kg

Number Number NumberCommercial gradesa of pigs (percent total of pigs (percent total) of pigs (percent total)

No. . . . . . . . . . . . . . . . . . 80 (18) 117 (41) 295 (69)No. 2 . . . . . . . . . . . . . . . . . 115 (26) 83 (29) 76 (18)No. 3 . . . . . . . . . . . . . . . . . 142 (32) 65 (23) 39 (9)No, 4 . . . . . . . . . . . . . . . . . 76 (17) 15 (5) 11 (3)No. 5 . . . . . . . . . . . . . . . . . 34 (8) 2 (1) 4 (1)Total . . . . . . . . . . . . . . . . . 447 282 425aCommercial packer grades based on live weight and tenth rib backfat thickness:No. 1 = 0.80 in. or less (95-113 kg); 1.00 in. or less (1 14–122 kg); 1.20 in. or less (123 kg and up)No. 2 = 0.81-1.00 in. (95-113 kg); 1.01-1.20 in. (1 14-122 kg); 1.21-1.40 in. (123 kg and up)No. 3 = 1.01–1.20 in. (95-113 kg); 1.21–1.40 in. (1 14-122 kg); 1.41-1.60 in. (123 kg and up)No. 4 = 1.21-1.40 in. (95-113 kg); 1.41-1.60 in. (114-122 kg); 1.61-1.60 in. (123 kg and up)No. 5 = Over 1.40 in. (95-113 kg); over 1.60 in. (114–122 kg); over 1.80 in. (123 kg and up)NOTE: Percents may not add to 100 because of rounding.

SOURCE: K. Prusa et al., “Influence of Porcine Somatotropin (PST) on Carcass Characteristics of Pigs—A Summary of 15 Producer Trials,” Journal ofAnimal Science 69:344, 1991.


backfat thickness, and increases the carcass percent leanand the weight of the major boneless pork cuts. Carcassdressing percentage increases with beta-agonist use, butdecreases with pST administration. Both growth prom-otants show promise as methods to produce leaner porkcuts more efficiently. These changes have implicationsfor present pork carcass grading and payment systems.

Potential Parameters for AlternativeGrading System

USDA grades and grading criteria are rapidly becom-ing irrelevant for at least two reasons. First, the industrydoes not use USDA grades because they do not measurecharacteristics deemed important by industry. Second,advancing technologies, such as pST, will significantlychange the composition of pork cuts to leaner productsdesired by consumers. Current USDA grading criteriabased on backfat thickness and degree of muscling willnot be relevant since there will be little, if any, differencein these characteristics among products produced withthe new technology. For a grading system to be usefulnew criteria will be needed.

In determining potential criteria for use in alternativegrading systems, it seems logical to focus on those char-acteristics considered most important by the ultimate con-sumer of pork products, with some consideration of theintermediate customer and the pork processor. The goalof an evaluation scheme as it pertains to pork quality isto predict from characteristics of fresh meat the generalmerit and value of the cooked product. In purchasinghigh-value products, consumers will consider price aswell as such product characteristics as amount of leanversus fat and bone in the pork product; cholesterol lev-els; flavor, tenderness, texture, and firmness; degree ofmarbling; juiciness; color of the lean and fat; and aromaof the product. Moisture holding capacity is importantfor products to be cured or smoked.

External Fat

Both USDA and packer grades of pork are influencedlargely by the amount of subcutaneous (external) fat,which accounts for approximately 70 percent of totalcarcass fat (8). Until recently, external fat was trimmedto approximately ¼ inch on pork cuts at the retail level.The Pork Market Basket Study completed in 1990 at theUniversity of Wisconsin revealed that pork currently istrimmed to an average of only 1/8 in. of external fat.

Although trimming away undesirable external fat isone method of improving product quality and increasingconsumer appeal, it is less appealing to the retailer who

Photo credit: John Forrest, Purdue University

Grades for pork carcasses are based on a combinationof subjective visual appearance and measurement of fat

thickness (by simple ruler) and carcass weight. Fatthickness will not be a relevant criteria in the future.

suffers the trim loss. Fat is perhaps viewed even lessfavorably by the producer who stood the consequencesof inefficient gains of his animals (fat requires morecalories than lean). Furthermore, carcasses with exces-sive external fat are likely to contain more intermuscularor seam fat, which is difficult to locate and remove,particularly in large roasts. Intermuscular or seam fatlevels in excess of 20 percent are common in pigs; onaverage that type of fat represents 15 percent of carcassweight. Thus, trimming away of external fat deposits isa less than satisfactory solution to the fatness issue.

Lean-Fat Ratios

An accurate method of determining directly the totalfat percentage or lean-fat ratio of carcass products wouldbe valuable for both consumers and packers. Presentmeasurement procedures will be described in a later sec-tion. These techniques do not adapt well to the modern-


day rapid slaughter line. The Anyl-Ray procedure forassessing fat content of ground fresh meat samples iswidely used in meat processing and has a relatively highdegree of accuracy; however, it cannot assess fat contentof the intact carcass.

Intramuscular Fat

The relative importance of marbling (intramuscularfat) to product acceptability is not clearly established.Malphrus et al., (34) reported a closer relationship be-tween marbling and juiciness than between marbling andtenderness, although both exhibit a positive relationship.Further, marbling seems to be more important to palat-ability in fresh than cured pork and more important inchops than in pork roasts. However, marbling or intra-muscular fat generally is considered a factor affectingpalatability (7, 11, 53).

Cholesterol and Unsaturated Fatty Acids

Reduction of caloric content (fat content) of meat cancontribute to reduction of obesity in humans and possiblyimproved health. The fat component of meat (particularlysaturated fatty acids and cholesterol content) has beenimplicated in cardiovascular disease (23). More recently,red meat consumption has been linked to higher rates ofcolon cancer.

Muscle Quality

Problems of poor muscle quality continue to plaguethe pork industry. Pale, soft, and exudative (PSE) anddark, firm, and dry (DFD) muscle have been reportedfor 3 to 25 percent of carcasses in U.S. packing plants.Exudative pork has the tendency to lose water. It is im-portant to monitor this problem if our foreign markets(particularly that of color-conscious Japan) and our do-mestic market are to be maintained or expanded.

Tenderness

Objective muscle shear measurements such as the War-ner-Bratzler shear have been positively correlated withpalatability (tenderness) of cooked pork as well as othermeats (7). While there may not be a practical approachto obtaining this measurement on fresh carcasses, theremay be a need to include some measure of tenderness inthe grading process. In Denmark, shear force values haveincreased significantly with reduction in backfat and in-creased lean content. These changes have been signifi-cantly associated with a reduction in intramuscular fat.To date, there is no practical direct method of evaluatingtenderness in fresh meat or in the meat animal carcass.

Indirect indicators of meat tenderness such as color andtexture of lean are questionable, at best.

Nutrient Content

Nutrient content variation in pork cuts with a similarlean-fat ratio primarily reflects the PSE condition andthe extent to which nutrient-containing juices are exuded.For example, many nutritional elements are water solubleand may be lost during retail storage or cooking. Meyeret al. (37) examined B vitamin content and found greaterlosses from PSE muscle than from normal muscle. Nia-cin, however, was found to be higher in the final cookedPSE muscle. Biochemical differences in muscle metab-olism were postulated as the reason for these differences.Collection and analysis of the drip from normal and PSEchops showed losses of protein, potassium, calcium, andmagnesium per unit weight of lean were higher in PSEchops (16). Nutrient concentration of the drip was similarfor the PSE and normal chops, but twice as much dripfrom PSE chops meant greater nutrient losses from thePSE product. Such losses, however, represent a verysmall portion of total nutrients present in a pork chop,and the differences observed did not appreciably changethe nutritive value of PSE chops.

Flavor

Flavor is the most difficult to define of all the sensorytraits. The lipid composition and metabolism of fat pri-marily are responsible for flavor (56). However, lean isalso known to have important flavor components (9).Minimum quantities of fat necessary for “typical” flavorare not clearly defined, perhaps because juiciness be-comes a palatability factor at low fat levels before lossof flavor occurs. The lipid component of pork can leadto the development of off-flavors. The high degree ofunsaturated fatty acids in pork fat is the major reason forthe potentially greater rancidity of pork relative to beef.There are no commercially feasible technologies cur-rently available for measuring flavor. The primary tech-nique utilized presently is sensory panels.

Options for an Improved Grading System

There are a number of alternatives to the current USDApork grading system that warrant consideration. A fewobservations about the current situation and imminentchanges in the pork industry will lay the background forconsideration of possible changes in the pork gradingsystems. The current USDA pork grading system is noteffectively differentiating between carcasses that varywidely in value. Packers are not currently using the USDAgrading system for evaluating or pricing hogs. The packer


grading systems in use vary in the extent to which theydiffer from the USDA system. The inadequacy of theUSDA grading system will become more apparent asproducers begin using new growth promotant technologysuch as pST or beta-agonists.

Product characteristics valued by the consumer are onlypartially reflected in current grading systems. Fat contentof pork products is a key factor for consumers, and externalbackfat thickness is a key factor in current packer andUSDA grading systems. Fat content is related to caloriecontent, so calories are indirectly considered. While therecurrently are no grades for retail pork products, the labelingsystems on a limited number of branded, processed prod-ucts listing percent fat-free and calories serve the samepurpose. Cholesterol and saturated fatty acid content, andmuscle quality traits (color, tenderness, texture, etc. ) con-sidered important by consumers are not reflected in currentgrading systems. Technologies to measure these variablesare not curently available or cannot be economically in-corporated into the fast line speeds, etc., of the modempacking plant. (See box 14-A.)

Ideally, grading systems should provide recognizablehomogeneous groups of products based on highly valuedconsumer characteristics that are accurately and effi-ciently measured. This would facilitate better informedpurchasing and pricing decisions, and market feedback.Making producers and processors aware of value differ-ences via the grading and pricing and market informationsystem should improve industry resource allocation.

New growth promotants being developed for use inpork production are likely to change the compositionalrelationships within the pork carcass and the resultingconsumer products. These changes will primarily impactlean/fat/bone relationships rather than sensory propertiesor eating quality. The compositional changes will ne-cessitate further adjustments in current grading systemsto provide accurate grading, equitable pricing, and ac-curate price reporting of pigs and their products or theelimination of grades altogether.

Several changes in the grading system that might im-prove industry performance are considered. Potentialbenefits and costs to consumers and industry participantsare briefly analyzed.

Option l—Status Quo

Maintain the status quo in the USDA grading system,with a single measurement of backfat depth as the pri-mary indicator of grade. This would be the least expen-sive alternative for the government and pork industry.

Since packers currently do not use the USDA gradingsystem, the impact on industry performance would belimited to the market information system that relies onUSDA grades for price reporting. The Federal-State mar-ket price information based on USDA grades will becomegradually less discriminating and useful, as an increasedproportion of carcasses varying widely in value wouldbe graded U.S. No. 1. The Federal-State Market Newsservice has already deviated from using the USDA grad-ing system by splitting their U.S. No. 1 grade carcassprice reports into separate price reports for hogs with lessthan 0.8 inches of backfat and more than 0.8 inches ofbackfat.

Use of growth promotants will further widen the cur-rent disparity and variability between carcass grade andcarcass value, especially in the highest grade. Differencesbetween packer grading standards and USDA gradingstandards will likely continue to widen if packers con-tinue to adapt their grading and evaluation systems tothe changing characteristics of the market hog popula-tion. Several different packer grading and evaluation sys-tems will continue to coexist, with differences in methodand accuracy of evaluation. Producers will continue tohave difficulty comparing alternative packer price quo-tations based on different grading systems. This wouldprimarily affect producers’ abilities to assure getting thebest price for their hogs, and would have a small impacton resource allocation decisions by pork producers. Gradeswill continue to offer no useful information on lean qual-ity or fat content to consumers, but individual packergrades and pricing systems likely will continue to offersome incentives for leaner hogs. However, many packergrading systems may have to be changed to reflect moreaccurately the changes in carcass composition from pigsproduced using new growth promotants. The USDA gradeswill be even less able to reflect relationships betweenvalue characteristics and value. At the extreme, USDAgrades could be rendered highly ineffective.

Option 2—Develop Grades Based on Lean-FatComposition and Quality

Develop pork grades designed to reflect lean-fat com-position as well as product characteristics most highlyvalued by the consumer. Use these grades for consumerproducts as well as at the packer level. Such grades mightdistinguish product groups differing in eating quality(tenderness, texture, freedom from PSE, freedom fromodor, and color) and composition (percent lean, caloriesper ounce, etc.). There could be a separate quality grade,or a minimum quality standard for each composition grade.


Box 14-A—Technology To Evaluate Pork Carcasses or Procuts

Some 50 years of research and development has gone into the grading and classification of pig carcasses.Along with visual assessment and direct measurement of various fat and lean parameters with grids and metalrulers, the industry now has several highly sophisticated electronic techniques with which to measure economicallyImportant characteristics of pork carcasses or products. Some of these await only the final stages of developmentbefore they can be applied commercially.

Subjective Visual Assessment and Ruler/Grid MeasurementsCurrently, grades for pork carcasses are based on a combination of subjective visual appraisal of muscle

thickness and objective measurements of fat thickness and carcass weight. In reality, most carcasses that aregraded are subjectively evaluated by trained personnel However, actual measurementt of fat thickness at somepoint on the midline of the split carcass often is done with a simple ruler. the correlation of 10th rib backfat depthwith quantity of fat-free lean mass is generally low (-0.27), but the measure is much more highly correlated withpercentage fat-free lean mass (-0.56) (42). Combining measurements of the cross-sectional area of the loin muscleat the 10th rib with measurement of fat depth at the 3/4 point over the loin muscle significantly improves theprediction of either fat-free lean mass or percentage fat-free lean mass.

Carcass and cut DissectionThe standard to which most techniques for carcass

evaluation are compared is the complete dissection ofat least one side of the carcass into lean, fat, bone,and skin followed by chemical analysis of the soft tis-sues to calculate either a fat-free lean mass or a fat-standardized lean mass. In many instances the majorprimal cuts (ham, loin, belly, shoulder) are dissectedindividuality in order to determine changes in compo-sition within the carcass that could be due to breed, orthe utilization of growth stimulants or repartitioningagents. This is not practical in current commercialslaughter plants.

Carcass and cut Grinding and chemical AnalysisGrinding of the whole side or entire carcass fol-

lowed by chemical analysis is sometimes utilized todetermine composition under research conditions. whilethis technique reduces the labor that would be requiredfor full dissection, it is very costly because none of thetissues can be salvaged for human consumption. An-other disadvantage of this technique is that the com- Photo credit John Forrest, Purdue University

position of the edible soft tissues and the skeletal The Fat-0-Meter is an optical probe that directly sensesstructures cannot beseperately determined. Like car- reflected light to determine tissue boundaries.cass and cut dissecttion, this too is not practical forcommercial slaughter plants.

Optical and Mechanical Fat-Lean ProbesThe Hennessy Grading Probe, Fat-o-Meter, Anatech PG-1OO, and Tecpro PG-200 are optical probes that

directly sense reflected light to determine tissue boundaries. Accuracy levels of the grading probes in predictingpercentage lean vary depending on the probe sites and combinations of parameters.

Mechanical-Pneumatic Assessmentt of ConfirmationAn electro-pneumatic mechanical system measures the width of hams and loin. These measurements are

combined with fat depth determined on the midline. This system is considerably more complex and expensive thanan optical probe.

Chapter 14—Food Quality: the Relevance of Food Grades .363

Potent/a/ Technology for Measuring Composition of Pork Carcasses and Pork ProductsMagnetic Resonance Imaging and Nuclear Magnetic Resonace Spectroscopy

Magnetic resonance imaging (MRI) utilizes elec-tromagnetic signals induced by a strong magnetic fieldto map and image fat and lean tissues. This technologyis currently very expensive to purchase ($225,000 ormore) and requires special shielding. It is slow and notcurrently adaptable to modem day slaughter plants.The high correlations with lipid (0.965), water (0.995)and protein (0.995) content from MR spectroscopy andthe high resolution obtained from MRI images suggestthat this technology could be used in research to re-place time consuming and expensive carcass dissec-tion. To be effective in commercial application, furtherresearch and development to reduce the cost and in-crease the speed of operation would be required.

x-ray computed TomographyCAT scan or X-ray Computed Tomography pro-

duces a two-dimensional cross-sectional image of thecarcass. A CAT scan of live animals has been shownto give highly accurate predictions of pork carcass com-position without significant biases with respect to gen-der, breed, or live weight (55). The Norwegian MeatMarketing Board plans to use this technology to replacecarcass dissection in the validation of other live animaland carcass grading instruments. High cost and theslow rate of data capture make this technology currentlyimpractical for consideration in online applications.

Photo credit: John Freest, Purdue University

Magnetic Resonance Imaging is a potential technologyfor measuring pork carcass composition by usingelectromagnetic signals to map and image fat and

lean tissue.

Video Image Analysis of Conformation and Fat DepthVideo image analysis offers the possibility of objectively measuring the shape and thickness of pork carcasses,

and could be combined with lean-fat probe data to improve predictive accuracy. In Denmark, a classification centerhas been developed for beef carcasses that uses video image analysis combined with an optical probe system.Tecpro, a company in Germany, is developing a similar system for pork carcasses. Costs for this system are difficultto determine at this point. Speed of operation should be limited only by computer capability for image processing.

Bioimpedance AnalysisBioimpedance analysis (BIA) exploits the conductivity differential between the fat-free mass and fat to measure

carcass fatness. As carcass fatness increases, the impedance to the flow of electricity increases. BIA has been shownhighly accurate in predicting the fat-free soft tissue content of Iamb caresses (27). Swantek and coworkers (61) reportedthat BIA accounted for 64 percent of the variation in fat-free mass in chilled pork carcasses. This system, as currentlystructured, would be difficlt to use in the context of current Iine speeds of many packing plants.

UltrasoundReal-time ultrasonic imaging devices have the ability to produce cross-sectional images at various locations

in either the live animal or carcass. An image of the cross-section of the loin at the 10th rib can be used to obtainmeasurements of fat depth and loin muscle area. From this a model can be developed to estimate either the weightor percentage fat standardized lean mass. This technique may be useful in evaluating composition of seedstockanimals or for evaluation of market animals to determine optimal market weight. With proper engineering andadaptation, ultrasound also may be useful in evaluating carcasses on the slaughter line.

SOURCE: Office of Technology Assessment, 1992.


Including eating quality characteristics as grading cri-teria could make the pork grading system more useful atthe consumer level. Unfortunately, few such character-istics are amenable to reasonably accurate and efficientmeasurement under commercial conditions. And it is notclear what quality measures would reflect characteristicsconsumers consider important but cannot visually eval-uate themselves.

The cost and difficulty of implementing compositionor quality grades beyond percent lean in ground porkmight be particularly oppressive for small processors orretailers who do a small amount of meat processing.Mandatory label or grade information thus could havesome undesirable structural implications. On the otherhand, providing that information could level the playingfield between small processors and larger retailers andprocessors with advertised brands. Further, reducing con-sumer uncertainty regarding any important quality char-acteristics by having a grade carry through to the consumerlevel could enhance consumer demand for pork products,and provide signals regarding undesirable quality to hogproducers and pork merchandisers, which could stimulatequality improvements.

The technical feasibility of quality grading is a criticalissue. Without a clear, pressing quality problem ad-versely affecting domestic or export demand, the poten-tial benefits may not be large enough to justify this optioneven if the technical problems could be overcome. Theprice reporting system necessarily would become morecomplex as quality and composition differences wouldhave to be reflected in price reports, requiring significantadministrative costs and education of marketing systemparticipants.

Option 3—Require Standardized Grading andMeasurement Systems

Require packers to use standardized grading systemsand a standardized effective measurement technology.Use that system for market price reporting.

This would be unpalatable for packers who usually areextremely independent and negative toward more gov-ernment intervention in their operations. Standardizedgrading systems would make price reporting easier andmore accurate, and facilitate comparisons of grade-re-lated packer bids or hog prices for producers. However,this approach would not allow individual packers to ad-just to any special considerations relevant to their cus-tomers or suppliers. Moreover, USDA grading systemshave been notoriously slow to change when conditionswarranted it, and the same might be true of any standard

grading system. Small packers may find it difficult tocompete if needed changes are expensive to implement.

Greater equity among producers may be facilitated bythese changes. Other economic benefits are in the formof faster industry adjustment to consumer wishes andimproved resource allocation and efficiency in the longrun. The costs would be incurred in the short run, pri-marily by packers (especially small packers) and pro-ducers of “poor quality” hogs. Establishing a mandatorysystem would involve significant research and develop-ment costs by the USDA and packers (and subsequentprocessors and merchandisers of pork products if thequality and composition grades would be carried throughto the consumer level). The added operating costs couldalso be significant. Standardization across all packers andmerchandisers would certainly improve the accuracy andease of acquiring price reports related to the USDA grad-ing system, but the complexity of the system would alsobe increased significantly.

Option 4—Use Percent Lean as USDA GradeCriteria

More extensive use of lean-fat probes to predict carcasslean percent suggests that percent lean (based on loinmuscle depth and backfat thickness, off-midline) ratherthan the current percent-lean cuts (primarily based onmidline backfat thickness) is a grading criterion more intune with the measurement technology becoming dom-inant in the pork industry. If the USDA simply basedgrades on percent lean without tying particular backfator loin depth measures to any numerical grades (e. g., 52to 53 percent lean rather than U.S. No. 1) the graderelationships would be less apt to lag behind changes inthe hog population.

The percent-lean measure, which is the common stan-dard for carcass evaluation by meat scientists today, hasone flaw. It does not reflect the fact that lean from a loinor ham has a different market value than lean from an-other part of the animal. If the hog population has sig-nificant variability in the proportion of carcass lean comingfrom various parts of the animal, those differences invalue would not be accounted for in a grading and pricingsystem based on (total) percent lean.

However, this system might be superior in value dis-crimination to some packer systems now in use, andwould be compatible with the probe technology currentlyused by several large packers. Further, the percent-leancriterion at the carcass level would be consistent withthe lean-fat composition information that many consum-ers demand for pork products.


Significant administrative costs would be required toestablish new grades and to implement the price reportingsystem. Price reporting might be difficult for packers notusing probes, but current measurement systems could beadapted to the percent-lean criterion. If slightly less ac-curacy in grade reporting is acceptable, it probably wouldnot be necessary to require use of probes for this systemto be workable. If probes were required, this would in-volve significant transition costs for many packers.

Option 5—Abolish the USDA Pork GradingSystem, and Use Percent-Lean DescriptiveTerms for Classes of Market Hogs inGovernment Price Reporting

Currently, the USDA grading system is used only bythe Federal-State Market News Service in providing themarket classes for price reporters to use. Many packersalready are using the percent carcass lean as their basisfor market hog grading and evaluation; others have notadopted that system, often because of perceived problemswith the probe measurement system or because their ownsystem is considered adequate. Asking packers to shiftto a new USDA grading system would involve significanttransition costs to packers not using a percent-lean probesystem, and more market costs for packers currently us-ing those systems. If packers do not use USDA gradesnow in their grading and evaluating systems, a high like-lihood exists that they would continue to use their ownsystems, which they have tailored to their specific needs,even if the USDA system was improved. In addition,USDA grades require significant time and administrativecosts to promulgate, and may in the future lag behindpractices used in the industry. These costs can be avoidedby eliminating official grades. Instead, prevalent industryterminology (weight and percent-lean classes) could beused to report prices by government price reporting agen-cies, in consultation with the users of the price reports.This could be done with much less administrative cost,and retain greater flexibility to change with industry prac-tices and technology. Since many hog producers may notbe familiar with the percent-lean terminology, price re-porters could use percent-lean ranges and correspondingbackfat ranges with which farmers are familiar in pricereporting for a transition period.

The benefits of this system would be the lower costand greater adaptability to changes in the market hogpopulation and measurement technologies, due to re-duced bureaucracy involvement; and a better basis forgovernment price reporting. It would encourage themovement by many packers to have their prices moreaccurately reflect carcass merit. The costs would in-

clude those necessary for government agencies to developcomparable percent-lean and backfat measurements foruse in translating prices paid on the basis of noncon-forming grading systems into prices for the percent-lean equivalent classes. Also, the lack of uniformityof packer grading and evaluation systems would con-tinue, with attendant problems for producers in com-paring packer bids based on different systems. However,the increased use of percent-lean systems should grad-ually lead to easier comparisons.

ConclusionsMany packers are shifting to probe measurement sys-

tems where their grades and prices are based on estimatesof carcass lean percentages. Since these estimates are notbased solely on backfat, the USDA could shift to carcasslean percentage as the basis for both grade and pricereporting. However, it does not seem likely that such achange will prompt many pork slaughter processors toadopt the USDA grading system, since many of themhave their own system already developed and adapted totheir needs. Moreover, changing internal evaluation sys-tems is costly.

Grading or labeling the quality of lean would appeardesirable in pork products and carcasses. However, thisseems impractical at this time due to the absence ofcommercially feasible measurement technology. Nutrientcomposition or similar labeling of fat content, calories,fatty acid profiles, or cholesterol content for pork prod-ucts at the consumer level would provide informationthat could enhance demand or provide clearer signals toproducers and processors regarding consumer prefer-ences. Some branded pork processors currently are pro-viding some of this information. In addition, some industryconsumer information programs are beginning to movein this direction. Unfortunately, the commercially avail-able technology for meat-quality evaluation is primarilyadaptable to ground meat, and fat content is more easilymeasured than some other characteristics. Adapting thisapproach to highly variable intact fresh and processedpork products could add relatively significant capital andlabor costs, especially in small processing and merchan-dising operations. If effective quality measurement tech-nology were developed, the quality measurements andinformation provided would need to be incorporated intoproduct evaluation and pricing throughout the marketingsystem. Then, consumer reactions to differences in qual-ity would be effectively transmitted through the systemand affect prices paid to producers.

Several promising technologies that might provide ac-curate estimates of lean/fat composition of carcasses or


pork products, including products affected by the newgrowth promotants, are in the research and developmentstage. This research could be encouraged. These tech-nologies, when commercially feasible, could be incor-porated with grading programs that focus on carcass percentlean. Classifying pork carcasses via carcass lean per-centages could be initiated with the view toward addinglean-quality information at a later date. When a com-mercially feasible lean-quality measurement becomesavailable, pork carcass grades could be determined bycarcass percentage lean and quality of the lean. Dramaticadjustments in reporting of pork prices would not beneeded to incorporate quality information with carcasspercent-lean information.

Finally, the descriptive terms (currently primarily USDAgrades) used in government price reporting could bechanged to percent-lean classes, with related backfatmeasures reported for a transition period. In the longerterm, quality information can be added when commer-cially feasible. When fully implemented, price would bereported by percent-lean and lean-quality classes or mea-surements. If there is a need for a USDA grading system,it could be based on carcass percent lean, measurements(not grades), with lean-quality information added whenit becomes commercially feasible to do so. However,packers are unlikely to use an improved voluntary sys-tem. Price reporting agencies should be able to adoptpercent-lean ranges for reporting prices with less bu-reaucratic cost and more flexibility than would be thecase for changes of grading systems. Consequently, astrong argument can be made for abolishing the USDApork grading system. This is essentially what has beenhappening de-facto in the pork industry over the lastdecade.

THE FRUIT AND VEGETABLEGRADING SYSTEM2

The U.S. Department of Agriculture has a long-estab-lished system for fruit and vegetable grades. Standardsused to determine a grade include “attributes,” such assize, quality, and condition, and their related “toler-ances. ” For example, one attribute for fresh market po-tatoes is “free from sunscald. ” The tolerance for thisattribute is “no more than 10 percent defects at the pointof shipping. ” This attribute and its tolerance are usedalong with other attributes and tolerances to designate

grade. Attributes are based on sensory characteristics,such as touch, sight, and taste, as well as shelf-life con-siderations, palatability considerations, or some combi-nation of these factors.

Challenges have been raised to the Federal gradingsystem. Some question grades that do not explicitly in-clude health and nutritional factors. Others argue that thecurrent sensory-based grade attributes indirectly encour-age the use of chemicals in production, so as to minimizeblemishes and ensure vibrant skin-color.

Consumers are increasingly concerned about the useof chemicals or chemically based ingredients in the pro-duction and preservation of our food supply, both forenvironmental and health reasons. There is concern thatchemicals used in the production process may damagethe environment and that chemical ingredients in or onfood may impair human health, perhaps in ways yetunknown to the scientific community.

Consumers increasingly want to be more fully in-formed about choices available in the marketplace. Givensuch information consumers will, through their pur-chases, indicate levels of nutrition they want, what levelsof pesticide residue they are willing to tolerate, and whatlevel of blemishes they are willing to accept.

Thus, some alternative or revised set of grade attributesmight be more socially desirable than current sensory-based attributes. The natural question that arises is whetherit is more feasible and desirable to incorporate additionalor modified attributes, such as nutrition information orother “nonsensory “ information, into current standards;or to identify conceptual alternatives to the current sen-sory-based standards. This case study focuses on the useof sensory and potential alternative grading attributes forfruits and vegetables.

Fruit and Vegetable Production andConsumption

The U.S. fruit and vegetable industry accounts for 8.7percent of the market value of all agricultural productssold in the United States (table 14-5). Fruits, nuts, andberries account for 5.2 percent of the market value whereasvegetables account for 3.5 percent of the market value.Reflecting their high market value per acre of production,fruits, nuts, berries, and vegetables account for only 1.8percent of total U.S. acreage.

zmi~ ~dy~is is b- on the OTA co~ssion~ paFr “Assessing Federat Grade Criteria for Fruits and Vegetables, ” by Thomas Sporleder) Rebecca

Boerger, Mark Bemett, James Hoskins, Eugene Jones, Timothy Rhodus, Kuti Wiese. and Carl Zulauf, all associated with the Ohio State University(59).


Table 14-5—Market Value of Agricultural Products Sold and Total Acreage, United States, 1987

Total fruits,nuts and % of % of

U.S. total berries total Vegetables total

Market valueof agriculturalproducts sold . . . . . . . . . . . . . . . . . . . . 136,048,516 7,084,818 5.2 4,698,083 3.5

($1 ,000)Acreage (acres) . . . . . . . . . . . . . . . . . . 282,223,880 4,404,946 1.56 3,467,563 1.23

SOURCES: 1987 Census of Agriculture AC87-A-51, U.S. Department of Commerce, Bureau of the Census, November 1989 and Fruits and Nuts Situationand Outlook Report Yearbook, U.S. Department of Agriculture, Economic Research Service, Washington, DC, November 1990,

Table 14-8-Top 12 Commercial Shipping PointCommodities, Fresh Inspected Shipments, Fiscal

Year 1990(Reported in cwt.)a

Commodity Tonnage

Potatoes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Tomatoes . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . . . .Apples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Onions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Grapefruit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Grapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Oranges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Cantaloupes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Pears . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Lettuce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Peaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Plums . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

100,805,47725,645,86719,313,89115,667,91613,628,5879,166,9987,976,8607,483,4636,790,2356,751,0396,071,9655,179,140

alnspected fresh product only.

SOURCE: Fresh Products Branch, Annual Report for Fiscal Year 1990,AMS, U.S. Department of Agriculture, Washington, DC, 1990,and ”Fruit and Vegetable Shipments:Market News, AMS, USDA.

In terms of tonnage at commercial shipping points,the most significant commodity among fruits and vege-tables for fiscal year 1990 was potatoes (table 14-6).Tomatoes were second in volume but with only aboutone-fourth the volume of potatoes. Apples were the thirdlargest commodity volume-wise with about three-fourthsthe volume of tomatoes.

Apples, oranges, potatoes, and tomatoes were chosenhere for specific case analysis. These commodities wereselected because they represent a wide variety of gradestandards, have relatively high per capita consumption,and figure significantly in today’s food markets. Annualvalue of production for these commodities ranges from$1 billion for apples to nearly $3 billion for potatoes.Annual consumption per capita for the four commoditiesranges from about 15 pounds for oranges to over 127pounds for potatoes. Since 1970, per capita consumptionof all fruits and vegetables in the United States has trendedupward.

Table 14-7—Number and Type of USDA Grades forFruits and Vegetables

Number ofgrade

Category standards

Fruits for fresh market:Wholesale market . . . . . . . . . . . . . . . . . . . . . . .Raw products for processing . . . . . . . . . . . . . .

Fruits for processing . . . . . . . . . . . . . . . . . . . . . . .Canned fruits . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Dried and dehydrated fruit ., . . . . . . . . . . . . . . . .Frozen fruits , . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vegetables for fresh market:

Wholesale market . . . . . . . . . . . . . . . . . . . . . . .Consumer retail market . . . . . , . . . . . . . . . . . .

Vegetables for processing . . . . . . . . . . . . . . . . . .Canned vegetables . . . . . . . . . . . . . . . . . . . . . . . .Frozen vegetable . . . . . . . . . . . . . . . . . . . . . . . . . .

291515361421

5812243926

SOURCE: U.S. Department of Agriculture, Agricultural Marketing Service

USDA Grade Standards

Current grade standards for fruits and vegetables areadministered by the U.S. Department of Agriculture(USDA) under authority of The Agricultural MarketingAct of 1946. The purpose of these sensory-based gradestandards is to encourage uniformity and consistency incommercial practices related to the quality, quantity, andcondition of agricultural products shipped in interstatecommerce.

Use of USDA grade standards is voluntary. However,if a firm decides to use grade standards and designatethe U.S. grade on a package label, they must use USDA’sgrade standards.

Fruit and vegetable USDA standards can be groupedinto categories (table 14-7). Most grade standards forfresh fruit and vegetables pre-date 1960. Grade standardsfor processed fruit and vegetables generally are of morerecent vintage.

At the commercial shipping point nearly 90 percent offresh potatoes and approximately 77 percent of fresh


Photo credit: Grant Heilman, Inc.

Voluntary sensory-based grades encourage uniformityand consistence of agricultural products. At least 75

percent of fresh tomatoes are graded.

tomatoes are graded. Only about one-third of fresh applesand around one-fifth of the fresh oranges are graded.

At the raw product processing stage, nearly 80 per-cent of potatoes were graded while only about 5 percentof the tomatoes were graded. Approximately 86 per-cent of the oranges and nearly 30 percent of apples aregraded.

Grading attributes can be broadly divided into threecategories: size, quality, and condition. Size of a com-modity can be described by diameter, length, weight,and uniformity (65). Quality factors are defined as “thecombination of the inherent properties or attributes of aproduct which determines its relative degree of excel-lence” (26). In general, quality factors refer to the at-tributes of a commodity that remain permanent once thecommodity is harvested. Examples include variety,cleanliness, shape, and maturity. Defects in quality canbe divided into four classes:

1.2.3.4.

fungal injuries,insect injuries,mechanical injuries, andother defects (ill shaped, undesirable color, sun-burn, growth cracks, and dirt) (65).

Condition refers to

the relative degree of soundness of a product that mayaffect its merchantability and includes those factors thatare subject to change after harvest. Condition (i.e., ripe-ness or freshness) may reflect age, improper handling,storage or lack of refrigeration. . . . (10).

Along with attributes, tolerances are used to determinegrade. Tolerances are legal limits of acceptable size,quality, and condition attributes. They generally are statedin percentage terms, and can vary by product, use, orsize of the individually packaged product. The tolerancesfor U.S. No. 1 apples illustrate the variety of forms thattolerances can take:

1. no more than 10 percent of apples with quality andcondition defects including no more than 2 percentof apples with decay, 2 percent with internal break-down and 5 percent with wormholes; and

2. the apples cannot be further advanced in maturitythan generally firm ripe.

Size, quality, and condition attributes, as well as tol-erances, differ for different commodities, they also varywith market destination. In general, attributes and tol-erances are more strict for fresh produce destined for thefresh market than for fresh produce destined for the pro-cessing market. For example, U.S. Extra No. 1 freshpotatoes at the wholesale level must be firm, a conditionattribute. In contrast, U.S. No. 1 potatoes for processingat the wholesale level have a comparable condition att-ribute of moderately firm. Similarly, the retail consumergrade for fresh produce tends to be more strict than thewholesale standard, To illustrate, for U.S. No, 1 to-matoes at the wholesale level, defects can total no morethan 10 percent at shipping points or no more than 15percent en route or at the destination point. On the otherhand, defects can total no more than 5 percent for U.S.Grade A fresh tomatoes at the consumer retail level.

Most sensory attributes are measured by inspectorsusing their sense of touch, sight, and smell. Many tech-nologies, however, have been developed to measure sen-sory attributes of foods. A considerable amount ofautomation and computerization is occurring in this area.For example, up-to-date mechanical harvesters used inthe harvest of processing tomatoes are computer equippedand give a preliminary objective color assessment that ismore accurate than previous human, subjective evalua-tion. Advancements in computer technology are leadingto fully automated color and size measurements that willpermit accurate sensory evaluation of products from thefield to the retail store, with perhaps the need for onlylimited human spot-checking (38). One large fruit pack-


Photo credit: Grant Heilman,

Most sensory attributes are measured by inspectorsusing their sense of touch, sight, and smell. Inspectors

grade nearly 90 percent of all fresh potatoes.

Inc.

ing house in Florida recently added computerized equip-ment that weighed, optically scanned for dimensions,and used an infrared camera to determine fruit size. Usedtogether, the processes are able to determine density andcull fruit that is internally damaged by freezing (63).

Conceptual Considerations of GradeStandards

A grade is assigned to fruits and vegetables by applyingprespecified standards to a random sample of the com-modity being graded. Three conditions must be met foran attribute to serve as a grade standard. First, the quality,condition, and size attributes stated in the standards mustbe observable or measurable. If an attribute cannot beobserved or measured, then it is not possible to includeit in a grading standard. Second, information about theattribute must exist and be available to the public.

Third, the attribute must vary among individual spec-imens of the commodity. If the attribute does not vary,then including it in the grading standard would provideno information. The use of tolerances on quality, con-dition, and size attributes reflects this variability. Tol-erances allow for a sample to obtain a given grade eventhough not all specimens in the sample have the samequality, condition, and size attributes.

Basing grades on the presence and quantity of chemicalresidues and nutrient value, for example, mandatesknowledge about chemical residues and nutrient values.If these two attributes vary among samples of a com-modity, and are measurable, they can be incorporatedinto or substituted for existing grade standards. The nexttwo sections address the measurement and variability ofnutrient and chemical residue attributes in fruits and veg-etables. Their purpose is to introduce the conceptual basisfor two different fruit and vegetable grade standards—one based on nutritional content, the other on chemicalresidues.

Nutritional Attribute Measurement

Cost-effective techniques that provide information ona timely basis do exist for several nutrients (box 14-B).The willingness of consumers to pay for this informationcould broaden the range of cost-effective techniques fornutrient analysis. An alternative approach is to determineif sensory characteristics also convey information aboutnutritional characteristics. In other words, can sensorygrade attributes be used to evaluate the nutritional char-acteristics of fruits and vegetables? This question is ad-dressed in the next section.

Nutritional Attriutes Variation

Knowledge Gaps

While much is known about the nutritional value offruits and vegetables, inadequate data exist in manykey areas (3). (See tables 14-8 and 14-9. ) Little or nodata exist for 9 nutritional components of fresh fruits,14 nutritional components of frozen or canned fruits,18 nutritional components of fresh vegetables, and 12nutritional components of frozen and canned vegeta-bles. This lack of information is due in part to theminute quantities of some nutritional components offruits and vegetables, and uncertainty as to the exactnature of these components’ contribution to human nu-trition. For example, the fat soluble vitamins (A,D,E,and K) can be accurately assayed and quantified inmost samples. However, quantities of these vitaminsmay be present in bound form or other forms not uti-lizable or under-utilized in human physiological proc-esses. Thus, their overall role in human nutrition isuncertain. Additional research on nutrition of fruits andvegetables is needed before all nutritional attributescan be included in a grading standard.


B0X 14-B-Technology for Nutrient Attribute Measurement of Fruits and Vegetables

Nutritional attribute of food in general cannot directly be sensed by consumers. Consequently, scientificmethods and instruments are needed to measure these attributes. Currently available methods and instrumentsare numerous and sophisticated.

Currrent Methods for Determining Nutrient ContentIn addition to water, fruits and vegetables usually contain significant amounts of most or all types of carbo-

hydrates, such as sugars, starches, and fiber. They also contain vitamins (notably vitamins A and C) and smaller,but nutritionally significant, amounts of minerals and protein. Specific methods of analysis exist for each nutrientcategory. These methods have varying degrees of accuracy, simplicity, and cost.

For carbohydrates, analytical methods indclude observing color changes, microbial assays, enzymatic assays,and chromatography. Chemical extraction procedures will use one of these methods to extract and differentiatesimple sugars, complex sugars, starch, and dietary fiber for analysis. A technique recently developed for quantifyingfiber is enzymatic degradation.

Protein composition generally is determined by empirical techniques. Proteins are decomposed into constituentamino acids by hydrolysis (a decomposition procedure using water). These amino acids are isolated by chroma-tography (a technical procedure that separates substances based on factors of size, electrical charge, or affinityfor another compound).

Analysis of mineral components in plants is challenging because minerals generally are present only in minutequantities. Traditionally, quantification of mineral has involved analysis of the inorganic ash residue obtained fromburning a plant sample. Mineral ash from fresh fruits ranges from 0.2 to 0.8 percent of the weight of the entire fruit,and the quantity of ash generally is inversely related to moisture content. Mineral content in vegetables is usually higher,at about 1 percent. The oldest analytical techniques applied to mineral ash forms of spectroscopy (xray fluorescenceabsorption.) Spectroscopy is the observation and measurement of radiation emitted from chemical elements after theiratoms have been excited in a certain way. Each element has a characteristic pattern of wavelengths following excitation(45).

Assessment of Current Techniques and MethodsBeecher and Vanderslice have cattegorized methods of nutrient analysis based on their level of accuracy and other

attributes as adequate, substantial, conflicting, and lacking. Their criterion for accuracy is the production of ananalytical value within 10 percent of a true value when a nutrient is present in food at a nutritionally significant level,defined as greater than 5 percent of the Recommended Daily Allowance (RDA) per standard serving or daily intake,whichever is greater. Many methods fail to meet this criterion (45).Adequate and “substantial” methods are highly accurate, Speedy, and modest in cost-defined as less than

$100 per test. “Conflicting” and “lacking” methodologies are unlikely to render valid results under conditions ofroutine analysis.

Although problems exist with accurate assessment of nutritional components of fresh fruits and vegetables, analysisof fresh produce is less Problematic than is analysis of processed foods. Adequate and substantial methods of analysisalready exist for many nutrients in fresh fruits and vegetables.

Developments in Nutrient CompositionMeasurementTechnological advances are improving the ability to accurately and expeditiously measure nutrient components.

An example is flow injection chromatography (60). it permits numerous rapid sequential analyses and is appropriatefor constituents other than proteins, including vitamins, and carbohydrates. Similarly, a new advance in spectroscopicanalysis is Simultaneous Multielement Atomic Absorption Spectrometry (SIMAAC). It is a furnace atomizationtechnique that compares analytic signals to known calibration standards. Simultaneous Muitielement Atomic Ab-sorption Spectrometry, which permits simultaneous analysis of up to 16 elements, has important implications formore rapid sample turnout in nutrient analysis of foods. However, careful sample preparation and accurate instrumentcalibration is required to avoid erroneous results (60).

Other new techniques in food analysis Include use of bioindicators, mass spectroscopy, delayed light emission,xray diffraction, supercritical C02 chromatography, microbial assays, and computerization. Although the list is notall inclusive, it suggests some of the directions food analysis will follow. Last, advances in computer technologypoint toward further miniaturization of techniques as well as improved speed and accuracy.



Table 14-8-Knowledge of Nutrient Composition of Fresh Fruits

Little or Substantial Inadequate NotNutritional component no data data data applicable

Individual sugars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xStarch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xNutrient fiber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xTotal fat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xFatty acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xSterols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xCalcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xIron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xPhosphorous . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xSodium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xMagnesium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xPotassium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xZinc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xTotal protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xIndividual amino acids . . . . . . . . . . . . . . . . . . . . . . . . . . . .Folacin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vitamin D....... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vitamin E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xBiotin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Choline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Pantothenic acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B1 (Thiamin) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B2 (Riboflavin) . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B12.... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin C...... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xNiacin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

Tables from: G.R. Beecherand J.T. Vanderslice, “Determinationof Nutrients in Foods: Factors That Must Be Considered:’ Modern hfethods ofFoodAna/ysis, K. Stewart and J. Whitaker (eds), 1984, pp. 34-41. Tables prepared from USDA, Nutrient Data Research Branch, Consumer Nutrition Divisionof the Human Nutrition Information Service research publications.

Variation in Nutrient Attributes

To ascertain whether the nutritional value of a fruit orvegetable varies among individual samples of the fruitor vegetable, relevant information for potatoes, toma-toes, apples, and oranges was collected by examiningthe past 10 years of International Food ScienceandTech-nology Abstracts.

Nutritional variation was found to exist among samplesof fruits and vegetables in several published studies. Forexample, protein, niacin, and thiamin increased in potatoeswhile ascorbic acid as well as starch decreased when ni-trogen fertilizer was applied. Sandy soils increased theamounts of protein, ascorbic acid, riboflavin, niacin, so-dium, and iron in potatoes but decreased the amounts ofthiamine, magnesium, and calcium (2). One study (35)indicated that samples of a single potato cultvar may differwidely in sugar content after 9 weeks of storage. Incor-porating phosphorus or potassium to the soil had no effecton protein or nonreducing sugars, but phosphorus increasedthe starch and sugar content of the potatoes.

Environmental factors influence the sugar-acid ratio,beta-carotene, and nitrogen content and quality of to-

X

xx

xx

matoes (24). Nitrogen and potassium ratios also influencedry matter, soluble dry matter, and beta-carotene of fruitsas well as their keeping quality. Maturity of the tomatoaffects total sugars and the ratio of reducing to nonre-ducing sugars as well as the percentage of total solublesolids. Mineral content and composition in tomatoes areinfluenced by location and growth but do not vary amongcultivars. However, cultivar and fertilizer both affect theamount of ascorbic acid in tomatoes (25, 44).

In apples, seasonal variation affects anthocyanin, totalphenol content, diameter and weight, total soluble acids,acidity, and Magnes-Taylor puncture values. Bruising andsoftening rates in cool storage varied by cultivar (13, 32).

Vitamin C in oranges was found to be influenced byvariety, cultural practice, maturity, climate, fresh fruithandling, and processing factors such as packaging andstorage. Percentage of juice, Brix, acidity, and total sug-ars varied with orange cultivar (40, 54).

In summary, the nutritive composition of fruits andvegetables varies due to factors of climate, geographicallocation, cultivar, soil variables, irrigation practices, fer-


Table 14-9—Knowledge of Nutrient Composition of Fresh Vegetables

Little or Substantial Inadequate NotNutritional component no data data data applicable

x

x

Individual sugars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xStarch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xNutrient fiber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xTotal fat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xFatty acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xCholesterol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sterols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xCalcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xIron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xPhosphorous . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xSodium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xMagnesium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xPotassium . . . . . . . . . . . . . . . . . . . . . . . . 4 . . . . . . . . . . . . . xZinc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Total protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Individual amino acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . xFolacin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vitamin D...... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xBiotin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Choline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xPantothenic acid... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Vitamin A....,.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B1 (Thiamin) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B2 (Riboflavin) . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin B12, ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xVitamin C....... . . . . . . . . . . 4 . . . . . . . . . . . . . . . . . . . . . xNiacin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

Tables from: G.R. Beecher and J.T. Vanderslice, “Determination of Nutrients in Foods: Factors That Must Reconsidered;’ hfodemhfethodsof FoodAna/ysis, K. Stewart and J. Whitaker (eds.), 1984, pp. 34-41. Tables prepared from USDA, Nutrient Data Research Branch, Consumer Nutrition Divisionof the Human Nutrition information Sewice research publications.

x

xx

x

tilization practices, and seasonal and annual variation.Post-harvest physiology and handling introduces addi-tional sources of variation in the nutritional compositionof fruits and vegetables.

Conclusion

Available evidence suggests that intracommodityvariation in nutritional value does exist. Thus, onerequirement for developing a grade standard based onnutritional characteristics is fulfilled. However, the lackof adequate data on several nutritive components offruits and vegetables remains a problem. This defi-ciency needs to be rectified before nutritive attributescan be included in grade standards incomprehensivemanner.

Assessing the Relationship Between Nutrientand Sensory Characteristics

Concept

Whether it makes sense to change from sensory-based grading to nutrient-based grading depends on the

extent to which nutrition and sensory characteristicsare related. To illustrate, consider the extreme case.Suppose all criteria contained within the sensory char-acteristics base for grade standards were positively cor-related at 1.0 with whatever criteria were chosen fornutrition-related grade standard. This would imply lit-tle or no impact from a change to an alternative base.Obviously, however, it is more likely that some (butnot all) sensory criteria are correlated with some (butnot all) nutrition-related criteria.

As discussed earlier, current grade criteria for fruitsand vegetables are based on three main considerations—quality, condition, and size. In general, the quality cri-teria involve maturity, cleanness, shape and form, color,and quality defects. The condition criteria generally in-volve firmness, condition defects, and color.

A matrix relating current sensory grade criteria tonutritional characteristics is presented in table 14-10.The current grade standards, generalized across all fruitsand vegetables, appear as rows in the table. The col-umns are various nutrition-related characteristics. Some


Table 14-10-A Method for Conceptualizing the Relationship Between Sensory Characteristics andNutrition Characteristics

Current grade criteria, Conceptual nutrition-related characteristicsgeneralized across all Enzymes & Carbo- Fats &fruits and vegetables Vitamins Minerals Calories proteins hydrates oils Sodium Calcium FiberQuality

MaturityCleannessShape/FormColorQuality defects

Fungus injuryInsect injuryMechanical injuryOtherb

ConditionFirmnessCondition defects

DecayBruisingFreezingDiscoloration

Ground color/color

SizeaThe OSU study team believes that this list accurately portrays the criteria which predominate across all fruits and vegetables. However, there are somecriteria in the current standards for a specific fruit or vegetable not reflected in this list. Such omissions have scant consequence for the present assessment.%)ther is defined as ill-shaped, undesirable color, sunburn, growth cracks, and/or dirt.SOURCE: Office of Technology Assessment, 1992.

cells of the matrix are not expected to be of equalrelevance. For example, one might expect positive cor-relation between maturity and calories per gram, whereasthe fiber-insect injury cell might not have any corre-lation or importance. Similarly, if a nutrition-relatedbase for standards were ever adopted, one would notexpect all the criteria listed as columns in the table tobe included in a standard. At this point, however, thereare no compelling reasons to exclude cells formed bythe matrix from examination, except for the cells in-volving cleanness and shape and form. These two cur-rent sensory grade criteria are not related to nutritionattributes. Therefore, these two rows are shaded toindicate no correlation is expected.

Each of the 126 relevant cells of the matrix, in effect,defines a specific topic where knowledge is desired.A task of the assessment of the nutrition-related basefor grade standards was to carefully review existingscientific literature for each of the relevant cells forthe four commodities chosen for analysis—potatoes,tomatoes, apples, and oranges. The past 10 years ofvolumes of the International Food Science and Tech-nology Abstracts have been examined for research lit-erature relevant to the matrix and the case studycommodities.

Current Information

A summary of the findings is presented in table 14-11. A letter for each of the investigated commodities (Afor apples, O for oranges, P for potatoes, and T fortomatoes) is placed in a cell if information existed aboutthe nutrition-sensory relationship.

As is evident from the summary table, no scientificliterature was found for many of the cells. For onlyabout 8 percent of the 504 total cells (126 for eachcommodity) does at least one research article exists.No studies were found that investigated the relation-ships between current sensory grade characteristics andsodium while only one study examined calories. Theinevitable conclusion is that much is unknown aboutthe relationship between sensory characteristics andnutrition-related characteristics.

Nonetheless, some knowledge is available. The re-lationships between maturity and nutrition, especiallywith respect to vitamin C and carbohydrates, are themost researched. The concentration of vitamin C in-creases with maturity in potatoes and tomatoes, butdecreases dramatically in oranges and potatoes the longerthese commodities are held in storage. Carbohydratesin apples and tomatoes are positively related to ma-


Table 14-1 l—Summary Table of Scientific Literature on the Relationship Between Sensory Characteristics andNutrition Characteristics for the Four Study Commodities.

Current grade criteria, Conceptual nutrition-related characteristicsgeneralized across all Enzymes & Carbo- Fats &fruits and vegetables Vitamins Minerals Calories proteins hydrates oils Sodium Calcium FiberQuality

Maturity . . . . . . . . . . . . . A,O, P,A, O, P, T T T o A, O, P, T O, T A,O,T A, T

Cleanness . . . . . . . . . . .Shape/form . . . . . . . . . .Color . . . . . . . . . . . . . . .Quality defects . . . . . . .

Fungus injury . . . . . .Insect injury . . . . . . .Mechanical injury . .Otherc . . . . . . . . . . . .

ConditionFirmness ., . . . . . . . . . .Condition defects . . . .

Decay . . . . . . . . . . . . 0Bruising . . . . . . . . . . . PFreezing . . . . . . . . . . P, TDiscoloration . . . . . .

Ground colorl/color . . .

Size . . . . . . . . . . . . . . . . . . P

P

o

P T

A, T

A

aKey: A = apples, O = oranges, P = potatoes, T = tomatoesb% OSU study team believes that this list accurately portrays the criteria which predominate across all fruits and vegetables. However, there are somecriteria in the current standards for a speeific fruit or vegetable not refleeted in this list. Such omissions have scant consequence for the present assessment.Oher is defined as ill-shaped, undesirable mlor, sunburn, growth cracks, and/or dirt.


turity. In potatoes, starch is more readily converted tosugars after harvest. Conversely, oranges show a de-crease in glucose and fructose during storage and asthey decay.3

Chemicals and the Grading System

Current Pesticide Usage in the United States4

Herbicides, insecticides, and fungicides comprise thethree major components of the $4 billion-a-year U.S.agricultural pesticide market. Herbicides surpassed in-secticides in the late 1960s to become the most utilizedpesticide class. With $2.5 billion in sales, they accountedfor 90 percent of the total pesticide pounds applied in1986. The insecticide agriculture market was second with$1.0 billion in sales, followed by fungicides with salesof about $265 million.

In 1982, slightly more than 500 million pounds ofpesticide active ingredients were utilized in American

agriculture. Pounds of pesticide active ingredients were170 percent higher than in 19&l, while acres under cul-tivation remained essentially constant. By 1987, poundsof active ingredients had declined to about 430 millionpounds. Ninety percent of all herbicides and pesticidesare applied to four crops: corn, cotton, soybeans, andwheat.

Fungicides account for about 10 percent of all pesti-cides applied in agriculture and are the most significantpesticide product used in production of fruits and veg-etables. Insecticide use is also significant in fruit andvegetable production, however, its use has declined inrecent years through the adoption of new, more effectiveproducts and innovative strategies such as crop rotationsand Integrated Pest Management.

Most new pesticide products introduced since 1980have been herbicides. Thirty-seven herbicides have beenregistered with the Environmental Protection Agency(EPA) since 1980 as compared to 10 fungicides. This

3Note that mmy of these ~ic]es address ~St-hmest changes. These changes are not a maturity issue; however, they do ilhIstrate the imprtanceof post-harvest storage and handling techniques to the nutritional value consumers ultimately derive from a stored fruit or vegetable.

gInformation in this ~ction comes from pages 43 through 49 of Alternurive Agriculture, a report by the Committee on the Role of AlternativeFarming Methods in Modem Production Agriculture, Board of Agriculture, National Research Council, 1989.

Chapter 14—Food Quality: the Relvance of Food Grades ● 375

Photo credit: Grant Heilman, Inc.

Chemicals applied during production of fruits andvegetables may affect certain grade criteria. Enhanced

grade quality is one of many reasons for usingpesticides.

disparity reflects differences in the size of the marketand the higher profitability of the herbicide class, whichencourages new product innovation. Development of newfungicides is tricky due to a tendency for the developmentof pest resistance. Finally, fungicides have faced signif-icant regulatory problems due to high carcinogenicity oroncogenicity. Although important to the production offruits and vegetables, introduction of a new fungicideproduct can be a financial risk for the developing company.

Production of processing tomatoes in California andfresh market tomatoes in Florida and Ohio are discussedto highlight patterns of fruit and vegetable fungicide use.About 1.3 million tons of active ingredients are appliedto the 304,000 acres devoted to these crops. California,which has 240,000 acres in processing tomatoes, uses784 tons of fungicide active ingredient. On a pound-per-acre basis, however, the State uses only 6.5 lb per acre,compared to 11.5 lb per acre in Ohio and 17.9 lb peracre in Florida. The higher application rates in Ohio andFlorida are due in part to the more rigid cosmetic re-quirements needed for fresh market production. Moreimportantly, the more humid Midwestern and Southernclimates necessitate increased levels of fungicide use.

The fungicide use pattern of tomatoes is representativeof most fruits and vegetables. California uses less peracre because of its dry, favorable climate. But becauseit produces over half of the Nation’s fruits and vegetables,

California utilizes the largest share of fungicide productsapplied nationwide.

Pesticides and the Current Grading System

Chemicals applied during production may affect cer-tain grade criteria in the current USDA grade standardsfor fruits and vegetables. An assessment of the relation-ship among various chemicals and current grade criteriawas completed for apples, potatoes, and tomatoes. Tables14-1 2–14- 14 summarize current, recommended culturalpractices and the relationship of the chemical to current,selected USDA grade criteria. An ‘‘X’ is placed in eachcell where the chemical’s use affects the particular gradecriterion. The summary reveals that chemical use pri-marily is relevant to three general grade criteria—fungusinjury, insect injury, and decay. Thus, chemicals are usedprimarily to protect potatoes and tomatoes from fungalor insect damage.

While relationships between pesticide usage and gradecriteria have been found, it is not clear whether or notcurrent grade criteria encourage use of pesticides. Prob-ably, improved grade quality is only one reason for usingpesticides. Other reasons would likely include higheryield, better harvesting conditions, and reduced pest pre-serves on subsequent crops.

Chemical Residue Grading Standard

For an attribute to serve as a portion of a grade stan-dard, variation in the attribute is necessary. Two recentsurveys of chemical residues in food suggest that indi-vidual samples of fruit and vegetables are likely to exhibitdifferences in chemical residues. In 1989, the State ofCalifornia sampled 9,403 food samples for pesticide res-idues (43). The following distribution was found:

Percentof

Residue distribution samples

No detectable residues . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.9Residues 10% or less of tolerance level . . . . . . . . . . . . 13.0Residues between 1O%. and 50% of tolerance level . . . 7.4Residues from 50% to 100% of tolerance level . . . . . . 1.0Exceeded tolerance level . . . . . . . . . . . . . . . . . . . . . . . . . 0.7

FDA annually tests about 20,000 samples of freshand processed foods for residues exceeding tolerancesestablished for 10,000 food additives and 300 pesti-cides (51 ). Foreign food imports make up a large pro-portion (36 percent) of the samples. In 1988, no residueswere found in 60 percent of the samples tested. Theremaining 40 percent contained detectable residues,


Table 14-12-Relationship Among Selected USDA Grade Criteria and Chemicals Approved for Useon Apples, Ohio, 1991

Selected generic grade criteria

Chemical (Scientific Name) Maturity Fungus injury Decay Insect injury Sizea

Growth regulatorFruitone N (1-Naphthalene-Acetic Acid) . . . . . . x

HerbicidesGramoxone (Paraquat) (Bipyridylnium) . . . . . .Sinbar (3-tert-Butyl-5-chloro-6-methyluraciI) . .Karmex (Substituted Urea) . . . . . . . . . . . . . . . . .

FungicidesCaptan (Cis-N-trichloromethylthio-4-

cyclohexene-2 1,2-dicarboximide) . . . . . . . . . xBenlate (Methyl-1 (butylcarbamoyl)-2-benzimi-

dazolecarbamate) . . . . . . . . . . . . . . . . . . . . . . . xDithane (Ethylene bisdithiocarbamate) . . . . . . . x

InsecticidesOil (Oil solutions) . . . . . . . . . . . . . . . . . . . . . . . . . x xGuthion (Organophosphorous-Pesticide

family) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x xVendex (Organotin) . . . . . . . . . . . . . . . . . . . . . . . x xImidax (N-(Mercaptomethyl) phthalimide S-O,

O-dimethylphosphorodithioate) . . . . . . . . . . . . x x

x

xx

xxx

aVery poor weed mntml can result in smaller size because of competition between weeds and the commercial crop.SOURCES: Office of Technology Assessment, 1992, compiled from Ohio Crop Errtefptise Budgets, 1989: Speciahy Crops, The Ohio State University,

Columbus, OH, p. 30 and Farm Chemicals Handbook, Meister Publishing Co., 1991.

but less than 1 percent of the samples exceeded EPAtolerances. 5

EPA regulations exclude from the human food sup-ply any commodity for which safe chemical residuelevels are exceeded. This is not a grading question,but a food safety concern. However, assuming that thesafe level for detectable residue is greater than zero,a grading standard hypothetically could be established ‘on the basis of detectable levels of a specific chemicalresidue. The degree of detectable residue denotes aparticular grade category. A hypothetical example ap-pears in table 14-15.

Table 14-15 indicates that, if the level of detectablechemical residue were the only attribute used for grading,higher grades would be assigned to foods with succes-sively lower residue levels.

Conceptually, each type of chemical would constitutea separate attribute. The set of chemicals deemed appro-priate would then compose the standard. Another pos-sibility would be to develop a summary index or weightedaverage measure for chemical residue. Such a summary

index could allow the resultant grade to be assigned onthe composite or summary score.

Conclusions

Implementation of a chemical residue attribute standardfor fruits and vegetables would require decisions concerningwhich chemicals would form the standard. This task wouldbe controversial and would require participation from abroad array of interested parties. It is reasonable to assumethat some potentially usable chemicals would not be ad-mitted to form the standards.

If a chemical residue grading system were implemented,lack of inclusion of naturally occurring toxic substanceswould be controversial. Naturally present phenolic com-pounds in fruits and vegetables have been found to becarcinogenic. Flavinoids tuercetin and campherol are pres-ent in many fruits and vegetables. Acetaldehyde, found inapples, is reported to be mutagenic. Aflatoxin is a fungaltoxin and known carcinogen that can and does occur invirtually every fruit and vegetable from the fresh to pro-cessed state. Thus, a grading standard based on residuesof chemicals ideally should include naturally occurring as

S~ the samples that exceeded to]e~ce ]eve]s, 84 Pereent involved cases for which there wss no established EPA tolerance. hck of ~ EPAtolerance level generally means that any residue deems the commodity to be “adulterated” and subject to regulatory action. Exceptions include“Unavoidable Pesticide Residues, ” which result unavoidably in certain processes under “good” agricultural and manufacturing procedures, andEPA “Emergency Exemptions, ” which are granted for use of nonregistered pesticides under certain emergency situations.


Table 14-13—Relationship Among Selected USDA Grade Criteria and Chemicals Approved for Use onPotatoes, Ohio, 1991


Chemical (Scientific Name) Maturity Fungus injury Decay Insect injury Sizea

Vine Killer DessicantDiquat (1,1 ’-ethylene, 2,2’ bipyridyliomion)b . . . . . . . . . . . . . x

HerbicidesLorox (Linuron & Chlorimuron Ethyl) . . . . . . . . . . . . . . . . . . .Dual (Chloracetanilise) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Eptam (S-Ethyldipropylthiocarbamate) . . . . . . . . . . . . . . . . . .Sencor-Lexone (Triazinone) . . . . . . . . . . . . . . . . . . . . . . . . . . .

FungicidesBravo (Chlorohalonil) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xRidomil (Metzlaxyl & Mancozeb) . . . . . . . . . . . . . . . . . . . . . . . x

/insecticidesDi-Syston (Organophosphorous) . . . . . . . . . . . . . . . . . . . . . . . x xSevin (Carbamate) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x xPhorate (Organophosphate) . . . . . . . . . . . . . . . . . . . . . . . . . . x xGuthion (Organophosphorous) . . . . . . . . . . . . . . . . . . . . . . . . x xCygon(Carbamate) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x x

Werypoorweecfcontrol canresultin srnallersize becauseofeompetition betweenweedsandthe commercial crop.bD@atls alwwp~edto S.etpotatoskins.

xx

xxxx

SOURCE:Officeof Technology Assessmen~ 1992, cx)mpiled from Ohio Crop Enterprise Budgets, 1989: Specialty Crops, The Ohio State University,Columbus, OH, p. 16 and Farm Chemica/s Handbook, Meister Publishing Co., 1991.

Table 14-14-Relationship Among Selected USDA Grade Criteria and Chemicals Approved for Use on StakedFresh Market Tomatoes, Ohio, 1991


Chemical (Scientific Name) Fungus injury Insect injury Decay Sizea

HerbicideTreflan (3,3,3-trifluoro-2,6-dinitro-N, N-propyl-p-toluidine) . . . . . . . . . . . . . . . . . . . . . . . x

FungicidesBravo (Chlorothalonil) . . . . . . . . . . . . . . . . . . . . x xBenlate (Methyl-1 (butylcarbamoyl) -2-benzimi-dazolecarbamate) . . . . . . . . . . . . . . . . x x

InsecticidesSevin (Carbamate) . . . . . . . . . . . . . . . . . . . . . . . x xThiodan (Chlorinated Bicyclic Sulfite) . . . . . . x x

aVery poor weed control can result in smaller size because of competition between weeds and the commercial crop.SOURCE: Office of Technology Assessment, 1992. Compiled from Ohio Crop Enterprise Budgets, 1989: Specia/fy Crops, The Ohio State University,

Columbus, OH, pp. 3–5 and Farm Chemica/s Handbook, Meister Publishing Co., 1991,

well as synthetic toxic substances. b Such a standard would has determined three requirements for an attribute to serve,be complex and controversial. in whole or in part, as a grade standard. One requirement

is that the attribute must vary across the produce to be

Options for an Improved Grading Systemgraded. A second requirement is that information on theattribute must exist so that preferences can be assigned

The purpose of the case study to this point has beento gradations of an attribute. The third requirement isthat the attribute must be measurable.

to introduce the conceptual basis for two different fruitand vegetable grade standards—one based on nutritional The assessment of conceptual alternatives has estab-content, the other on chemical residues. The investigation lished that both nutrition and chemical residue attributes

bAn argument can be made that humans have evolved over a long period of time eating these foods and have adapted to them and the chemicalsin them. But humans have not evolved with pesticides so the impacts can be different.

297-937 0 - 92 - 13 Q L 3


Table 14-15-Hypothetical Example of GradingSystem Based on Chemical Residues

Level of detectablechemical residue Resultant grade

Greater than EPA established residue No grade, excludedtolerance level from human food

supply<49% safety level . . . . . . . . . . . . . . . . . . . Grade C50-90% safety level . . . . . . . . . . . . . . . . . Grade B>90% safety level . . . . . . . . . . . . . . . . . . . Grade A


could be expected to vary across types of produce. Thus,the first requirement is met.

The second and third requirements are more complexand difficult to assess. The scientific literature reviewcontained in this chapter reveals substantial gaps in theknowledge base required for either grading alternative.

Measurement, as a third requirement for an alternativegrade standard, is a special issue. Current standards thatprimarily rely on sensory attributes mean that humangraders can gauge the presence or absence of the attributewithout mechanical assistance. Neither of the alternativestandards is sensory in nature, implying the need formechanical measurement. This, in turn, has significantimplications for the viability and cost effectiveness ofeither alternative, given today’s technology.

Mechanical measurement or testing likely would beslower and more costly than conventional grading byhumans. Lower efficiency and consequent higher gradingcosts would probably occur for either the chemical res-idue or nutrition-based alternatives. This would raise con-sumer prices for fruits and vegetables.

The relative merit of implementing either alternativefor fresh versus processed fruits and vegetables bearsanalysis. Consumers who purchase fresh produce at retailfor at-home consumption presumably would benefit themost from information embedded in either alternativestandard. Processing firms and firms in the food serviceindustry (hotel, restaurant, and institutional away-from-home market) already can and often do test produce theypurchase for nutrient or chemical residue characteristics.In addition, since nutritional labels are on most processedfood products, a nutrition-based standard for processedgrades would be redundant and of little value to theultimate consumers.

OTA concludes that insufficient justification exists torecommend shifting away from the current sensory stan-dards to either of the alternatives discussed here for the

processed and food service markets. The argument foralternative grading for the retail at-home (fresh) marketsegment has more viability, and the ensuing discussionis limited to that portion of the market.

The chemical residue concept for a grading systemcombines the issue of food safety with that of food qual-ity. The current food distribution system treats food safetyand quality separately. That is, the current distributionand marketing system essentially assigns grades only tofood determined safe for human consumption. The ‘‘mix-ing’ of these issues distinguishes the chemical residueattribute from the existing system.

The objective of implementing such a standard wouldbe to provide consumer information on the amount ofdetectable residue below some “safe” level. Presumablythis would allow consumer choice among various levelsof ‘‘safe for human consumption residue’ at alternativeprices. However, the chances for consumer misinfor-mation from such an attribute probably would be quitehigh. Consumers could easily misconstrue the informa-tion to mean that some foods on the market are not safe.Because of these problems, the chemical residue basefor standards is dismissed as a viable alternative by OTA,even for the retail at-home fresh fruit and vegetable mar-ket segment.

Thus, three viable policy options arise from this anal-ysis: abolishing current retail grades and standards, re-lying on point-of-sale (POS) nutritional labeling, andmodifying the current Federal standards to reflect someinformation on nutrient content. An evaluation of eachpolicy option follows.

Option l—Abolishing Grades

Consumer grade standards exist, but seldom are used.Explanations that might account for the limited use ofconsumer grade standards include the following:

. retail grades are not useful as a merchandising de-vice, and

. retail grades do not convey any additional infor-mation beyond that embodied in wholesale grades.

Regardless of the reasons for lack of use of retail grades,it is clear that abolishing them would not have a directand significant impact on the marketing of fruits andvegetables.

Because grade standards are used extensively forwholesale trading, abolishing wholesale grades wouldhave significant economic consequences for the fruit and


vegetable industry. Some immediate and obvious con-sequences would result:

●

●

●

●

transactions costs associated with trades wouldincrease.marketing efficiency would decline.marketing information would become less mean-ingful because price differentials by quality wouldbe less accurate, andfewer buyers would be available for a given seller(i.e., geographical area of trades would diminish).

Without the impartial information conveyed throughgrade standards, fruit and vegetable marketing wouldexperience a significant decline in overall efficiency.Commodities previously bought by grade descriptionswould require inspection by buyers, producing a de-cline in the efficiency with which fruits and vegetablesare shipped from production areas to consuming areas.Such inspection also would reduce the area over whichcommodities could be traded, thereby limiting marketcompetition and raising commodity prices at the whole-sale and retail level. Moreover, while the current grad-ing system facilitates grading at the shipping point level,abolishing grades would encourage trade consumma-tion at terminal markets. Previous experience has al-ready shown that terminal market transactions are lessefficient than the current geographically dispersed sys-tem (i. e., most produce bypasses terminal markets be-cause chain stores buy direct from shipping pointmarkets).

Although grade standards primarily are used to facil-itate wholesale trading, abolishing them is likely to havesignificant impact at the consumer level. For example,one reason grades might not be used at the consumerlevel is that their use at the wholesale level captures therelevant attributes for consumers. That is, attributes suchas color, maturity, shape, and size, which facilitatewholesale transactions, are likely to be important forconsumer transactions. If these attributes are not usedfor wholesale transactions, then consumer purchases atthe retail level that are based on these attributes are likelyto be impeded.

Option 2—Point of Sale Nutritional Labeling

The U.S. Congress in 1990 passed and the Presidentsigned a fruits and vegetables nutritional labeling law.The law stipulates that the content, format, and deliv-ery of fruit and vegetable nutritional labeling is to bedetermined by the Food and Drug Administration (FDA).In general terms, the bill will require the posting ofpoint of sale (POS) signs that detail the nutritional

content of the 20 most frequently consumed fruits andvegetables. During an 18-month period following sign-ing of the law, compliance is voluntary. Should com-pliance be deemed insufficient, a provision in the lawenables the FDA to then make in-store nutritional la-beling mandatory.

The bill had the general support of industry trade as-sociations such as the United Fresh Fruit and VegetableAssociation, the Produce Marketing Association, and theFood Marketing Institute. The final compromise legis-lation proved to be less onerous than earlier versions ofthe bill, which would have called for labeling of virtuallyall produce sold in stores. The trade associations viewlabeling as positive because of the opportunity to presentinformation highlighting the nutritional benefits of pro-duce. The conclusion drawn by the produce industry, interms of labeling’s potential impact on sales, is that tothe extent that consumers are better informed about thenutritional quality and healthful benefits of fruits andvegetables, overall sales of fruits and vegetables shouldgo up. These indusry groups, however, do not supportthe idea of mandatory labeling and therefore are workingto assure high voluntary compliance. Additionally, theyseem to be advocating simplified labeling with infor-mation on calories, carbohydrates, fiber, vitamin A, andvitamin C.

The production of nutritional labels (signs) that pre-sumably would be posted in every retail food store inthe country under this legislation will entail significantstartup costs. Once the labeling system has been put intoplace, maintenance costs should be modest. The nutri-tional components of the produce to be displayed in thelabeling will come from government published data, andthe signs (or labels) themselves will become permanentfixtures within produce departments. Open to questionis the extent to which implementation costs may be passedon to consumers. Little direct cost will be incurred byproduce retailers. The labeling will be provided by var-ious industry trade associations, and the signs and labelsshould be freely available in the 18-month “voluntary”initial phase of the law as the various industry groupsare interested in bolstering participation to stave off man-datory labeling.

The final form nutritional labeling will take is still beingworked out between the FDA and interested industry andconsumer advocacy participants. The produce industry per-ceived several years ago that nutritional labeling was aninevitability. By becoming involved with nutritional label-ing in its early stages, the industry can exert influence onthe form nutritional labeling would take.


A survey by Opinion Research Corp. commissionedby the National Food Processors Association in late 1989found that 4 of 10 consumers say that the first time theybuy a food product they read the labels for general nu-tritional information and make purchasing decisions basedon their comparisons. The survey results report that themore nutritionally sound a food product is (e. g., break-fast food v. snack food), the more likely consumers areto buy it. Other research has revealed that perceivednegative food attributes such as high sodium or choles-terol contents are just as important as positive attributesin formulating consumer decisions to buy one food prod-uct over another. Significantly, the proposed producelabeling is limited to nutritional attributes perceived byconsumers to be positive.

The final form that nutritional labeling will take mayfavor some fruits and vegetables over others in market-place competition. First, determining which are the top20 fruits and the top 20 vegetables by consumption isdifficult: there seems to be some jockeying for a placeamong positions 15 through 20. In these lower rankingcategories, consumption statistics do not indicate clearwinners. Foods that do carry nutritional labels probablywill attract consumers and lead to sales increases at theexpense of the lower rated foods. A second importantimplication of nutritional labeling in terms of marketplacecompetition relates to display of the nutritional infor-mation. Will labeling take the form of presentation ofaggregate data at a centralized location, with the 40 pro-duce products ranked on attributes; or will each producebin have a unique sign with nutritional attributes dis-played solely for that product? Research indicates that,for aggregate data, sequencing would have an impact onconsumer purchase decisions. If, for example, rankingoccurred on a positive (negative) nutritional attribute,then consumers would be steered toward (away from)purchase of the higher ranked food.

The nutritional labeling law will present the FDA withanother program area to administer. Therefore, somegovernmental costs will be incurred. After FDA’s initialinvolvement of writing provisions of the legislation, how-ever, its involvement will be limited to measuring com-pliance. Should the labeling legislation become mandatory,then it is possible that administrative costs related toenforcement could rise.

Option 3—Modifying Grades

Basing Federal fruit and vegetable grades for the at-home retail market in part on nutrient characteristicspresents an interesting and plausible option. The sci-

entific knowledge base for this option is relatively ad-equate though not comprehensive in scope. Thepossibility of combining some nutrient attributes withexisting sensory characteristics appears feasible. Forexample, the relationship between maturity in the cur-rent standards and several nutrient attributes is fairlywell established.

The economic impact and cost of adjustment to somenutrition-based grade standards, especially if they weremandatory, would be substantial. Transactions costs wouldincrease for some period of time during adjustment tothe new standards. Costs of grading would increase, es-pecially if destructive testing for nutritive content werenecessary. Consequently, during the adjustment period,prices for fresh fruits and vegetables at retail likely wouldbe higher and producer prices lower.

After some period of adjustment, nutrition-based grad-ing standards would become customary for all firms in-volved in the marketing channel-producers, wholesalers,and retailers. At this point, transaction costs of using thenew system should not be significantly different fromthe previous sensory standards; however, grading costswould be higher because nutrition-analysis requires theuse of instruments and experts. These increased trans-actions costs would be passed on to consumers in thelong run.

The distribution of costs to various industry partic-ipants would be different during the adjustment periodthan in the long term. Initial uncertainty about the newstandards would increase transaction costs to users ofthe new standards. If use of the new standards werevoluntary, relatively higher transaction costs woulddiscourage use of the new system by wholesalers andretailers. Instead, they would use the former standardsor rely on trade associations or comparable groups todefine standards similar to the old system. Further-more, over the longer term, the higher transaction costswould result in higher costs to consumers and/or lowerprices for producers.

The shift to a grading system based in part on nutritioncriteria would probably diminish the historic role theAgricultural Marketing Service has played in grading andenhance the role of FDA. The food science componentof FDA would be a more natural focal point for regulatoryand compliance activities.

Conclusions

A summary table of the conclusions concerning thepotential viability of the alternative conceptual bases ex-


Table 14-16—Summary Conclusions on Potential Viability of Conceptual Grading Alternatives

Market segment Chemical base Nutrient base

Fresh Costly to implement Costly to implementAt-Home Sparse scientific knowledge base Inadequate current scientific knowledge base

May impart misleading information Advantage lessened by recent nutritional in-formation point-of-sale program

Relatively most viableAway-from-Home Marginal value to consumers Marginal value to consumers

Costly to implement Costly to implementProcessed Marginal value to consumers Marginal value to consumers

Costly to implement Costly to implementSOURCE: Office of Technology Assessment, 1992

amined is presented in table 14-16. Before either thenutrient or chemical base could be implemented on acost-effective basis, advances in measurement technol-ogy would need to occur. This is on the horizon, butuntil advances occur, the wisdom of adopting an alter-native base seems marginal from a societal perspective.At the current time, neither the scientific informationbase or the technology for measurement permits nutrientattributes to be an exclusive grade standard for fruits andvegetables.

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