Balanced use of fertilizer nutrients and its determinants: a case of cotton cropBy

Khuda Bakhsh

Institute of Agricultural and Resource Economics, University of Agriculture, Faisalabad,

Pakistan

Email: kbmultan@uaf.edu.pk

1. Introduction

One of the strategies to boost farm productivity is by means of agricultural intensification.

However, the process of intensification in agriculture depends on the sufficient supply of plant

nutrients to the crops for assuring high yield of the respected crops (Amar and Cisse 2007).

Fertilizer is a key player to enhance crop production by upgrading soil fertility. It also serves as a

key for securing the food requirements of a country. None of the country has been able to boost

agricultural productivity without making expansion in the use of chemical industry. Balanced

fertilization refers to application of essential nutrients of plant, chiefly the major nutrients-

Nitrogen (N), Phosphorous (P) and Potassium (K) in optimal quantities through accurate method

and application time in precise proportion (Alam and Khan 1999). Balanced fertilization leads to

enhance the yield of crops, quality of crops and farm income. Further it serves as a remedy to

correct soil nutrient deficiencies and helps in maintaining the soil fertility. But it can also be

observed that in-spite of increased use of fertilizers overtime in Pakistan, productivity of crops

could not be increased (Afzal and Ahmad 2009). Some empirical studies had also showed this

fact that on many high-yielding lands, the rate of nitrogen fertilizer application has been too

high, resulting not only in decrease in efficiency and high costs, but also negative effects on

air and water quality had been observed (Zhu and Chen 2002, Wang et al. 2005). Similarly,

Weight and Kelly (1999) stated the following negative impacts of over-fertilization or imbalance

use, acidification of soil may occurs as a result of excessive ammonium N fertilizers usage,

negative effects on traditional systems and environment i.e. increase in pollution and emission of

green house gases.

The use of commercial fertilizers in Pakistan was initiated in 1952-53, and its consumption was

only 1,000 nutrient tonnes of N whereas phosphorus was introduced in 1959-60 with an initial

off-take of 100 nutrient tonnes. Potash fertilizer usage was started in 1966-67 with a volume of

about 120 nutrient tones (Quddus et al. 2008). These trends of fertilizer usage gave emphasis to

the significance and function of fertilizer in the national economy. Currently, the consumption of

fertilizer in Punjab province was about 3054 thousand N/Tones in the year 2010-11 (Govt. of

Punjab 2011). So far, there has been an incessant rise in the utilization of fertilizers (Quddus et

al. 2008). Of all the farm inputs fertilizer is the most profitable. Furthermore, the relative low

cost of fertilizer in contrast with the cost of other farm inputs such as land, wages and farm

machinery, have also contributed towards increasing the fertilizer consumption in the country

(Alam and Khan 1999).

At present fertilizer usage in the country is imbalanced. There is a rapid increase in the

consumption of nitrogenous (N) fertilizer than those of phosphate (P2O5) and potash (K2O)

fertilizers during the last 4 decades, thus leading to severe imbalance between N, P and K

nutrients (Rashid 1994 and Afzal and Ahmad 2009). This rapid rise in nitrogen consumption can

be ascribed to a range of economic and technical factors. Urea which is the chief source of

nitrogen is cheaper, provides rapid crop response and locally accessible. In contrast, phosphate

and potash fertilizers are pricey and imported from other countries (Solaiman and Ahmad 2006).

There is an immense requirement of utilizing recommended doses of fertilizers for getting

utmost crop yield. The superlative option is to determine the nutrient contents of soil through

soil or plant analysis and then apply fertilizers in accordance with the requirements. However, in

reality most of the farmers are not getting their soil analyzed and hence harvest low yields (Alam

et al, 2005). The other feasible option is to use the trial data of relevant district and develop site

specific recommendations. At the same time, it is crucial to make the management practices as a

part of site-specific recommendations to overcome the constraints which are impairing the

efficiency of various nutrients.

Cotton is an important non‐food cash crop which contributes significantly in foreign exchange

earnings of the country. In 2010-11, it accounts for about 1.4 percent of GDP. During 2009‐10, 

an  important  development  in cotton production was  the  rising  usage  of  Bt cotton  by the

farmers. In Punjab, Bt cotton was grown approximately on 80% areas (Government of Pakistan

2010-11). The use of genetically modified Bt cotton seed will result into less pesticide usage and

higher output of cotton (Thirtle et al. 2003 and Qaim and Matuschke 2005).

This paper made an attempt to emphasize the adoption of balanced nutrients in Bt cotton

production in Multan District of Punjab, in order to throw light on the fact that whether there is

adoption of balanced fertilizers in that locality or not and what are the factors effecting the

adoption of balanced fertilization in particular crop.

Materials and MethodSources of data

The study makes use of primary data collected from the field. A Multi-Stage Random Sampling

Technique was used for the present study. The Punjab province was selected purposively

because it is the largest contributor in the economy of Pakistan. Moreover, the Punjab province

comprises of various cropping zones in the irrigated areas. The dominant cropping zones include

rice-wheat, mixed and cotton-wheat cropping zones. Multan District was selected from the

Cotton-Wheat zone because it is representative district in the cotton-wheat zone where cotton is a

major crop. In the next sampling stage, Multan and Shujabad tehsils were selected randomly. For

the purpose of data collection 10 villages from each tehsil were selected using Systematic

Random Sampling Technique from the list of villages available with the concerned district

census officer. At the final stage of sampling design, complete list of farmers in the selected

village was obtained and from this list, 10 % farmers were selected randomly. The respondents

were selected using Systematic Random Sampling Technique. A sample of 154 respondents was

interviewed to obtain information on various aspects of fertilizer application.

Data was collected through interview schedule. The well-structured and pre-tested questionnaire

was used to gather information on the use of fertilizer nutrients, other inputs and yield obtained

in the particular crop along with socio-economic characteristics of the respondents.

Price signal can also influence the selection of crop enterprise in the specific cropping zone and

most of the time such changes in cropping pattern are transitory. So keeping this in mind, data

was collected for that crop which was being cultivated continuously for more than two years.

The reason is that farmers commonly take more care of crops being cultivated on the basis of

price fluctuations during certain years. Hence they may be using more fertilizer nutrients and

other inputs in order to exploit maximum benefits of output price. Thus cotton and wheat were

the dominant crops in the zone. Sugarcane, rice and sunflower crops were cultivated at a very

low scale.

Empirical method (Logit model)

The logistic regression technique is used when the dependent variable is dichotomous (binary) in

nature in which case the event either “occurs” or “does not occur”. In the present study, logistic

regression model is used in order to analyze the joint effect on the use of balanced application of

fertilizer nutrients. Furthermore, it is used to explore the influence of various factors in the

decision of applying balanced use of nutrients in the particular crop enterprise. This study is

postulated that the probability of a farmer using balanced fertilizer nutrients depends on farm and

farmer related characteristics. The dependent variable is dichotomous and, it, therefore, takes

value of one if farmer uses balanced fertilizer nutrients and zero if he does not do so.

Logit model is widely used in various studies of adoption of technologies (for example, Yahanse

et al. 1990, Polson and Spencer 1991, D’Souza et al. 1993, Hussain et al. 1998, Salalsya et al.

1996, Chilot et al. 1996). This model not only helps to assess the various factors that influence

the adoption of specific technologies, but also provides predicted probabilities of adoption. In the

present study, we use logit model to determine effects of various factors on balanced use of

fertilizer nutrients. Here we data contain information two types of fertilizer use, one is balanced

use (following the principle of 1.5-2:1 nitrogen and phosphorus ratio) and the other one is

relating to other types of fertilizer use1. Thus the data is of binary nature regarding fertilizer use.

For binary type of dependent variable, logit regression analysis is specified following Demaris

(1992). The logistic regression for the log odds of adoption of balanced use of fertilizer nutrients

is written as:

log( Pi1−P i )=∑ β j x ij+μi

Here Pi=prob(y=1) is the conditional probability that a farmer is balanced user of fertilizer

nutrient whereas (1−P i)= prob(y = 0) shows conditional probability of farmer not using balanced

amount of fertilizer nutrients in his fields. β j are parameters to be estimated whereas x ij are

independent variables having impacts on balanced use of fertilizer nutrients and μi is the error

term. The descriptions of the explanatory variables are given in Table 1.1 According to Pakistan’s soil condition, the recommended NP ratio is 2:1. Any deviation from this ratio is considered to be imbalanced use of nitrogen and phosphorus fertilizers. Some farmers were using more phosphorus compared to nitrogen. Similarly others were making higher use of nitrogen than that of phosphorus. So we consider all these farmers as imbalanced users of fertilizer nutrients in the present study.

We will present logistic regression results in terms of odds ratio because odds is a pure summary

statistic for the partial effect of a given predictor, controlling for the other predictors in the

logistic regression (Demaris 1992).

Table 1: Definition of variables in the logit modelVariables Description of variablesLNAGE Age of the respondents in yearsLNAGE2 Square of age of the respondentsLNEXP Farming experience of the respondents in yearsMFARMERORG Dummy for member of farming organization (1=Yes, 0=No)DINFORMALTRAIN Dummy for receiving informal training (1=Yes, 0=No)OFFFARM Dummy for off-farm income (1=Yes, 0=No)TESTINGSOILWATE

Dummy for knowledge about soil and water testing laboratory (1=Yes, 0=No)

DECISIONSOIL Dummy for decision of fertilizer use according to soil type (1=Yes, 0=No)

IMPACTSNPK Dummy for knowledge about impacts of different fertilizer nutrients (1=Yes, 0=No)

DPRIM Dummy for primary education (1=Yes, 0=No)DMIDDLE Dummy for middle level education(1=Yes, 0=No)DMATRIC Dummy for matriculation level (1=Yes, 0=No)DTENANT Dummy for tenants (1=Yes, 0=No)DOWNTENANT Dummy for owner-cum-tenants (1=Yes, 0=No)FARMSIZE Farmer size in acresRESULTS AND DISCUSSION

Summary statistics of variables

The summary statistics of the variables included in the logit model is presented in Table 2. It

shows characteristics of households selected in the study area for cotton crop. On an average,

there is little difference in the age of farmers using balanced fertilizer and imbalanced fertilizer.

However, balanced users are more experienced farmers than other group of farmers. This may be

because of the reason that they apply fertilizer in balanced amounts on the basis of their more

experience.

About 22 percent farmers using balance amounts of fertilizer are associated with some

organizations having links with agricultural production. Moreover, it is found that such farmers

are commonly associated with input-oriented-organizations. In contrast, the proportion of

imbalance users is only 11 percent which were associated with some farm organizations.

Informal training is also important factor in deciding proper amounts of inputs. Results of the

present study show that 22 percent of farmers using balance fertilizer have chance to obtain

informal training whereas only 8 percent of other type of farmers received informal training.

Such type of training was provided by different pesticide companies, fertilizer companies and

extension staff. This result indicates that training has an important role in proper application of

fertilizer nutrients.

Availability of Off-farm income is crucial to make decision in selection and purchasing types

and amounts of different farm inputs especially fertilizer nutrients. Results of the study show that

farmers having off-farm income are respectively 26 and 25 percent in two types of categories i.e.

balanced users and imbalanced users. The availability of off-farm income between these two

groups is almost same.

The larger numbers of balanced users were those who possessed knowledge about soil and water

testing laboratory and made decision of fertilizer use according to the soil type. The 86 and 48

percent balanced users and imbalanced users respectively have awareness about impacts of

distinguish nutrients in cotton field which shows that a larger proportion of respondents are well

aware of this fact and this ultimately resulted in balanced use of fertilizers.

Considering education level of two types of farmers under analysis, it is found that balanced

fertilizer users are comparatively more educated (in all the three education categories i.e.

primary, middle and matriculation) than their counterparts making a small proportion in getting

education. Thus such farmers coupled with ample farming experience and higher education let

them able to better understand new technologies and amounts of fertilizers to be used for specific

crops.

Tenancy status provides incentives to farmers for long-term investment for sustaining land

fertility and productivity. Our results show that the proportion of tenant farming is almost same

in both categories of users while owner-cum-tenants are relatively more among balanced users in

contrast with the imbalanced users. Whereas average farm size of balanced fertilizer users is 29

acres and it is 25 acres for imbalanced fertilizer users. This shows that farm size also contributes

in balanced use of fertilizer nutrients.

Table 2: Summary statistics of variables included in the model

Variables 

Balance Used Imbalance Used

Mean Std. Deviation Mean Std.

DeviationAge of the respondents (years) 40.93 13.347 40.56 12.565Farming experience of the respondents (years) 17.04 10.537 14.17 7.991Membership in farming organizations (yes=1) 0.22 0.424 0.11 0.309Having informal training (yes=1) 0.22 0.424 0.08 0.268Off-farm income (yes=1) 0.26 0.447 0.25 0.435Testing soil and water (yes=1) 0.37 0.49 0.12 0.32Fertilizer use according to soil type (yes=1) 0.89 0.32 0.52 0.50Information on impacts of NPK (yes=1) 0.86 0.34 0.48 0.51Primary education (yes=1) 0.48 0.51 0.16 0.37Middle education (yes=1) 0.19 0.40 0.14 0.35Matriculation education (yes=1) 0.25 0.43 0.18 0.39Tenant farming (yes=1) 0.33 0.47 0.30 0.47Owner cum tenant farming (yes=1) 0.13 0.33 0.04 0.19Farm size (acre) 29.22 26.471 25.50 29.285

Econometric analysis

Table 3 shows the results regarding estimates of logit model for balanced use of fertilizer

nutrients in cotton (Bt cotton sown in May-June) crop. Results regarding balanced use of

fertilizers in cotton crop show that out of 15 variables, 10 variables have significant effects on

the adoption of balanced nutrients. These are age of the respondent, his farming experience,

square of the age, having membership in any organization relating to agriculture, off-farm

income, knowledge about soil and water testing laboratory, decision of fertilizer use according to

soil type, knowledge about impacts of different fertilizer nutrients, acquisition of primary

education and tenants. While getting informal training, acquiring middle and matriculation

education, owner-cum-tenants and farm size are statistically non significant which means that

these variables are not contributing in balanced use of nutrients in cotton crop.

The odd in favour of adopting balanced nutrients is positive but small for increase in age of

farmers by 1 year. But the value of odd for square of age of the respondents has negative odds

ratio. The odd in favour of adoption of balanced nutrients increases by a factor of 7.062 among

experienced farmers. The odd value is 21.016 for members of farming organization which imply

that the respondents who are members of farming organization are over 21 times more likely to

adopt balanced nutrients than those who are not members of farming organization. The odds of

off-farm income and knowledge about soil and water testing laboratory in favour of balanced use

of nutrients increases by a factor of 16 which show that the respondents having off-farm income

and knowledge about soil and water testing laboratory are 16 times more likely to adopt balanced

use of nutrients than those having no off-farm income and no knowledge about testing

laboratories. Similarly, the odds in favour or balanced use of nutrients increases by a factor of

196.593 and 0.004 among respondents who take decision of fertilizer use according to soil type

and having knowledge about impacts of different fertilizer nutrients respectively. The odd value

in favour of balanced use of nutrients increases by 16.288 for respondents who have acquired

primary education. The odd in favour of balanced use of nutrients is decreased by a factor of

0.012 for tenant farming.

Table 3: Logit estimates for the adoption of balanced nutrients in cotton Variables Cotton

Coefficients S.E. Exp(B)LNAGE 43.347* 25.207 0.000LNEXP 1.955** 1.008 7.062LNAGE2 -5.676* 3.452 291.805MFARMERORG 3.045* 1.121 21.016DINFORMALTRAIN 0.195 0.933 1.216OFFFARM 2.807** 1.378 16.565TESTINGSOILWATE 2.791** 1.335 16.294DECISIONSOIL 5.281** 1.701 196.593IMPACTSNPK 5.454*** 1.509 0.004DPRIM 2.790** 1.411 16.288DMIDDLE -0.460 1.455 0.631DMATRIC 1.142 1.494 3.134DTENANT -4.405* 2.414 0.012DOWNTENANT -0.786 1.214 0.455FARMSIZE 0.003 0.017 1.003Constant 71.545* 44.369 1.180E31*, ** and *** indicate significant level at 10, 5 and 1 percent level of significance respectively

Discussion

Results of Table 3 shows estimates of logit model for balanced use of fertilizer nutrients in

cotton (Bt cotton sown in May-June) crop. The odd in favour of adopting balanced nutrients is

positive for increase in age of farmers by 1 year but the odd value became negative for increase

in age of the farmers by twice. This implies that with the increase in age of the farmers the

adoption of balanced fertilization decreased. This is because of the reason that the aged farmers

are reluctant to adopt new practices and technologies thus, making less use of balanced fertilizers

rather they made use of the traditional practices. The odd ratio for the adoption of balanced

nutrients increases among experienced farmers because of the reason that the experienced

farmers are more likely to adopt balanced fertilization in contrast with the inexperienced farmers

on the basis of their higher experience and motivation towards adopting better practices and

technologies that led them to increase the yield of their crop. The odd value is higher for those

farmers who were members of some farming organization because of the reason that they

possess awareness about use of balanced fertilization and its merits. The odd of off-farm income

shows that farmers having some sources of off farm income have financial feasibility to purchase

the fertilizers in order to make balanced use of that. The odd for knowledge about soil and water

testing laboratory shows that the respondents having knowledge about soil and water testing

laboratory will definitely go for their soil and water test and made usage of the fertilizers

according to the prevailing conditions of their soil. Similarly, the positive odds in favour of

balanced use of nutrients among respondents who take decision of fertilizer use according to soil

type and having knowledge about impacts of different fertilizer nutrients indicates the adoption

of balanced fertilizer usage by these respondents due to their awareness about the merits of using

balanced fertilization. The odd value in favour of balanced use of nutrients is higher for the

educated respondents because educated respondents are more likely to adopt balanced

fertilization as compared to illiterate respondents. Zhou et al., (2010) also reported that higher

education significantly decreases the use of over fertilization. The odd in favour of balanced use

of nutrients is negative for tenant farming.

Conclusion

The results regarding logit model indicates that factors like age of the respondent, education,

farming experience, membership of any farming organization, off-farm income, knowledge

about testing soil and water laboratories, knowledge about impacts of different nutrients,

decision of the respondent according to soil type and tenant farming have significant impact on

the adoption of balanced fertilization in cotton crop in that particular locality.

Acknowledgement

The author is thankful to the Endowment Fund Secretariat, University of Agriculture, Faisalabad

for providing funds to conduct this study.

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