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FACTORS AFFECTING GUAVA PRODUCTION IN PAKISTAN

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A study was conducted at Technology Transfer Institute (PARC), Tandojam, Pakistan during 2005-06. Primary data were collected from 120 guava producers from major guava producing areas of Sindh and Punjab to identify factors affecting guava production in Pakistan. The results indicate that old planting material, poor management practices, extensive fruit drop and attack of insect pests and diseases are major factors that affect guava production badly. It was investigated that growers do not follow recommendations made by scientists particularly about inputs requirements, because they do not know advantage of proper application of inputs. The results further show that 68 percent variation in guava production is explained by included explanatory variables. Number of inter-culturing and soil type are significant at 1 percent level, whereas, coefficients of number of guava trees, farm yard manure (FYM), fertilizer and number of labour engaged are significant at 5 percent. Area of farmland devoted to guava production is not significant. Moreover, major production inputs such as pesticide sprays, fertilizer, FYM and labour for orchard management are under utilized, affecting guava production.
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Factors affecting guava production 201



FACTORS AFFECTING GUAVA PRODUCTION IN PAKISTAN

Ali Muhammad Khushk, Aslam Memon
and M. Ibrahim Lashari*

ABSTRACT

A study was conducted at Technology Transfer Institute (PARC), Tandojam,
Pakistan during 2005-06. Primary data were collected from 120 guava
producers from major guava producing areas of Sindh and Punjab to identify
factors affecting guava production in Pakistan. The results indicate that old
planting material, poor management practices, extensive fruit drop and attack
of insect pests and diseases are major factors that affect guava production
badly. It was investigated that growers do not follow recommendations made
by scientists particularly about inputs requirements, because they do not know
advantage of proper application of inputs. The results further show that 68
percent variation in guava production is explained by included explanatory
variables. Number of inter-culturing and soil type are significant at 1 percent
level, whereas, coefficients of number of guava trees, farm yard manure (FYM),
fertilizer and number of labour engaged are significant at 5 percent. Area of
farmland devoted to guava production is not significant. Moreover, major
production inputs such as pesticide sprays, fertilizer, FYM and labour for
orchard management are under utilized, affecting guava production.


KEYWORDS: Psidium guajava; production factors; farm inputs; farm
management, Pakistan.

INTRODUCTION

Guava (Psidium guajava), the apple of tropics, is a common fruit in Pakistan.
Mature guava fruits, freshly plucked from tree, have a sweet and attractive
flavour. Fruit is largely eaten fresh, but is also used in jellies and jams. Fruit
contains 82 percent water, 0.7 percent protein, 11 percent carbohydrate and
desirable amounts of vitamin A, B. C, minerals and high amount of pectin. It
contains three to six times more vitamin C than oranges, 10-30 times more
than bananas and about 10 times more than papaya. Guavas are also useful
source of calcium, nicotinic acid, phosphorous and soluble fiber. These are
very good for immune system and are beneficial in reducing cholesterol and
protecting the heart. Like other fruits ad vegetables, guava contains no

*Technology Transfer Institute (PARC), Tandojam, Paksitan.

J. Agric. Res., 2009, 47(2)

A. M. Khushk et al.
202
saturated fat, sodium or cholesterol. There are about 25 calories per guava,
thus experts give maximum marks in terms of its nutritional value.

Guava is extensively grown in Sindh and Punjab. It is a tropical tree and
adapts itself to most conditions of soil and climate. Among major fruits of
Pakistan, guava occupies third position after citrus and mango in terms of
area and production; 183.8 thousand hectares are under citrus, 151.5
thousand hectares under mango and 63.5 thousand hectares under guava.
Data indicate that guava area has increased from 60.3 to 63.5 thousand
hectares during 1999-02 to 2004-05 and production increased from 494.5 to
570.6 thousand tons during the same period (1). Yield of guava (10-12 t/ha) is
less than potential yields. The gap between potential and actual yield occurs
due to poor management practices and post harvest losses. It is believed that
guava production system has been transferred from previous generations and
is dominant among the growers. Traditional methods are commonly used in
guava management where labour is an important input in guava production
process. Production process is not mechanized and is mostly labour
intensive. Majority of growers do not follow modern practices like proper use
of FYM, interculturing, fertilizer application, sprays and timely irrigation.
Problems of post harvest lsoses include improper handling, immature fruit
harvesting and inadequate transport and storage facilities. Post harvest
losses are estimated at 20 to 40 percent of total fruit production in Pakistan
(8).

The present study aims to broadly overview guava production practices being
followed by guava producers and also to identify technical and socio-
economic factors, which limit guava production in Pakistan.

METHODOLOGY

This study was conducted at Technology Transfer Institute (PARC),
Tandojam, Pakistan during 2005-06. A primary survey of guava producers in
major guava growing area in Sindh and Punjab was made and data from 120
guava producers were collected (60 growers from each province).

Production function analysis

Production function analysis was made to identify guava input-output
relationship in form of mathematical function and to gain an understanding of
influences of various inputs on guava output. Once such relationships are
understood than efficient use of inputs can be determined to achieve better
J. Agric. Res., 2009, 47(2)

Factors affecting guava production 203
crop yield. For this purpose Cobb-Douglas type production function was used
to estimate input-output relationship in guava production.

The Cobb-Douglas production function can be used in case of two variable
inputs;

Y = Ax1 b1 X2 b2

where a and b coefficients are estimated by converting all variables both
inputs and outputs into their logarithms and then using ordinary least squares
multiple regression on their logarithms, thus:

Log Y = a + b1 log x1 + b2 log x2

This function is sometimes known as double-log function to distinguish it from
other functions where only one side of the equation is transformed into
logarithms (9). Equation can easily be extended to include more variables.
Marginal products are given as under:



MP1 = dy/dx1 = b1 Ax1 (b1-1) x2 b2 = b1y/x1
MP2 = dy/dx2 = b2y/x2

Average product varies, depending on input level, so it is usually estimated at
average level. Where there are diminishing marginal return, b1 and b2 are
less than 1. Cobb-Douglas production function can be used to estimate
returns to scale provided that all inputs are included in function. Advantages
of this function are that it is easy to estimate, it may show diminishing
marginal returns and it can also be used to estimate return to scale. Possible
demerits are that it cannot show both increasing and diminishing marginal
returns in a single response curve and that may lead to over estimate of
economic optimum (9).

To examine efficiency with which guava producers are using their resources,
marginal value products (MVPs) for respective factors were calculated from
Cobb-Douglas production function. Optimum allocation of resources was
done under constraint of available capital. Test for MVPs was performed by
deriving following equation from Cobb-Douglas function for assessing
resource allocation efficiency:-

MVPj = ?i (Y / X) Py Kj Pxi
where:

J. Agric. Res., 2009, 47(2)

A. M. Khushk et al.
204

MVP =
Marginal value products of the i th input, Xi

?i
=
Output elasticity of the i th input

Y
=
Average (mean) guava output in crates/hectare

X
=
Average (mean) quantity of the i th input


Py
=
Average (mean) price of the output (guave)

Pxi
=
Average (mean) price of the i th input

Ki
=
Allocative efficiency parameters of the i th input

The input is over used if K < 1, and under utilized if K > 1, the input is
efficiently used if K = 1. Results of regression equations were calculated
using Microsoft statistical package. In addition, attempt was made to describe
and analyze the farmer’s management practices in guava orchards. It is
commonly believed that production expansion of any enterprise could be
achieved by improving the existing production system.

Data collection procedure

Initially an informal survey of guava producing area was carried out to
understand existing guava production system. Open ended interviews were
held for each category of respondents to identify key issues and variables.
Sampling frame was prepared and interview checklists and general questions
were refined. Distribution of selected sample size was; small farmers < 12
hectares (30%), medium farmers 12-50 hectares (45%) and large farmers
>50 hectares (25%).

RESULTS AND DISCUSSION

Guava production system

Farm size and guava orchard: Many earlier studies showed a inverse
relationship between farm size and productivity. It was found that due to
higher land use intensity and use of relatively more efficient family labour in
self-cultivated farms, their productivity is higher. It has been argued that large
farmers have higher productivity because they have better access to
production factors such as irrigation water, credit, technical knowledge, etc.
Khan (5) and Mahmood and Haque (7) found that small and large farmers are
more efficient than medium farmers. Hoque (4) observed medium size
farmers as the most efficient. In all these studies, productivity was measured
as gross values product per unit area, which is sum of value of all that was
produced on farm. More recently, Heltberg (3) found that small farms are
more productive as compared to big farms in Pakistan.

J. Agric. Res., 2009, 47(2)

Factors affecting guava production 205
The data (Table 1) revealed that small growers devote greater proportion of
farm area to guava in both provinces. These indicate that small growers have
perhaps tended to maximize land under guava orchard and on remaining land
they grow cereal and fodder crops mainly for their domestic use. In contrast,
large growers have more land that could be converted to guava orchard.
Large growers also clearly indicated during discussion that they are keen to
convert maximum possible area to guava orchard.

Farm yard manure (FYM): The results indicated that growers are regularly
using FYM in guava orchards to maintain fertility level. Manure is usually
applied in a ring around tree. Such rings are dug around base of the tree, 30
cm away from main trunks. Ring is dug to a depth of 8-10 cm, manure is
properly mixed with soil followed by irrigation. At the time of establishment of
new guava orchard, growers normally use 2 to 3 trucks of FYM per acre. FYM
cost per truck ranges between Rs. 1000 to 1500. Growers normally use FYM,
soon after interculturing of guava orchard, which helps guava plant become
healthier and produce more flowering in early October. Finally, it was
observed that growers do not follow any recommendations made by the
scientists in respect of nutrient requirements of guava.

Use of fertilizer: Guava plants depend heavily on soil nutrients and
particularly nitrogen, phosphorus ad potash. Matured trees may require as
much as ½ pound actual nitrogen per year. In guava, fruits are borne on
current season’s growth. In study area very little use of feriltizer was noted in
guava orchards. Growers applied 2 bags of urea and 1.5 bags of DAP per
acre. It was also observed that guava growers have not recognized the
importance of potash although potash requirement for guava tree is higher
than any other essential nutrient.

Yield and farm size:
Yield differences by farm size were not consistent
between small, medium and large growers for guava orchards in both Sindh
and Punjab provinces (Table 2). No variation was found in management
practices and input use among these categories.
J. Agric. Res., 2009, 47(2)

A. M. Khushk et al.
206



Plant population and guava yield: Plant population was not found to be
systematic or regular in all types of guava orchard. It was noted that growers
who planted their orchard about 15 years ago, planted about 67 trees per
acre in Sindh and 65 trees per acre in Punjab (Table 3). However, in recent
years growers have realized importance of plant space and decreased
number of trees to about 55 in Sindh and 52 in Punjab.

Guava yield varied from farm to farm and there are number of reasons for
yield variation i.e. plant population, management practices, attack of insect
pests and diseases. Guava tree starts produce after third year of planting and
it gives maximum yield after 15th year. The results also indicate that growers
in both provinces i.e. Sindh and Punjab received maximum yield of 916.1 and
893.8 crates per acre, respectively (Table 3). It was also reported by guava
producers that guava production could be increased by maintaining proper
plant population.



Intercropping in guava orchard: In early stages of establishment of guava
orchard till bearing, inter-space can be economically utilized by growing
suitable intercrops. In a crop combination, vegetables and fodder crops are
considered as safe intercrops. However, when trees are full grown,
J. Agric. Res., 2009, 47(2)

Factors affecting guava production 207
intercropping is neither feasible nor desirable. In Sindh province no guava
grower intercropped in matured guava orchard. However, in Punjab 95
percent farmers intercropped berseem in guava orchard, 67.5 percent wheat
and 35 percent respondents intercropped vegetables in rabi. In kharif season,
62.5 percent farmers intercropped maize in guava orchard, 62.5 percent
sorghum and 50 percent intercropped vegetables.

Factors affecting guava production

Guava production is a complex process and can be conceived as a function
of several variables. Knowledge of relative importance of resource inputs
influencing guava production is essential for guava producers so that
desirable changes may be introduced in their operation at micro level. It will
also help policy makers formulate plans for improvements in horticulture
sector productivity based on sound economic principles at macro level.
Production practices such as planting material, plant space, soil type ad
availability of irrigation have considerable impact on guava yield. While
analyzing inputs and output relationship of guava production, important inputs
i.e. chemical fertilizer, FYM, pesticides, interculturing and use of labour were
considered.

It has been argued that there are various problems in estimating input output
relationship using survey data, because variables are not controlled as these
are in an experiment. Environmental conditions and managerial ability vary
from farm to farm. Ultimately, these factors affect crop output. To achieve
maximum income from guava cultivation, precise estimation of resources
productivity and examination of allocation efficiency of various factors
affecting guava production would help producers to allocate their resources
optimally. Therefore, both inputs and output factors analysis was carried out.
For this purpose ordinary least squares regression method is widely used
which enables not only to find the line of best fit, but also to measure how
good a fit it is.

Crop input and output relationship has most often been examined on an
individual plot basis but it is better for permanent crops like guava to estimate
on a per tree basis. However, in this case guava growers and contractors
provided information on per hectare basis. Therefore, in absence of detailed
information of guava input and output on per tree basis, the decision was to
estimate on per hectare basis. Input factors such as, chemical fertilizer, FYM,
pesticides and use of machinery, purchase prices for hire rates were used.
Hired labour, family lahour, draft animals, equipment and other resources
were recorded and converted into standard man-days. The output of guava
J. Agric. Res., 2009, 47(2)

A. M. Khushk et al.
208
per hectare was estimated including quantity of guava both marketed and
used for home consumption.

The optimum allocation fo resources was done under the constraint of
available capital. To examine impact of various inputs on guava production,
the Cobb-Douglas production function has been fitted, fertilizer, pesticide
spray, interculturing and labour use. Also log data of continuous variable such
as, guava yield, area, trees and farmyard manure (FYM) were used in the
production function, zero order correlation matrices were worked out and
correlation coefficient were examined to detect the multicollinearity problems.
If value of coefficient of correlation between any two explanatory variables
was less than the value of coefficient of multiple determination, then it could
not be treated as a problem of multicollinearity (6). It was found from
correlation matrix that ploughing and land leveling variables were highly
correlated, therefore, these were excluded from analysis. The descriptive
statistics of major production inputs are presented in Table 4.

The results of regression analysis show that 68 percent of variations in guava
production are explained by included explanatory variables. The parameters
estimates obtained for number of interculturings and soil type are at one
percent level. However, coefficients of number of labour engaged are
significant at 5 percent level (P = 0.05). The area of farm land devoted to
guava production is not significant (Table 5).




J. Agric. Res., 2009, 47(2)

Factors affecting guava production 209


Regression coefficients of MVPs of major production inputs were statistically
significant in production function and these are set out alongwith their prices.
All inputs and output were expressed in monetary terms, the criterion used
here to examine resource allocation efficiency. The results derived from
Cobb-Dauglas function were analyzed and presented in Table 6.

The estimates of MVPs and allocative efficiency parameters (K) show that all
major inputs for guava production were underutilized by growers. It appears
that pesticide spray and labour were particularly poorly utilized in existing
guava production system. Results also suggest that there are opportunities to
enhance guava production by increasing expenditure on major inputs and
management practices.

CONCLUSION AND RCOMMENDATIONS

The foregoing analysis has indicated that major production inputs such
as pesticide sprays, fertilizer, FYM and use of labour for management
practices are underutilized, affecting guava production. It was also
investigated that guava producers do not know the advantages of
proper use of inputs such as sprays and fertilizer. They think that
application of fertilizer in fruit orchards encourages the vegetative
growth of plant and does not increase guava production. Use of
chemical sprays and use of labour appear to be limited by available
resources with guava producers. It is, therefore, suggested that proper
J. Agric. Res., 2009, 47(2)

A. M. Khushk et al.
210
dose of chemical fertilizer and timely use of chemical sprays are
essential to achieve better guava production.

Moreover, it is also recognized that some social factors are playing an
important role in process of guava production. These have not been
included in this analysis because of difficulties in their quantification
and non-availability of data. This however, does not reduce the
importance of assessing their impact on economic development,
particularly in developing countries where social institutions are
relatively more important both from view point of helping or hampering
the development efforts.

The major problems in guava production identified are: old planting
material, poor management practices, extensive fruit droppage and
attack of insects and pests. It is clearly indicated that this sector has a
tremendous scope for future expansion of production and export
performance. This would be possible by screening existing potential
planting material as it has the potential to improve production upto 30-
40 percent when combined with improved management practices and
adoption of scientific recommendations.

REFERENCES

1. Anon. 2005. Agricultural Statistics of Pakistan. 2004-05. Ministry of
Food, Agriculture and Livestock (Economics Wing), Govt. of Pakistan,
Islamabad.
2. Hedge, H.G. and J. P. Tiwari. 1981. Tropical and Subtropical Fruit
Crops. Nat. Symp. Banglore, p. 83.
3.
Heltberg, R. 1996. How Rural Market Imperfections Shape the Relation
between Farmsize and Productivity. A General Framework and an
application to Pakistan data. Institute of Economics, University of
Copenhagen, Denmark.
4. Hoque, A. 1988. Farm Size and Economic Allocative Efficiency in
Bangladesh Agriculture. Applied Economics. 20(10):1353-1368.
5. Khan, M. H. 1979. Farm Size and Land Productivity Relationship in
Pakistan. Pakistan Development Review. 28(1):68-77.
6.
Klein, L. R. 1973. An introduction of economics. Prentice-Hall of India
Pvt. Ltd. New Delhi. International Horticulture Seminar. January 9-11.
7.
Mahmood, M. and N. Haque. 1981. Farm Size Productivity Revisited.
Paksitan Development Review. 20(2):150-190.
8. Malik, M. N. 1993. Challenges for the year 2000 in the Field of
Horticulture. Proc.First International Horticulture Seminar. January 9-11.
9. Upton, M. 1996. The Economics of Tropical Farming System,
Cambridge University Press, UK.
J. Agric. Res., 2009, 47(2)

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