Advances in ISSN: 2373-6402APAR

Plants & Agriculture Research
Research Article
Volume 4 Issue 5 - 2016
Quantitative Analysis of Returns from Vegetable Seed Crop and Fresh Vegetables, a Case of District Gilgit (Gilgit-Baltistan)
Verma AK* and Singh Deepti
Munir Ahmed, Ali Noor Shah M Azhar Javaid* and Tajwar Alam
Received: May 10, 2016 | Published: September 26, 2016
*Corresponding author: Ali Noor Shah M Azhar Javaid, Senior Scientist, National Institute of Organic agriculture, Pakistan, Email:
Citation: Ahmed M, Javaid ANM, Alam T (2016) Quantitative Analysis of Returns from Vegetable Seed Crop and Fresh Vegetables, a Case of District Gilgit (Gilgit-Baltistan). Adv Plants Agric Res 4(5): 00151. DOI: 10.15406/apar.2016.04.00151

Abstract

The objective of this study was to estimate and compare the costs and revenues of selected vegetables grown for fresh consumption to that of seed crops in district Gilgit. The analysis is based on survey data for 2011-12 harvesting year. Mean comparing t-statistics with dummy variable approach is used as data concordance with each other; indicate that except for net revenue of onion the costs and net revenue of selected vegetables for consumption and seed are statistically different. The analysis conclude that vegetable fresh crops give higher net revenues than vegetable seed in project area due to the high cost of production and low price of output of seed crops. The study reveals, however, that vegetable seed crops have the potential to become attractive enterprise if proper attention is given to develop production and marketing infrastructure.

Keywords: Labour intensive culture; Vegetable seed; Consumption; Gilgi; Harvesting; Revenues; Infrastructure

Introduction

Development of vegetable sub sector is of great importance in densely populated developing countries with high unemployment due to its labour intensive culture; high value added ability both as commodity and as a processed final product and high nutritional value. Quality seed is a prerequisite for development of vegetable sector but unfortunately the annual vegetable seed production in Pakistan is about 84 tons that is negligible quantity for the requirement of the country Akhonzada [1]. Most of the vegetable seed requirements are met through imports from Europe, USA, Japan and India. Thus vegetable seed production is not only important for development of vegetable sector but also will earn/save scarce foreign exchange. The UNDP, The British High commission, AKRSP, and other donor agencies are pushing for introducing vegetable and vegetable seed production to replace poppy and as a strategy of poverty alleviation in Northern Pakistan. The empirical literature documents the importance of relative profitability of vegetable and vegetable seed production and factors affecting them. For instance, Defoer et al. [2] and Malik A [3] for Pakistan, Thakur et al. [4] and Kutty et al. [5] for India, and Groin et al. [6] for sub-Saharan Africa show comparatively higher net returns from vegetable and vegetable seed production than other crops. Studies such as Santini [7] for Itlay, Abak et al. [8] for Turkey, and Vansickle et al. [9] for Canada USA depict that lack of modern techniques, inefficient production and marketing infrastructure are seriously affecting the costs and net returns of vegetable and vegetable seed production. In this paper, we use quantitative analysis to:

  1. Estimate and compare the costs and net revenue of selected vegetable grown for consumption and seed crops;
  2. Identify the factors effecting the production and marketing of vegetable and vegetable seed
  3.  Forward policy recommendations for the improvement of vegetable seed production.

Material and Methods

The study is carried out in district Gilgit, Gilgit-Baltistan due to its ideal climatic conditions for vegetable seed production and its recent introduction by AKRSP through North south seed corporation as a strategy for poverty alleviation. Primary data was collected for selected vegetables i.e. onion, tomato and peas for the harvesting season 2004-2005 from 90 growers, 45 each for consumption and seed crops. A pretested questionnaire is used to get the background information of growers, data on economics of vegetables production and problems faced by the growers.

Data analysis techniques

Budgeting technique is used to arrive at costs net revenues of selected vegetables grown for consumption and seed crops. Then differences between the costs and benefits of the two types of vegetable crops, that is, fresh vegetable crop and the one produced as seed crop, are analyzed by the following techniques.

Comparing two means: using t-statistics

Partial budgeting uses simple averages to compare the costs and net revenues of two scenarios but these statements cannot decide whether the differences statistically significant or not. For this purpose, we can use the “Test of difference between two means” newbold [10] there are generally two such tests, namely.

Test of difference between two means of matched pair: This test hypothesis:

H 0 : μ vc = μ vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamisaK qbaoaaBaaaleaajugWaiaaicdaaSqabaqcLbsacaGG6aGaeqiVd02c daWgaaqaaKqzadGaamODaiaadogaaSqabaqcLbsacqGH9aqpcqaH8o qBlmaaBaaabaqcLbmacaWG2bGaam4CaaWcbeaaaaa@46E2@

H 1 : μ vc μ vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamisaS WaaSbaaeaajugWaiaaigdaaSqabaqcLbsacaGG6aGaeqiVd02cdaWg aaqaaKqzadGaamODaiaadogaaSqabaqcLbsacqGHGjsUcqaH8oqBlm aaBaaabaqcLbmacaWG2bGaam4CaaWcbeaaaaa@4716@

Where:

μ vc MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqiVd0 2cdaWgaaqaaKqzadGaamODaiaadogaaSqabaaaaa@3B78@ =Average cost (or net revenues) of fresh crops

μ vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqiVd0 wcfa4aaSbaaeaajugWaiaadAhacaWGZbaajuaGbeaaaaa@3C8E@ =Average costs (or net revenues) of seed crops

The t-statistics is:
t-statistics = d ¯ s d / n MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqbaoaalaaake aajuaGdaqdaaGcbaqcLbsacaWGKbaaaaGcbaqcLbsacaWGZbqcfa4a aSbaaSqaaKqzadGaamizaaWcbeaajugibiaac+cajuaGdaGcaaGcba qcLbsacaWGUbaaleqaaaaaaaa@4098@  (1)

Where  is the mean of differences ( d i ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqbaoaabmaake aajugibiaadsgalmaaBaaabaqcLbmacaWGPbaaleqaaaGccaGLOaGa ayzkaaaaaa@3BE1@ between fresh and seed crop for every observation and  is the standard deviation of that differences.

The decision rule is:

Reject H0 (in favor of H1 ) if t calculated < t n1 a 2 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamiDaS WaaSbaaeaajugWaiaadogacaWGHbGaamiBaiaadogacaWG1bGaamiB aiaadggacaWG0bGaamyzaiaadsgaaSqabaqcLbsacqGH8aapcqGHsi slcaWG0bWcdaWgaaqaaKqzadGaamOBaiabgkHiTiaaigdaaSqabaqc fa4aaSaaaOqaaKqzGeGaamyyaaGcbaqcLbsacaaIYaaaaaaa@4D07@ or t n1 a 2 > t calculated MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamiDaS WaaSbaaeaajugWaiaad6gacqGHsislcaaIXaaaleqaaKqbaoaalaaa keaajugibiaadggaaOqaaKqzGeGaaGOmaaaacqGH+aGpcaWG0bWcda WgaaqaaKqzadGaam4yaiaadggacaWGSbGaam4yaiaadwhacaWGSbGa amyyaiaadshacaWGLbGaamizaaWcbeaaaaa@4B8F@ (2)

Test of Difference between Two Means of Independent Samples: Though the hypothesis remains the same b but test statistics changes for this particular test for independence samples.

t- Statistics = x vc ¯ x vs ¯ S ve 2 n ve + S vs 2 n vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqbacbaaaaaaa aapeWaaSaaaOqaaKqbaoaanaaakeaajugibiaadIhajuaGdaWgaaWc baqcLbmacaWG2bGaam4yaaWcbeaaaaqcLbsacqGHsisljuaGdaqdaa GcbaqcLbsacaWG4bqcfa4aaSbaaSqaaKqzadGaamODaiaadohaaSqa baaaaaGcbaqcfa4aaOaaaOqaaKqbaoaalaaakeaajugibiaadofalm aaDaaabaqcLbmacaWG2bGaamyzaaWcbaqcLbmacaaIYaaaaaGcbaqc LbsacaWGUbWcdaWgaaqaaKqzadGaamODaiaadwgaaSqabaaaaKqzGe Gaey4kaScaleqaaKqbaoaalaaakeaajugibiaadofalmaaDaaabaqc LbmacaWG2bGaam4CaaWcbaqcLbmacaaIYaaaaaGcbaqcLbsacaWGUb qcfa4aaSbaaSqaaKqzadGaamODaiaadohaaSqabaaaaaaaaaa@5F61@

Where x vc ¯ MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqbacbaaaaaaa aapeWaa0aaaOqaaKqzGeGaamiEaKqbaoaaBaaaleaajugWaiaadAha caWGJbaaleqaaaaaaaa@3C16@ and x vs ¯ MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqbacbaaaaaaa aapeWaa0aaaOqaaKqzGeGaamiEaKqbaoaaBaaaleaajugWaiaadAha caWGZbaaleqaaaaaaaa@3C26@ are means of costs (or net revenues) selected vegetables and S vc 2 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeaeaaaaaa aaa8qacaWGtbWcdaqhaaqaaKqzadGaamODaiaadogaaSqaaKqzadGa aGOmaaaaaaa@3CA5@ and S vs 2 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeaeaaaaaa aaa8qacaWGtbWcdaqhaaqaaKqzadGaamODaiaadohaaSqaaKqzadGa aGOmaaaaaaa@3CB5@ and n vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeaeaaaaaa aaa8qacaWGUbqcfa4aaSbaaSqaaKqzadGaamODaiaadohaaSqabaaa aa@3B73@ and n vc MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeaeaaaaaa aaa8qacaWGUbWcdaWgaaqaaKqzadGaamODaiaadogaaSqabaaaaa@3AD5@ are variances and sample sizes.

Comparing Two Means: Using Dummy Variable Approach: Though for comparing two means, the aforementioned t-statistics has relative advantage over partial budgeting, however, it fail to explain the size of the difference of one variable from another. Dummy variable method, a still more sophisticated econometric technique, is use to address this concern (Gujrati, 1995 : page 499). For comparison of costs, the model is specified as follows:

C= β β 0 +β β 1 D MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi MaeqOSdi2cdaWgaaqaaKqzadGaaGimaaWcbeaajugibiabgUcaRiab ek7aIjabek7aITWaaSbaaeaajugWaiaaigdaaSqabaqcLbsacaWGeb aaaa@4406@ (3)

Where:

C= cost of selected vegetable production (consumption and seed crops)

D= 1 for seed crop and 0, otherwise.

β 0 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi 2cdaWgaaqaaKqzadGaaGimaaWcbeaaaaa@3A3A@ and + β 1 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi 2cdaWgaaqaaKqzadGaaGymaaWcbeaaaaa@3A3B@ are to be estimated. The estimated β 0 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi 2cdaWgaaqaaKqzadGaaGimaaWcbeaaaaa@3A3A@ gives the average costs of vegetable grown for consumption, while β 1 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi 2cdaWgaaqaaKqzadGaaGymaaWcbeaaaaa@3A3B@ measures the size by which the costs of vegetable grown for consumption differ from that of seed crops. In the same token, if the revenues of the two scenarios are to be compared, instead of costs (C), revenues (R) would be taken and used as dependent variable in equation 3. For a significant difference, β 1 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaeqOSdi 2cdaWgaaqaaKqzadGaaGymaaWcbeaaaaa@3A3B@ needs to be statistically different from zero.

Results and Discussion

We have used the two t-tests given in equation 1 and 2 to see whether there are significant differences of costs and benefits across the fresh vegetable crop and vegetable seed – crop. The results obtained for differences in costs and net revenues are provided in (Table 1, 2), respectively. More specifically, equation 2, the independent- sampled t-test, is used in Table 1, for comparing costs of onion and tomato production due to insignificant correlation (r=0.195 and 0.03) between cost variables respectively; whereas equation 1, the paired -sample t test, is used for comparing cost for peas production due to significant correlation (r=0.62) between its cost variables. Alternatively the coefficient of correlation between the revenue was significant for onion and tomato and non-significant for peas, therefore we have used equation 1, the paired-Sampled t-test, in Table 2 for comparing the revenues of onions and tomato while we have used equation 2, the independent-sampled t-test for peas.

Crops

t-Statistics Used

Calculated Value

Tabulated Value

Onion

Equation 2

2.77

2.05

Tomato

Equation 2

3.44

2.05

Peas

Equation 1

4.968

2.05

Table 1: Comparison of production costs of vegetable grown for consumption and seed crops.

Crops

t-Statistics Used

Calculated Value

Tabulated Value

Onion

Equation 1

0.352

2.05

Tomato

Equation 1

5.36

2.05

Peas

Equation 2

4.88

2.05

Table 2: Comparison of net revenue of vegetable grown for consumption and seed crops.

Table 1: depicts that for each of the three crops, the calculated t-ratio are grater then tabulated value, thus we accept alternative hypothesis. H 1 : μ vc μ vs MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamisaS WaaSbaaeaajugWaiaaigdaaSqabaqcLbsacaGG6aGaeqiVd02cdaWg aaqaaKqzadGaamODaiaadogaaSqabaqcLbsacqGHGjsUcqaH8oqBlm aaBaaabaqcLbmacaWG2bGaam4CaaWcbeaaaaa@4716@ This indicates that per acre cost of vegetable production for fresh consumption crop are statistically different from that of seed crops.

Onion

TC= 53243 ( 6.07 ) + 30671 D ( 2.73 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamivai aadoeacqGH9aqpjuaGdaWcaaGcbaqcLbsacaaI1aGaaG4maiaaikda caaI0aGaaG4maaGcbaqcfa4aaeWaaOqaaKqzGeGaaGOnaiaac6caca aIWaGaaG4naaGccaGLOaGaayzkaaaaaKqzGeGaey4kaSscfa4aaSaa aOqaaKqzGeaeaaaaaaaaa8qacaaIZaGaaGimaiaaiAdacaaI3aGaaG ymaiaabccacaWGebaak8aabaqcfa4aaeWaaOqaaKqzGeGaaGOmaiaa c6cacaaI3aGaaG4maaGccaGLOaGaayzkaaaaaaaa@5162@ (4)

NR= 81272 ( 5.34 ) 8725 D ( 0.493 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamOtai aadkfacqGH9aqpjuaGdaWcaaGcbaqcLbsaqaaaaaaaaaWdbiaaiIda caaIXaGaaGOmaiaaiEdacaaIYaaak8aabaqcfa4aaeWaaOqaaKqzGe WdbiaaiwdacaGGUaGaaG4maiaaisdaaOWdaiaawIcacaGLPaaaaaqc LbsacqGHsisljuaGdaWcaaGcbaqcLbsapeGaaGioaiaaiEdacaaIYa GaaGynaiaabccacaWGebaak8aabaqcfa4aaeWaaOqaaKqzGeWdbiaa icdacaGGUaGaaGinaiaaiMdacaaIZaaak8aacaGLOaGaayzkaaaaaa aa@51DE@ (5)

Tomato

TC= 38158 ( 9.3 ) + 11326 D ( 1.94 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamivai aadoeacqGH9aqpjuaGdaWcaaGcbaqcLbsaqaaaaaaaaaWdbiaaioda caaI4aGaaGymaiaaiwdacaaI4aaak8aabaqcfa4aaeWaaOqaaKqzGe WdbiaaiMdacaGGUaGaaG4maaGcpaGaayjkaiaawMcaaaaajuaGcqGH RaWkdaWcaaGcbaqcLbsapeGaaGymaiaaigdacaaIZaGaaGOmaiaaiA dacaqGGaGaamiraaGcpaqaaKqbaoaabmaakeaajugib8qacaaIXaGa aiOlaiaaiMdacaaI0aaak8aacaGLOaGaayzkaaaaaaaa@507B@ (6)

NR= 63803 ( 3.8 ) 63131 D ( 2.66 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamOtai aadkfacqGH9aqpjuaGdaWcaaGcbaqcLbsaqaaaaaaaaaWdbiaaiAda caaIZaGaaGioaiaaicdacaaIZaaak8aabaqcfa4aaeWaaOqaaKqzGe WdbiaaiodacaGGUaGaaGioaaGcpaGaayjkaiaawMcaaaaajugibiab gkHiTKqbaoaalaaakeaajugib8qacaaI2aGaaG4maiaaigdacaaIZa GaaGymaiaabccacaWGebaak8aabaqcfa4aaeWaaOqaaKqzGeWdbiab gkHiTiaaikdacaGGUaGaaGOnaiaaiAdaaOWdaiaawIcacaGLPaaaaa aaaa@5206@ (7)

Peas

TC= 28152 ( 16.3 ) + 7469 D ( 3.1 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamivai aadoeacqGH9aqpjuaGdaWcaaGcbaqcLbsaqaaaaaaaaaWdbiaaikda caaI4aGaaGymaiaaiwdacaaIYaaak8aabaqcfa4aaeWaaOqaaKqzGe WdbiaaigdacaaI2aGaaiOlaiaaiodaaOWdaiaawIcacaGLPaaaaaqc LbsacqGHRaWkjuaGdaWcaaGcbaqcLbsapeGaaG4naiaaisdacaaI2a GaaGyoaiaabccacaWGebaak8aabaqcfa4aaeWaaOqaaKqzGeWdbiaa iodacaGGUaGaaGymaaGcpaGaayjkaiaawMcaaaaaaaa@504A@ (8)

NR= 38642 ( 7.4 ) 61815 D ( 8.4 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiVCI8FfYJH8YrFfeuY=Hhbbf9v8qqaqFr0xc9pk0xbb a9q8WqFfeaY=biLkVcLq=JHqpepeea0=as0Fb9pgeaYRXxe9vr0=vr 0=vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaKqzGeGaamOtai aadkfacqGH9aqpjuaGdaWcaaGcbaqcLbsaqaaaaaaaaaWdbiaaioda caaI4aGaaGOnaiaaisdacaaIYaaak8aabaqcfa4aaeWaaOqaaKqzGe WdbiaaiEdacaGGUaGaaGinaaGcpaGaayjkaiaawMcaaaaajugibiab gkHiTKqbaoaalaaakeaajugib8qacaaI2aGaaGymaiaaiIdacaaIXa GaaGynaiaabccacaWGebaak8aabaqcfa4aaeWaaOqaaKqzGeWdbiab gkHiTiaaiIdacaGGUaGaaGinaaGcpaGaayjkaiaawMcaaaaaaaa@5154@ (9)

Table 2: In contrasts, gives the results of t-test for differences in the net revenues of selected vegetable crops. The results show that the net revenue in case of onion, whether grown for fresh and seed crop do not differ significantly, however, the net revenues from fresh and seed crops significantly differ for tomato and peas crops.

The results of dummy variable approach given in equation 3, further reinforce the t-tests results already discussed; these results, in addition, give the direction and magnitudes of the differences. The fallowing results of dummy variable analysis given in equation (4) to (9) indicate that cost of production of onion seed crop is significantly higher than that of fresh crop. Onion seed crop is produced at Rs.83914 (or 53243+Rs.30671) per acre. The reasons for higher costs of vegetable seed crop production specially of onion are due to its recent introduction to the study area and therefore lake of basic infrastructural facilities and cultural and marketing experience on the part of farmers. Though the costs of onion seed crop production is higher than the fresh crop by about 58 percent, the seed crop does not produce extra net revenue; rather the net revenue from seed crop is less ( by Rs.8725 ) than that of fresh crop ( Rs.81272) per acre.

The cost of tomato and peas seed crops is respectively, higher by 29.68 and 26.56 percent than that of fresh crop (Rs.38158 and Rs.28125) meant by consumption purposes. The revenues, however, of both tomato and peas seed crops are less than the fresh crops; in case of tomato, net revenue are less by 98.95 percent and in case of peas, less by about 160 percent, rather it is negative in the case of peas. Though the costs of seed crop production for tomato and peas are less than the onion, however, the net revenues from these crops are lower than onion due to lower prices of their seed output.

Conclusion and Recommendations

The study was designed to estimate and compare the costs and net revenue of selected vegetables grown as fresh crop and seed crop in District Gilgit. Given current set of sectoral condition, policies and motivation from NGOs production of selected vegetables for fresh crop seems to be profitable enterprise. However, at present, their production for seed crop does not look that much attractive due to high costs of production and low prices of seed output. The study further reveals that vegetables production for seed crop is newly introduced enterprise in the research area, its production and marketing is plagued with major problems particularly lack of marketing infrastructure for proper supply of input and marketing of vegetable output of seed and fresh crops in the study area. Looking at the tremendous potential of Northern Areas of Pakistan in general and Gilgit, in particular, in production of vegetables, vegetable seeds and all sorts of high value crops, the key for policy is to forge efforts of policy makers, scientists, and all the stalk holders to orient vegetable sector and related institutions and established it on modern lines of agribusiness to make it an effective strategy for poverty reduction in Northern areas (Gilgit-Baltistan). Some of the recommendations suggested by the study area as follow.

  1. A comprehensive study needed to see production and marketing infrastructure requirements of vegetable sector development, in general and vegetable seeds crops, in particular.
  2. Increase understanding of policy makers and the stalk holders to plan the vegetable sector on modern lines of agribusiness and use it as a strategy for poverty reduction in Northern Areas (Gilgit-Baltistan). The extension department, cooperatives and NGOs can play important role in this direction.
  3. The government can help in this direction by providing the infrastructure and institutional support and encourage the private sector to invest in different sub sectors of the vegetable sector that will not only increase the production and income of farmers but also will contribute to poverty alleviation and sustainable development [10,11].

References

  1. Ribant JM, Banziger M, Hoisington D (2002) Genetic dissection and plant improvement under abiotic stress conditions: drought tolerance in maize as an example. JIRCAS Working Report 85-92.
  2. Wang H, Wang H, Shao H, Tang X (2016) Recent Advances in Utilizing Transcription Factors to Improve Plant Abiotic Stress Tolerance by Transgenic Technology. Front Plant Sci 7: 67.
  3. Shinozaki K, Yamaguchi-Shinozakiy K, Sekiz M (2003) Regulatory network of gene expression in the drought and cold stress responses. Curr Opin Plant Biol 6(5): 410–417.
  4. Dhlamin Z, Spillane C, Moss JP, Rune J, Urquia N, et al. (2005) Status of research and application of crop biotechnology in developing countries. Food and Agriculture Organization of the United Nation Rome 35-36.
  5. Shao H, Wang H, Tang X (2015) NAC transcription factors in plant multiple abiotic stress responses: progress and prospects. Front Plant Sci 6: 902.
© 2014-2016 MedCrave Group, All rights reserved. No part of this content may be reproduced or transmitted in any form or by any means as per the standard guidelines of fair use.
Creative Commons License Open Access by MedCrave Group is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at http://medcraveonline.com
Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version | Opera |Privacy Policy