Performance Evaluation of Urban Vegetable Production in Kashmir: A Statistical Analysis from the Narkara Cluster

Abstract

Urban and peri-urban agriculture is gaining importance as a tool for achieving food security, employment, and sustainable development. This study evaluates the key determinants of vegetable production performance in the Narkara vegetable cluster on the outskirts of Srinagar city, Jammu & Kashmir. Utilizing primary data from 60 growers, a multiple linear regression model was employed to examine how land area, fertilizer use, plant protection expenses, and labor costs influence gross returns. The findings underscore the central role of landholding and labor input in driving productivity. The paper concludes with recommendations to optimize input efficiency and scale up urban agricultural potential in Kashmir.

Introduction

Urbanization in Kashmir has increased the demand for fresh produce while reducing arable land, pushing farmers toward intensive urban horticulture. This study evaluates which farm inputs most influence vegetable production performance in the Narkara cluster, a prominent peri-urban farming zone near Srinagar.

Objectives:

1. Assess resource use and production economics among vegetable growers.

2. Statistically evaluate the contribution of key inputs to gross farm income.

3. Identify priority areas for improving input efficiency and profitability.

Methodology:

• Study Area: Narkara cluster (Qazipora, Bunpora, Badamohalla, Baghandar), 7–9 km from Srinagar.

• Sample: 60 vegetable farmers (mostly smallholders with <1 ha land).

• Data Period: February–July 2019.

• Data Collected On:

  • Land under cultivation

  • Expenditures on fertilizers, manures, and pesticides

  • Human labor input

  • Gross income from vegetable sales

Analytical Approach:

• Tool Used: Multiple Linear Regression

• Model:

  Y=β0+β1X1+β2X2+β3X3+β4X4+UY = β? + β?X? + β?X? + β?X? + β?X? + UY=β0?+β1?X1?+β2?X2?+β3?X3?+β4?X4?+U

  • Y: Gross return per hectare

  • X?: Land area (ha)

  • X?: Fertilizer & manure cost

  • X?: Plant protection cost

  • X?: Labor cost

  • U: Error term

Key Insight (Implied):

The regression model helps isolate which inputs (e.g., land size, fertilizer use, plant protection, labor) most significantly drive farm income, offering evidence-based insights for improving input allocation and policymaking in urban agriculture.

Copyright

Copyright © 2025 Sehreena Maqbool. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.