COMPARATIVE EVALUATION OF POTATO CULTIVATION AND STORAGE CONSTRAINTS FORPOTATO PRODUCTION IN WEST BENGAL
31 / 19
Keywords:
Potato, Constraints, Fuzzy-AHP, TOPSISAbstract
Potato is the second most important and widely cultivated crop after cereals in West
Bengal. The state’s high potato production is primarily attributed to the favourable climatic conditions
in the districts of Hooghly, Paschim Medinipur, Purba Bardhaman, and Bankura. However, farmers
in these four districts face numerous challenges related to potato cultivation and storage, which
adversely affect both yield and the edible quality of potatoes. Through focus group discussions
and interviews with key stakeholders, fifteen major constraints in potato cultivation and storage
were identified. Data on these fifteen constraints were collected based on four response variables
severity, occurrence, detection, and environmental impact via a survey conducted in sixteen major
potato-growing blocks across these four districts during the year 2025. The relative weights of the
four response variables were determined using the Fuzzy-AHP (Fuzzy Analytic Hierarchy Process)
method, and the fifteen constraints were ranked using the TOPSIS (Technique for Order Preference
by Similarity to Ideal Solution) approach with statistical analysis of the survey data. The TOPSIS
analysis revealed considerable variation in the relative criticality of the identified constraints affecting
potato cultivation and storage. Among the 15 constraints evaluated, Constraint 1: “access to quality
seeds at an affordable price,” obtained the lowest TOPSIS score of 0.3320, indicating that it was the
most critical constraint in the study area. In contrast, Constraint 14: “pest attack during storage,”
recorded the highest TOPSIS score of 0.8214, and was consequently ranked as the least critical or
most favourable constraint among the 15 constraints. Thus, the findings can assist policymakers,
agricultural extension agencies, seed suppliers, cold-storage operators, and other stakeholders in
developing targeted and priority-based interventions rather than adopting a uniform approach to
all identified constraints.
Downloads
References
Ahrari A, Ghag K, Mustafa S, Panchanathan A, Gemitzi
A, Oussalah M and Haghighi AT (2024) Assess the
impact of climate variability on potato yield using
remote sensing data in Northern Finland. Smart
Agric Technol 8: 100485.
Alamar MC, Tosetti R, Landahl S, Bermejo A and
Terry LA (2017) Assuring potato tuber quality
during storage: A future perspective. Front Plant
Sci 8: 2034.
Aung MM and Chang YS (2014) Temperature management
for the quality assurance of a perishable food supply
chain. Food Control 40: 198-207.
Bhattacharyya K and Mitra A (2014) Characterization of
potato growers–a case study in West Bengal State
of India. Econ Aff 59(1): 49-55.
Campos H and Ortiz O (2020) The potato crop: Its
agricultural, nutritional and social contribution to
humankind. Springer Nature, Cham, Switzerland:
518p.
Datta S, Das R and Singh D (2015) Evaluation of genetic
diversity for yield and quality parameters of different
potato (Solanum tuberosum L.) germplasm. J Appl
Nat Sci 7(1): 235-241.
Demirel U (2023) Environmental requirements of potato
and abiotic stress factors. In: Potato Production
Worldwide, pp 71-86. Academic Press.
Demirel U, Morris WL, Ducreux LJ, Yavuz C, Asim
A, Tindas I and Hancock RD (2020) Physiological,
biochemical, and transcriptional responses to single
and combined abiotic stress in stress-tolerant and
stress-sensitive potato genotypes. Front Plant Sci
11: 169.
Deepa N, Khan MZ, Prabadevi B, PM DRV, Maddikunta
PKR and Gadekallu TR (2020) Multiclass model
for agriculture development using multivariate
statistical method. IEEE Access 8: 183749-183758.
Devaux A, Goffart JP, Kromann P, Andrade-Piedra J,
Polar V and Hareau G (2021) The potato of the
future: opportunities and challenges in sustainable
agri-food systems. Potato Res 64(4): 681-720.
Divya KL, Mhatre PH, Venkatasalam EP and Sudha
R (2021) Crop simulation models as decisionsupporting
tools for sustainable potato production:
a review. Potato Res 64(3): 387-419.
Islam S, Li J, Rahman MA, Xie F, Song B and Nie B (2024)
Resistance to biotic and abiotic stress in potato: the
origin of the genes and corresponding molecular
markers. Phytopathol Res 6(1): 4.
Keshavarzi A, Tuffour HO, Bagherzadeh A, Tattrah LP,
Kumar V, Gholizadeh A and Rodrigo-Comino J
(2020) Using fuzzy-AHP and parametric technique
to assess soil fertility status in Northeast of Iran. J
Mt Sci 17(4): 931-948.
Kitinoja L (2013) Use of cold chains for reducing food
losses in developing countries. Population 6(1.23):
5-60.
Kroschel J, Mujica N, Okonya J and Alyokhin A (2020)
Insect pests affecting potatoes in tropical, subtropical,
and temperate regions. In: The Potato Crop: Its
Agricultural, Nutritional and Social Contribution to
Humankind, pp 251-306.
Mangal V, Luthra SK, Sood S, Gupta VK, Bhardwaj V,
Kumar V and Bradshaw JE (2024) Breeding new
cultivars for biotic, abiotic and quality traits. In:
Approaches for Potato Crop Improvement and Stress
Management, pp 119-157. Springer Nature Singapore,
Singapore.
Misganaw E (2016) Host resistance and reduced fungicide
application for management of potato late blight
(Phytophthora infestans) in South west Ethiopia. Asian
J Plant Sci Res 6(2): 13-17.
Okonya JS, Mwanga RO, Syndikus K and Kroschel
J (2014) Insect pests of sweetpotato in Uganda:
farmers’ perceptions of their importance and control
practices. SpringerPlus 3: 1-10.
Piekutowska M, Niedbała G, Piskier T, Lenartowicz
T, Pilarski K, Wojciechowski T and Czechowska-
Kosacka A (2021) The application of multiple linear
regression and artificial neural network models for
yield prediction of very early potato cultivars before
harvest. Agronomy 11(5): 885.
Pinhero RG, Coffin R and Yada RY (2009) Post-harvest
storage of potatoes. In: Advances in Potato Chemistry
and Technology, pp 339-370. Academic Press.
Raigond P, Singh B, Dutt S and Chakrabarti SK (eds)
(2020) Potato. Springer, Singapore.
Raghav YS, Rather KUI, Elwahab MEA, Sharma VK,
Mishra R, Ray S and Mishra P (2025) Advanced
statistical modeling of agricultural potato data using
a novel compound distribution. Potato Res 1-20.
Rouyendegh BD and Savalan Ş (2022) An integrated
fuzzy MCDM hybrid methodology to analyze
agricultural production. Sustainability 14(8): 4835.
Sahu B, Choudhary VK, Sahu MP, Kumar KK,
Sujayanand GK, Gopi R and Ghosh PK (2023) Biotic
stress management. In: Trajectory of 75 Years of Indian
Agriculture after Independence, pp 619-653. Springer
Nature Singapore, Singapore.
Sen A, Chatterjee R, Bhaisare P and Subba S (2018)
Grafting as an alternate tool for biotic and abiotic
tolerance with improved growth and production
of solanaceous vegetables: challenges and scopes
in India. Int J Curr Microbiol Appl Sci 7(1): 121-135.
Singh B, Bhardwaj V, Kaur K, Kukreja S and Goutam U
(2021) Potato periderm is the first layer of defence
against biotic and abiotic stresses: a review. Potato
Res 64(1): 131-146.
Zandi P, Rahmani M, Khanian M and Mosavi A (2020)
Agricultural risk management using fuzzy TOPSIS
analytical hierarchy process (AHP) and failure mode
and effects analysis (FMEA). Agriculture 10(11): 504.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Potato Journal

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright of the articles published in Potato Journal is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.