Multi-criteria clustering analytics for agro-based perishables in cold-chain

Abstract

Purpose

The purpose of this paper is to determine compatibility groups of different fruits and vegetables that can be stored and transported together based upon their requirements for temperature, relative humidity, odour and ethylene production. Pre-cooling which is necessary to prepare the commodity for subsequent shipping and safe storage is also discussed.

Design/methodology/approach

The methodology used in this journal is an attempt to form clusters/groups of storing together 43 identified fruits and vegetables based on four important parameters, namely, temperature, relative humidity, odour and ethylene production. An agglomerative hierarchical clustering algorithm is used to build a cluster hierarchy that is commonly displayed as a tree diagram called dendrogram. The same is further analyzed using K-means clustering to find clusters of comparable spatial extent. The results obtained from the analytics are compared with the available data of grouping fruits and vegetables.

Findings

This study investigates the usefulness and efficacy of the proposed clustering approach for storage and transportation of different fruits and vegetables that will eventually save huge investment made in terms of developing infrastructure components and energy consumption. This will enable the investors to adopt it for using the space more effectively and also reducing food wastage.

Research limitations/implications

Due to limited research and development (R&D) data pertaining to storage parameters of different fruits and vegetables on the basis of temperature, relative humidity, ethylene production/sensitivity, odour and pre-cooling, information from different available sources have been utilized. India needs to develop its own crop specific R&D data, since the conditions for soil, water and environment vary when compared to other countries. Due to the limited availability of the research data, various multi-criteria approaches used in other areas have been applied to this paper. Future studies might be interested in considering other relevant variables depending upon R&D and data availability.

Practical implications

With the increase in population, the demand for food is also increasing. To meet such growing demand and provide quality and nutritional food, it is important to have a clear methodology in terms of compatibility grouping for utilizing the available storage space for multi-commodity produce and during transportation. The methodology used shall enable the practitioners to understand the importance of temperature, humidity, odour and ethylene sensitivity for storage and transportation of perishables.

Social implications

This approach shall be useful for decision making by farmers, Farmer Producer Organization, cold-storage owners, practicing managers, policy makers and researchers in the areas of cold-chain management and will provide an opportunity to use the available space in the cold storage for storing different fruits and vegetables, thereby facilitating optimum use of infrastructure and resources. This will enable the investors to utilize the space more effectively and also reduce food wastage. It shall also facilitate organizations to manage their logistic activities to gain competitive advantage.

Originality/value

The proposed model would help decision makers to resolve the issues related to the selection of storing different perishable commodities together. From the secondary research, not much research papers have been found where such a multi-criteria clustering approach has been applied for the storage of fruits and vegetables incorporating four important parameters relevant for storage and transportation.

Citation

Bhatnagar, A., Vrat, P. and Shankar, R. (2019), "Multi-criteria clustering analytics for agro-based perishables in cold-chain", Journal of Advances in Management Research, Vol. 16 No. 4, pp. 563-593. https://doi.org/10.1108/JAMR-10-2018-0093