Underlining Causes of Food Loss to Initiate Smart Agriculture Actions in the Milk Supply Chain: Production as a Mediator Effect

In 2050, the human population in the world is expected to reach 9.9 billion people. Due to the massive population, food production will be needed to satisfy more than average consumption in developed and developing countries. To manage the supply chain, food products require a technology approach to improve efficiency and reduce sources of wastage or loss. One of the foods that is affected by the loss is milk. A smart agriculture action is needed to ensure food security, and it can provide solutions and opportunities to face the challenges. The research examines the causes of food loss in the milk supply chain. It aims to identify the critical path to develop smart agriculture action based on the relationship between the causes of food loss, production, and the amount of food loss. The method used is quantitative, and a questionnaire was sent to survey 352 farmers in Malang Regency, Indonesia, which is initiating a smart city agenda. The analysis of those variables used structural equation modeling partial least squares (SEM-PLS). The result showed that production mediates between causes (cattle disease, weather, and collaboration) and the amount of food loss in quality and quantity. According to the model, it can be challenging for stakeholders to initiate smart agriculture action to prevent milk loss in the supply chain. The stakeholders can develop smart agriculture governance so that farmers can follow good farming practices by increasing technology adoption.

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Publication Details

Published
2024-09-04
DOI
https://doi.org/10.1109/iciss62896.2024.10751501
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Underlining Causes of Food Loss to Initiate Smart Agriculture Actions in the Milk Supply Chain: Production as a Mediator Effect

Wan Nurul Karimah Wan Ahmad, Fauzan Romadlon, Alina Shamsuddin
Food Waste Reduction and Sustainability
article

Underlining Causes of Food Loss to Initiate Smart Agriculture Actions in the Milk Supply Chain: Production as a Mediator Effect

Wan Nurul Karimah Wan Ahmad, Fauzan Romadlon, Alina Shamsuddin
article en

Abstract

In 2050, the human population in the world is expected to reach 9.9 billion people. Due to the massive population, food production will be needed to satisfy more than average consumption in developed and developing countries. To manage the supply chain, food products require a technology approach to improve efficiency and reduce sources of wastage or loss. One of the foods that is affected by the loss is milk. A smart agriculture action is needed to ensure food security, and it can provide solutions and opportunities to face the challenges. The research examines the causes of food loss in the milk supply chain. It aims to identify the critical path to develop smart agriculture action based on the relationship between the causes of food loss, production, and the amount of food loss. The method used is quantitative, and a questionnaire was sent to survey 352 farmers in Malang Regency, Indonesia, which is initiating a smart city agenda. The analysis of those variables used structural equation modeling partial least squares (SEM-PLS). The result showed that production mediates between causes (cattle disease, weather, and collaboration) and the amount of food loss in quality and quantity. According to the model, it can be challenging for stakeholders to initiate smart agriculture action to prevent milk loss in the supply chain. The stakeholders can develop smart agriculture governance so that farmers can follow good farming practices by increasing technology adoption.

Tun Hussein Onn University of Malaysia (MY)
Universiti Tun Hussein Onn Malaysia
Zero hunger
Openalex Percentile: Top 75%
Food Waste Reduction and Sustainability
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Underlining Causes of Food Loss to Initiate Smart Agriculture Actions in the Milk Supply Chain: Production as a Mediator Effect — Wan Nurul Karimah Wan Ahmad, Fauzan Romadlon, et al. · (2024) | TGRS Research Map | TGRS