Application of Computer and Data Analysis in Crop Planning

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".

Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 3626

Special Issue Editors


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Guest Editor
Bond Business School, Bond University, Queensland, Australia
Interests: digital agriculture; crop planning; optimisation climate change; computational science

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Guest Editor
School of Information and Communication Technology, University of Tasmania, Hobart, Australia
Interests: evolutionary computation; computational agriculture; multiobjective optimisation; ecoacoustics

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Guest Editor
Institute for Integrated and Intelligent Systems, Griffith University, Queensland, Australia
Interests: computational science; multiobjective optimisation; smart agriculture; scientific visualisation

Special Issue Information

Dear Colleagues,

Traditional agricultural methods have been revolutionised by the integration of computer science and data analytic techniques to such a fundamental extent that they are now an integral part of this field. Yet, sustainable agriculture, under a rapidly changing climate, is still one of the greatest challenges that humanity faces. Growing populations, increased arid land, and the demands for freshwater have been, and continue to be, challenges that adversely affect global food security. Over the past decade, a range of optimisation tools have been successfully applied in this area to attempt to increase production while simultaneously using fewer resources. However, the treatment of climate change and the use of predictive models within optimisation processes have been insufficient. Therefore, there is a pressing need to make substantial progress in this regard.

This Special Issue aims to highlight the remarkable progress, challenges, and future prospects in using advanced computational techniques and data analysis for enhancing crop planning strategies. This Special Issue particularly welcomes original submissions that use climate change modelling to help predict the type of cropping that will be sustainable in the future. Submissions that discuss agricultural, economic, security, and technological factors that surround the nexus between climate change and sustainable agriculture are also sought.

Prof. Dr. Marcus Randall
Dr. James Montgomery
Dr. Andrew Lewis
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • crop planning
  • climate change
  • water management
  • optimisation, evolutionary algorithms
  • computational agriculture

Published Papers (2 papers)

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Research

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17 pages, 5054 KiB  
Article
Improving Environmental Water Supply in Wetlands through Optimal Cropping Patterns
by Mahdi Sedighkia and Bithin Datta
Agriculture 2023, 13(10), 1942; https://doi.org/10.3390/agriculture13101942 - 05 Oct 2023
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Abstract
This study improves the environmental water supply in a wetland using a novel framework in which the environmental impacts due to irrigation supply and the economic losses for agriculture are minimized through the proposal of an optimal cropping pattern that changes the total [...] Read more.
This study improves the environmental water supply in a wetland using a novel framework in which the environmental impacts due to irrigation supply and the economic losses for agriculture are minimized through the proposal of an optimal cropping pattern that changes the total cropping area and cultivated area of each crop. The ecological degradation functions for rivers and wetlands were developed using a fuzzy approach and data-driven model. The net farming revenue was considered as the economic index to maximize benefits. The root mean square error (RMSE) and the Nash–Sutcliffe model efficiency coefficient (NSE) were applied to evaluate ecological models. According to the results, the optimal cropping pattern simultaneously minimizes environmental impacts due to irrigation supply and maximizes farmers’ benefits. The optimal cropping pattern provides more than 50% of the ideal net revenue on the catchment scale, which means that ecological degradations due to reductions in inflow in rivers and wetlands, as well as farmers’ revenue losses, are minimized simultaneously. Furthermore, the results indicate that cropping patterns should be dynamic, which means that changing the cropping pattern annually based on the available water is essential to mitigating ecological impacts. This study demonstrates that the linking of cropping pattern optimization and environmental flow simulation in freshwater bodies should be considered in land-use policies due to the impact of cropping patterns on environmental degradation in wetland catchments. Full article
(This article belongs to the Special Issue Application of Computer and Data Analysis in Crop Planning)
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Review

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17 pages, 1247 KiB  
Review
Factors Affecting Crop Prices in the Context of Climate Change—A Review
by Huong Nguyen, Marcus Randall and Andrew Lewis
Agriculture 2024, 14(1), 135; https://doi.org/10.3390/agriculture14010135 - 16 Jan 2024
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Abstract
Food security has become a concerning issue because of global climate change and increasing populations. Agricultural production is considered one of the key factors that affects food security. The changing climate has negatively affected agricultural production, which accelerates food shortages. The supply of [...] Read more.
Food security has become a concerning issue because of global climate change and increasing populations. Agricultural production is considered one of the key factors that affects food security. The changing climate has negatively affected agricultural production, which accelerates food shortages. The supply of agricultural commodities can be heavily influenced by climate change, which leads to climate-induced agricultural productivity shocks impacting crop prices. This paper systematically reviews publications over the past ten years on the factors affecting the prices of a wide range of crops across the globe. This review presents a critical view of these factors in the context of climate change. This paper applies a systematic approach by determining the appropriate works to review with defined inclusion criteria. From this, groups of key factors affecting crop prices are found. This study finds evidence that crop prices have been both positively and negatively affected by a range of factors such as elements of climate change, biofuel, and economic factors. However, the general trend is towards increasing crop prices due to deceasing yields over time. This is the first systematic literature review which provides a comprehensive view of the factors affecting the prices of crops across the world under climate change. Full article
(This article belongs to the Special Issue Application of Computer and Data Analysis in Crop Planning)
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