Improved Evaluation of Cultivation Performance for Maize Based on Group Decision Method of Data Envelopment Analysis Model

Wei Huang; Han Li; Kaifeng Chen; Xiaohua Teng; Yumeng Cui; Helong Yu; Chunguang Bi; Meng Huang; You Tang

doi:10.3390/app13010521

Applied Sciences (Dec 2022)

Improved Evaluation of Cultivation Performance for Maize Based on Group Decision Method of Data Envelopment Analysis Model

Wei Huang,
Han Li,
Kaifeng Chen,
Xiaohua Teng,
Yumeng Cui,
Helong Yu,
Chunguang Bi,
Meng Huang,
You Tang

Affiliations

Wei Huang: Economic and Management School, Jilin Agricultural Science and Technology University, Jilin 132101, China
Han Li: School of Science, Northeast Electric Power University, Jilin 132012, China
Kaifeng Chen: Electrical and Information Engineering College, Jilin Agricultural Science and Technology University, Jilin 132101, China
Xiaohua Teng: Electrical and Information Engineering College, Jilin Agricultural Science and Technology University, Jilin 132101, China
Yumeng Cui: School of Science, Northeast Electric Power University, Jilin 132012, China
Helong Yu: College of Information Technology, Jilin Agricultural University, Changchun 132101, China
Chunguang Bi: College of Information Technology, Jilin Agricultural University, Changchun 132101, China
Meng Huang: Electrical and Information Engineering College, Jilin Agricultural Science and Technology University, Jilin 132101, China
You Tang: Electrical and Information Engineering College, Jilin Agricultural Science and Technology University, Jilin 132101, China

DOI: https://doi.org/10.3390/app13010521
Journal volume & issue: Vol. 13, no. 1
p. 521

Abstract

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Maize cultivation performance, including the efficiency of the input and output of maize, which reflect the allocation and utilization of resources in the process of maize cultivation, is crucial for evaluating and improving maize cultivation. This paper adopts the method of quadratic regression orthogonal rotation combination experimental design to explore the effects of four main cultivation measures (planting density, nitrogen fertilizer, phosphorus fertilizer and potassium fertilizer) on maize yield at five levels (−2, −1, 0, 1; 2). The CCR (A. Charnes, W. Cooper and E. Rhodes) model, which is the basic model of data envelopment analysis (DEA), was used to evaluate the 36 groups of cultivation measures. The results show that 9 groups are CCR-effective cultivation measures, but the performance of these cultivation measures cannot be further evaluated. To improve the evaluation of cultivation performance, a novel method termed as the group decision method of DEA (GDM-DEA) is proposed to detect the improvement of evaluation performance and is tested using the measurements of maize cultivation. The results suggest that the GDM-DEA method can classify and sort the performance of all the cultivation measures, which is more sensitive and accurate than the CCR method. For the effective cultivation measures that meet the requirements of GDM-DEA, the optimal cultivation measures could be determined according to the ranking of yield. This method determined the most effective cultivation measure. Further independent validation showed that the final optimal cultivation measures fall in the range of the expected cultivation measures. The GDM-DEA model is capable of more effectively evaluating cultivation performance.

Published in Applied Sciences

ISSN: 2076-3417 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Engineering (General). Civil engineering (General); Science: Biology (General); Science: Physics; Science: Chemistry
Website: http://www.mdpi.com/journal/applsci

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