Crop Production and Water Productivity Simultaneously Optimization of Soybean Plant Using Two Meta-Heuristic Algorithms

IF 0.9 4区农林科学 Q3 AGRONOMY

Romanian Agricultural Research Pub Date : 2022-01-01 DOI:10.59665/rar3929

H. Babazadeh, M. Tabrizi, G. Hoogenboom

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引用次数: 1

Abstract

The maximum crop production achievement in arid and semi-arid regions is the main issue that requires the optimum use of different variables of crop and water. Therefore, this research has been carried out for simultaneous optimization of water productivity (WP) and for high crop productivity under deficit irrigation management conditions. An original data series has been used for this research from an experimental design that was conducted in the form of randomized complete blocks design with three replications and seven irrigation treatments of different growth stages during two conductive crop seasons 2010 and 2011. The genetic algorithm has been applied as a multi-objective (MOGA) and under two scenarios of the priority of objective functions. Also, in order to investigate the application of the simulated annealing algorithm (SA), in a combined optimizing of two objective functions of soybean WP and plant production using weight summation method, it has been converted to a single objective one. The results have shown that under the first scenario conditions, the optimum grain yield and optimum WP are 3,827 and 3,953 kg ha-1 and 0.53 and 0.58 kg m-3 ha-1 in 2010 and 2011, respectively. The results in the combined optimization under the second scenario conditions show the amounts of optimum crop production and WP are 3,838.1 and 3,902.7 kg ha-1 and 1.12 and 0.75 kg m-3 ha-1 in the two seasons, respectively. Comparison of the MOGA and SA results has indicated that MOGA has a better capability in simultaneous optimization of the two objective functions. Maximum crop production was 4446 kg ha-1 for consuming 664.9 mm irrigation water. Also, the maximum WP was 0.82 kg m-3 ha-1 for consuming 375.8 mm irrigation water. Therefore, the dual-objective genetic optimization method can well optimize both objective functions and achieve the desired results in optimal grain yield and WP under constrained water resources.

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基于两种元启发式算法的大豆作物产量和水分生产力同步优化

在干旱和半干旱地区，作物产量的最大化是主要问题，需要作物和水的不同变量的最佳利用。因此，本研究旨在亏缺灌溉条件下同时优化水分生产力(WP)和提高作物生产力。本研究使用的原始数据序列来自一项试验设计，该试验设计以随机完全区设计的形式进行，在2010年和2011年两个导电性作物季节进行了3个重复和7个不同生长阶段的灌溉处理。将遗传算法应用于多目标(MOGA)和目标函数优先级两种情况下。此外，为了研究模拟退火算法(SA)在大豆WP和植物产量两个目标函数的权重求和联合优化中的应用，将其转化为单目标优化。结果表明:在第一种方案条件下，2010年和2011年的最优产量和最优WP分别为3827和3953 kg hm -1和0.53和0.58 kg m-3 hm -1;第二种情景条件下的组合优化结果表明，两季最优作物产量和WP分别为3838.1和3902.7 kg hm -1, 1.12和0.75 kg m-3 hm -1。将MOGA算法与SA算法的结果进行比较，结果表明MOGA算法具有更好的同时优化两个目标函数的能力。灌溉用水量为664.9 mm，最高产量为4446 kg ha-1。用水量为375.8 mm时，最大WP值为0.82 kg m-3 ha-1。因此，双目标遗传优化方法可以很好地优化两个目标函数，并在水资源受限条件下获得最优粮食产量和最优WP。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Romanian Agricultural Research 农林科学-农艺学

CiteScore

0.90

自引率

28.60%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal ROMANIAN AGRICULTURAL RESEARCH is an “open access” one, which publishes original articles, short communications, presenting new scientific results – theoretical, experimental and technical – on plant breeding and genetics, physiology, biotechnology, mineral nutrition and plant protection, in field crops. Reviews on up-to date subjects and recent research, preferably from Eastern Europe, may also be published.