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基于改进TOPSIS法的黄土高原涌根灌溉山地苹果产量、品质及水氮利用效率综合评价

Comprehensive Evaluation on the Yield, Quality, and Water-Nitrogen Use Efficiency of Mountain Apple Under Surge-Root Irrigation in the Loess Plateau Based on the Improved TOPSIS Method.

作者信息

Hao Kun, Fei Liangjun, Liu Lihua, Jie Feilong, Peng Youliang, Liu Xiaogang, Khan Sher Aslam, Wang Dong, Wang Xiukang

机构信息

State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, China.

Institute of Water Resources and Hydroelectric Engineering, Xi'an University of Technology, Xi'an, China.

出版信息

Front Plant Sci. 2022 Apr 5;13:853546. doi: 10.3389/fpls.2022.853546. eCollection 2022.

DOI:10.3389/fpls.2022.853546
PMID:35449894
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9018000/
Abstract

The purpose of this study was to know the controlling effects of water and nitrogen coupling on the yield, quality, and water-nitrogen utilization effectiveness of mountain apples under surge-root irrigation in the Loess Plateau. In order to optimize the water and nitrogen irrigation systems of superior quality and high yield, 7 years was selected for the mountain apple test material. The trial was designed with four tiers of irrigation, i.e., full irrigation (FI: 85-100% , where is the field capacity), light deficit irrigation (DI: 70-85% ), moderate deficit irrigation (DI: 55-70% ), and severe deficit irrigation (DI: 40-55% ) and three tiers of nitrogen, i.e., high nitrogen (N: 600 kg ha), medium nitrogen (N: 400 kg ha), and low nitrogen (N: 200 kg ha). The subjective weight attained by the analytic hierarchy methods and the objective weight achieved by the enhanced coefficient of variation method were examined to find the comprehensive weight based on the notion of game hypothesis. Then, the weighted technique for order of preference by similarity to the ideal solution (TOPSIS) process was utilized to comprehensively assess the yield, quality, and water-nitrogen use efficiency of the apples, and a binary quadratic regression model was created between the comprehensive evaluation index and water-nitrogen inputs. The results showed that the effects of irrigation and nitrogen levels on the fruit yield, irrigation water use efficiency (IWUE), total water use efficiency (TWUE), nitrogen partial factor productivity (NPFP), and quality of mountain apples were significant ( < 0.05). The apple yield and TWUE first improved and then diminished with an escalating quantity of water-nitrogen inputs, the IWUE diminished with a boost in the irrigation quantity, the NPFP dwindled when the nitrogen amount was increased. The best water and nitrogen inputs for apple yield, quality, or water-nitrogen use efficiency were dissimilar. The best comprehensive evaluation index was DIN treatment, and the worst comprehensive evaluation index was DIN treatment, based on the TOPSIS system. The interval of irrigation and nitrogen attained from the mathematic model ranged in 95-115 mm and 470-575 kg ha, respectively. The outcome of this study may perhaps offer a theoretical basis for the scientific research of surge-root irrigation and the managing of mountain apple tree irrigation and fertilization in the Loess Plateau, China.

摘要

本研究旨在了解黄土高原涌根灌溉条件下水分与氮素耦合对山地苹果产量、品质及水氮利用效率的调控效应。为优化优质高产的水氮灌溉制度,选取7年生山地苹果作为试验材料。试验设计了4个灌溉水平,即充分灌溉(FI:85 - 100%田间持水量,其中田间持水量用θ表示)、轻度亏缺灌溉(DI:70 - 85%θ)、中度亏缺灌溉(DI:55 - 70%θ)和重度亏缺灌溉(DI:40 - 55%θ),以及3个施氮水平,即高氮(N:600 kg/ha)、中氮(N:400 kg/ha)和低氮(N:200 kg/ha)。基于博弈假说的概念,研究了层次分析法获得的主观权重和变异系数法得到的客观权重,以确定综合权重。然后,利用逼近理想解排序法(TOPSIS)对苹果的产量、品质和水氮利用效率进行综合评价,并建立了综合评价指标与水氮投入量之间的二元二次回归模型。结果表明,灌溉和施氮水平对山地苹果的果实产量、灌溉水利用效率(IWUE)、总水分利用效率(TWUE)、氮偏生产力(NPFP)和品质的影响显著(P < 0.05)。苹果产量和TWUE随水氮投入量的增加先升高后降低,IWUE随灌溉量的增加而降低,NPFP随施氮量的增加而减小。苹果产量、品质或水氮利用效率的最佳水氮投入量各不相同。基于TOPSIS系统,最佳综合评价指标为DIN处理,最差综合评价指标为DIN处理。数学模型得出的灌溉量和施氮量区间分别为95 - 115 mm和470 - 575 kg/ha。本研究结果可能为黄土高原涌根灌溉的科学研究以及山地苹果树灌溉施肥管理提供理论依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/5eed2e851fa7/fpls-13-853546-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/b10c8ade3985/fpls-13-853546-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/5eed2e851fa7/fpls-13-853546-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/b10c8ade3985/fpls-13-853546-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/53b66b3d37f7/fpls-13-853546-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/4f080b66d6f5/fpls-13-853546-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/9529a562ccaf/fpls-13-853546-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a362/9018000/5eed2e851fa7/fpls-13-853546-g006.jpg

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