Optimizing irrigation amount and fertilization rate of drip-fertigated spring maize in northwest China based on multi-level fuzzy comprehensive evaluation model

Xiao, Chao; Zou, Haiyang; Fan, Junliang; Zhang, Fucang; Li, Yi; Sun, Shikun; Pulatov, Alim

doi:10.1016/j.agwat.2021.107157

Cited by 47 publications

(20 citation statements)

References 69 publications

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“…were determined using a cubic spline. The approximation of the function ] was carried out using a fuzzy Mamdani model, which was implemented using the Fuzzy Logic Toolbox MATLAB 2015 extension [16,17].…”

Section: Results Of Practical Applicationmentioning

confidence: 99%

Intelligent decision support in the optimization of irrigation systems in agriculture

2023

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The issues of determining the optimal values of the regulatory parameters of irrigation systems engaged in the cultivation of agricultural crops are considered. Following the requirements of a market economy, the main emphasis is placed on taking into account two types of criteria: maximizing the yield of agricultural crops and minimizing monetary costs. The proposed method for solving the multi-criteria optimization problem is based on the combination of the minimax criterion and the medium-step convolution, which makes it possible to scalarize the vector optimality criterion with access to smooth optimization methods. Concerning the case of priority uncertainty according to particular optimality criteria, an intelligent algorithm is proposed based on the approximation of the preference function of the decision-maker by the fuzzy Mamdani model. The multi-criteria optimization of the irrigation system used for growing cotton results differ favorably from the average values. The one hectare yield in the republic- increased by 2%, monetary costs - reduced by 4.5%. It could be concluded that the developed methodology makes it possible to bypass the computational difficulties that arise when solving problems of multi-criteria optimization of irrigation systems engaged in the cultivation of agricultural crops and to obtain real results in conditions of certainty and uncertainty goals.

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Section: Results Of Practical Applicationmentioning

confidence: 99%

Intelligent decision support in the optimization of irrigation systems in agriculture

2023

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“…Optimizing water and N input at sensitive growth stages, and allowing an appropriate deficit in non‐sensitive periods can achieve the trade‐off between water and N saving and high yield (Du et al., 2015; Kang et al., 2017). Results from field experimental data suggest optimized irrigation and N fertilization rates (irrigation + N ) of 433 mm + 180 kgN/ha for field maize (Xiao et al., 2021), 298 mm + 175 kgN/ha for seed maize (Ran et al., 2017), and 323 mm + 150 kgN/ha for wheat (Wen et al., 2019) in the Hexi Corridor. These results consider crop yield, WP I , and NUE, which provides good guidance for actual field management and targets a trade‐off between saving water and N input and maintaining yield.…”

Section: Discussionmentioning

confidence: 99%

“…(2017), Xiao et al. (2021) and Li et al. (2018), and N concentration data was obtained from Chen et al.…”

Section: Methodsmentioning

confidence: 99%

“…N Y was calculated by multiplying crop aboveground biomass by crop N concentration, where aboveground biomass was obtained by dividing the simulated grain yields by the harvest index. Harvest index was obtained from Ran et al (2017), Xiao et al (2021) and Li et al (2018), and N concentration data was obtained from Chen et al (2022). N fer , N man , N min , N dep , and were obtained from different data sets, shown in Supporting Information S1 with the detailed information regarding APSIM, model performance, and the analysis methods.…”

Section: Optimization Framework Of Irrigation and Nitrogen Fertilizat...mentioning

confidence: 99%

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Adaptation Strategy Can Ensure Seed and Food Production With Improving Water and Nitrogen Use Efficiency Under Climate Change

et al. 2023

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Adaptation strategies can reduce the negative impacts of climate change on food security. As an important part of food security, more attention should be paid to seed security, as it determines the crop planting area and ultimately affects food production, especially in major seed production locations, such as the Hexi Corridor in China. This region is an important production base of grain (including field maize and wheat) and maize seed, but the shortage of water resources and low use efficiency of water and nitrogen (N) seriously constrain the sustainable development of agriculture. Formulating an adaptation strategy to balance the seed and food production and resource use efficiency is an important way to maintain regional as well as national food production. We established an optimization‐simulation framework, which consists of a novel crop production function and a grid‐based crop model, APSIM. This framework was used to optimize agricultural management and evaluate its performance considering the spatio‐temporal variability of climate and soil properties, actual crop water consumption and N uptake during each growth stage, and interactive sensitivity coefficients of water and N at different growth stages under climate change. We show that the proposed adaptation strategy could save 0.31 km³ of irrigation water and 22 thousand tonnes of N fertilizer, and increase seed and food production by 33 thousand tonnes, compared with traditional practices. Significant increases in irrigation water productivity and N use efficiency can be expected by using the adaptation supporting the sustainable development of agriculture.

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“…Therefore, adopting a reasonable and optimal combination of irrigation water and N fertilization is necessary for higher crop yield (H. Wang et al., 2018), and significantly increased straw and grain N accumulation (Yan et al., 2021). Similarly, the combined application of N fertilization with irrigation water of 80% evapotranspiration plays a vital role in maize growth, development, and significantly increased crop yield (Xiao et al., 2021). Moreover, supplementary irrigation combined with N fertilization could increase soil fertility, plant nutrient uptake, leaf area index (LAI), and chlorophyll content, which greatly increase crop photosynthesis and chlorophyll fluorescence, increasing biological and grain yield (G. Li et al., 2020; Shi et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Interactive effect of water and nitrogen fertilization improve chlorophyll fluorescence and yield of maize

et al. 2022

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Water scarcity and excessive N fertilization have a negative effect on maize (Zea mays L.) production. Low water and N fertilization are the major problem in sustainable agriculture by limiting crop growth and development. However, the combined effect of N fertilization and supplementary irrigation on chlorophyll fluorescence and maize yield is still not understood. The objective of the study was to signify the effect of supplementary irrigation and N fertilization on leaf area index (LAI), relative chlorophyll content (SPAD), maximum photosynthetic capacity (Fv/Fm), photochemical quenching coefficient (qP), and yield. The experiment was conducted in a split-plot design, with water management in main plot and N fertilization in subplot with three replications. Treatments included two water managements, that is, rainfed (natural rainfall) and irrigation water (70% field capacity). Five N fertilization rates were N0 (0 kg N ha −1 ), N150 (150 kg N ha −1 ), N200 (200 kg N ha −1 ), N250 (250 kg ha −1 ), and N300 (300 kg N ha −1 ). The LAI, SPAD, Fv/Fm, qP, and yield were significantly affected by water management, N rates, and their interaction (P < .05). The LAI, SPAD, Fv/Fm, qP, total dry matter accumulation, and yield under supplementary irrigation were significantly increased by 10. 99, 5.75, 6.57, 9.14, 15.64, and 14.58% than those under rainfed conditions, but the nonphotochemical quenching coefficient was significantly decreased by 22.82%. The 250 kg N ha −1 increased grain yield under irrigated conditions than that of other N treatments. The interaction between water management and N fertilization significantly and positively affected the SPAD, Fv/Fm, and grain yield in both years, but had no significant effect on LAI during 2021 and HI during 2020 and 2021. We concluded that N250 treatment with supplementary irrigation increased grain yield.

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Optimizing irrigation amount and fertilization rate of drip-fertigated spring maize in northwest China based on multi-level fuzzy comprehensive evaluation model

Cited by 47 publications

References 69 publications

Intelligent decision support in the optimization of irrigation systems in agriculture

Intelligent decision support in the optimization of irrigation systems in agriculture

Adaptation Strategy Can Ensure Seed and Food Production With Improving Water and Nitrogen Use Efficiency Under Climate Change

Interactive effect of water and nitrogen fertilization improve chlorophyll fluorescence and yield of maize

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