Modeling Tomato Yield and Quality Responses to Water and Nitrogen Deficits with a Modified Crop Water Production Function
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Published:2024-08-24
Issue:9
Volume:10
Page:898
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ISSN:2311-7524
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Container-title:Horticulturae
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language:en
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Short-container-title:Horticulturae
Author:
Jiang Xuelian1, Fan Mengying2ORCID, Wang Tianci3, Gong Shuai4, Hao Wenya4, Ye Yingxin4, Zhao Yueling1, Cui Ningbo2, Zhao Huan5, Zhao Lu2
Affiliation:
1. Weifang Municipal Key Laboratory of Agricultural Planting Quantization and Application, Weifang University, Weifang 261061, China 2. State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China 3. Anne Burnett Marion School of Medicine, Texas Christian University, Fort Worth, TX 76107, USA 4. Sinochem Agriculture Holdings Co. Ltd., Beijing 100032, China 5. Tuancheng Lake Management Office of Beijing South to North Water Diversion Project, Beijing 100195, China
Abstract
Increasingly severe crises, such as climate change, water scarcity and environmental pollution, pose significant challenges to global food security and sustainable agricultural development. For efficient and sustainable tomato cultivation management under resource constraints, quantitatively describing the relationship between yield-quality harvest and water-nitrogen application is practically beneficial. Two successive greenhouse experiments with three irrigation levels (1/3 FI, 2/3 FI, and full irrigation (FI)) and four nitrogen fertilizer treatments (0 FN, 1/3 FN, 2/3 FN, and full nitrogen (FN)) were conducted on tomatoes during the whole phenological stage. The tomato evapotranspiration and nitrogen application amount, yield, comprehensive quality, solid–acid ratio, and lycopene content were measured. Based on crop water production functions, three equation forms of water-nitrogen production functions containing 20 models were established and evaluated to predict tomato harvest parameters. The results show that water increased tomato yield while decreasing fruit quality, and the effect of nitrogen was primarily contrary. Water most significantly impacted tomato formation, and the interaction of water and nitrogen changed among different harvest parameters. Tomato yield and quality formation was more sensitive to water and nitrogen at the flowering and fruit maturation stages. Model Singh-2 outweighed other models for yield estimates, with an R2 of 0.71 and an RMSE of 0.11. Singh-Log, Singh-sigmoid and Rao-Root models were effective models for comprehensive quality, solid–acid ratio, and lycopene content prediction, with an R2 of 0.41, 0.62, and 0.42, and an RMSE of 0.33, 0.50, and 0.16, respectively. Finally, models in the form of f(ETi)·f(N) were ideal for tomato harvest prevision and are recommended for water and nitrogen management in tomato cultivation.
Funder
National Natural Science Foundation of China Shandong Provincial Natural Science Fund of China Science and Technology Development Plan of Weifang City Cooperative Research Project of Sichuan Water Resources Department
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