| 邓庆玲,崔宁博,陈飞,李小孟,胡笑涛,黎秋刚,官民,李明红,曾云,王燕.滴灌脐橙产量和品质的水肥生产函数研究[J].干旱地区农业研究,2023,(5):80~88 |
| 滴灌脐橙产量和品质的水肥生产函数研究 |
| Study on water and fertilizer production function for yield and quality of navel orange under drip irrigation |
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| DOI：10.7606/j.issn.1000-7601.2023.05.09 |
| 中文关键词: 脐橙 水肥生产函数 滴灌 产量 品质 |
| 英文关键词:navel orange water and fertilizer production function drip irrigation yield quality |
| 基金项目:（四川大学-泸州）科技创新研发项目（2019CDLZ-10） |
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| 中文摘要: |
| 以‘纽荷尔’脐橙为试材，在2020年4月—2021年12月抽梢开花期（I）、幼果期（II）、果实膨大期（III）和果实成熟期（IV）分别设置高水和低水2个亏水处理（灌水量分别为对照处理的70%和55%），高肥、中肥和低肥3个施肥处理（施肥量分别为对照处理的80%、60%和40%），以正常水肥管理为对照（CK）。CK处理I~IV期灌水量分别为136.43、204.65、272.86、136.43 m3·hm-2，施肥量分别为380.00、645.00、1550.00、400.00 kg·hm-2。基于W×F-Jensen/Minhas/Rao模型模拟脐橙产量和品质与不同生育期耗水耗肥量的关系，进而评价模型预测性能与敏感性。研究表明：脐橙产量、单果质量和可溶性糖均对III期水、肥亏缺最敏感；维生素C对Ⅲ期水分亏缺最敏感，对IV期肥料亏缺最敏感；可滴定酸对Ⅱ期水分亏缺最敏感，对IV期肥料变化最敏感。W×F-Jensen/Minhas/Rao模型均能较好地模拟脐橙产量（决定系数R2=0.76~0.90，均方根误差RMSE=0.030~0.045，平均绝对误差AAE=0.023~0.036，建模效率EF=0.74~0.88，一致性指数dIA=0.91~0.96），其中W×F-Minhas模型表现最佳；W×F-Jensen/Minhas/Rao模型均能很好地模拟脐橙果实含水量（R2=0.87~0.94，RMSE=0.010~0.011，AAE=0.008~0.009，EF=0.85~0.88，dIA=0.96~0.97），同时可较好地模拟单果质量和可滴定酸含量（R2=0.54~0.65，RMSE=0.026~0.050，AAE=0.023~0.040，EF=0.42~0.65，dIA=0.86~0.92）。W×F-Minhas和W×F-Rao模型分别在模拟可溶性糖和维生素C时表现最佳，R2分别为0.46和0.51。综上所述，推荐使用W×F-Minhas模型模拟脐橙产量和果实品质，以实现脐橙节水提质高效发展。 |
| 英文摘要: |
| ‘Newhall’ navel orange was used as the test material. Two water deficit levels (high and low water treatment, noted as HW and LW, and the perfusion volume was 70% and 55% of CK, respectively) and three fertilization levels (high, medium and low fertilizer, noted as HF, MF and LF, were applied at 80%, 60% and 40% of CK, respectively) were set at the shoot flowering stage (I), young fruit stage (II), fruit expansion stage (III) and fruit maturity stage (IV). The fertilizer application rates were 80%, 60% and 40% of CK, respectively with control treatment (CK). The irrigation amounts of CK treatment were 136.43, 204.65, 272.86 m3·hm-2 and 136.43 m3·hm-2 at stage I-IV, respectively, and the fertilizer amounts were 380.00, 645.00, 1550.00 kg·hm-2 and 400.00 kg·hm-2, respectively. W×F-Jensen, W×F-Minhas and W×F-Rao models were used to simulate the relationship between yield and quality of navel orange and water and fertilizer consumption at different growth stages, and to evaluate the prediction performance of the models. It was found that navel orange yield, fruit mass and soluble sugar were most sensitive to water and fertilizer deficit in stage III. Vitamin C was most sensitive to water deficit in stage III and fertilizer change in stage IV. Titratable acid was most sensitive to water deficit in stage I and stage IV, and most sensitive to fertilizer change in stage IV. W×F-Jensen, W×F-Minhas and W×F-Rao models established in this study simulated navel orange yield well, with R2=0.76~0.90, RMSE=0.030~0.045, AAE=0.023~0.036, EF=0.74~0.88, dIA=0.91~0.96, among which W×F-Minhas model was the best. W×F-Jensen, W×F-Minhas and W×F-Rao models could well simulate the water content of navel orange fruit, showing R2=0.87~0.94, RMSE=0.010~0.011, AAE=0.008~0.009, EF=0.85~0.88, dIA=0.96~0.97, which better simulated the fruit weight and titratable acid content. R2=0.54~0.65, RMSE=0.026~0.050, AAE=0.023~0.040, EF=0.42~0.65, dIA=0.86~0.92. W×F-Minhas和W×F-Rao models had the best performance when simulating soluble sugar and vitamin C, with R2 of 0.46 and 0.51, respectively. In conclusion, W×F-Minhas model was recommended to simulate navel orange yield and fruit quality to realize the efficient development of navel orange with water saving and quality improvement. |
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