环境因素影响马铃薯块茎产量对生长季降水量的响应性

Funian Zhao , Qiang Zhang , Jun Lei , Heling Wang , Kai Zhang , Yue Qi
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引用次数: 0

摘要

了解环境因素如何影响作物产量对生长季降水量(GSP)的响应,可以降低产量波动的风险,确保作物的稳定生产。本研究涉及中国西北气候过渡带三个地点的雨水灌溉马铃薯种植。我们采用逐步线性回归和机器学习技术,找出了影响马铃薯块茎产量的关键环境因素以及产量与降水量的关系。经测定,马铃薯水分限制产量潜力关系的斜率为 172.1 kg ha-1 mm-1,截距为 121.2 mm。马铃薯块茎产量随着 GSP 的增加而呈上升趋势,但一旦降水量超过 400 毫米,产量就会下降。然而,仅 GSP 就能解释高达 30% 的马铃薯块茎产量变化。播种时的土壤湿度、块茎匍匐茎萌发期和膨大期的最高温度、成熟期的昼夜温度波动以及生长季节的过量降水事件等因素对马铃薯块茎产量有显著影响,因此也影响了产量与 GSP 之间的关系。相反,气候因素占马铃薯块茎产量变化的 63% 以上,多元线性回归模型的结果最好。当根据 GSP 的数量和分布、最高温度和辐射水平将产量与降水量的关系分为两组时,这一点尤为明显。这一分析表明,在降水量少时防止不必要的水分蒸发,在降水量多时改善排水系统,以及在最佳日期种植马铃薯,都能提高马铃薯产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Environmental factors influence the responsiveness of potato tuber yield to growing season precipitation

Understanding how environmental factors influence the responsiveness of crop yield to growing season precipitation (GSP) can reduce the risk of yield fluctuations, ensuring stable crop production. This study involved the cultivation of rainfed potatoes at three locations within the climatic transition zone of Northwest China. We employed stepwise linear regression and machine learning techniques to pinpoint the key environmental factors influencing potato tuber yield and the yield-precipitation relationship. The slope of the water-limited yield potential relationship for potatoes was determined to be 172.1 ​kg ​ha−1 ​mm−1, with an intercept at 121.2 ​mm. The potato tuber yield exhibited an upward trend with increasing GSP but declined once the precipitation exceeded 400 ​mm. However, GSP alone explained up to 30% of the variability in potato tuber yield. Factors such as soil moisture at planting, maximum temperatures during the tuber stolon initiation and bulking stages, diurnal temperature fluctuations at maturity, and excessive precipitation events during the growing season significantly influenced potato tuber yield, and consequently, the relationship between yield and GSP. Conversely, climatic factors accounted for more than 63% of the variation in potato tuber yield, with the multiple linear regression model yielding the best results. This was especially evident when the yield-precipitation relationship was categorized into two groups based on the amount and distribution of GSP, maximum temperature, and radiation levels. This analysis suggested that preventing unnecessary water evaporation when precipitation is low, improving drainage when precipitation is high, and planting potato on an optimal date can advance potato production.

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