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Combining field-level data and remote sensing to understand impact of management practices on producer yields
Field Crops Research ( IF 5.6 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.fcr.2020.107932
Juan I. Rattalino Edreira , Spyridon Mourtzinis , George Azzari , José F. Andrade , Shawn P. Conley , James E. Specht , Patricio Grassini

Abstract Producer field-level data have been used in recent studies to identify suites of management practices that consistently increase yield for a given climate-soil environment. However, the physiological drivers underlying the empirical associations between yield and management practices derived from these studies have remained mostly speculative, particularly in terms of resource capture and conversion into economic yield. We followed an approach consisting of a large producer database, satellite imagery, and crop modeling to assess which key physiological parameters best explain on-farm yield response to producer-chosen management practices across different climate-soil production environments. Survey data on yield and management practices were collected from 5291 soybean fields sown across the US North Central region during 2014-2016. Producer data were grouped into 10 technology extrapolation domains (TEDs) to account for variation in soil, climate, and water regime across producer fields. Simulated phenology and satellite imagery were used to estimate incident (IPAR) and absorbed (APAR) photosynthetically active radiation during the entire crop season and also during the time-span beginning with pod setting and ending with physiological maturity. In each TED, seed yield was increased by early sowing (+13 to +39 kg ha-1d-1), which was physiologically driven by increases in the duration of both crop cycle and critical period, and by a higher APAR. In-season application of foliar fungicide and/or insecticide also resulted in significant yield increase (+0.35 Mg ha−1, p

中文翻译:

结合田间数据和遥感,了解管理实践对生产者产量的影响

摘要 在最近的研究中,生产者田间数据已被用于确定在给定的气候土壤环境中持续增加产量的管理实践套件。然而,这些研究得出的产量和管理实践之间经验关联背后的生理驱动因素仍然主要是推测性的,特别是在资源捕获和转化为经济产量方面。我们采用了一种由大型生产者数据库、卫星图像和作物建模组成的方法,以评估哪些关键生理参数最能解释农场产量对不同气候-土壤生产环境中生产者选择的管理实践的反应。从 2014-2016 年美国中北部地区播种的 5291 个大豆田中收集了有关产量和管理实践的调查数据。生产者数据被分为 10 个技术外推域 (TED),以解释生产者田间土壤、气候和水情的变化。模拟物候和卫星图像用于估计整个作物季节期间以及从豆荚设置开始到生理成熟结束的时间跨度内的入射 (IPAR) 和吸收 (APAR) 光合有效辐射。在每个 TED 中,种子产量因早播(+13 至 +39 kg ha-1d-1)而增加,这在生理上是由作物周期和关键期持续时间的增加以及更高的 APAR 驱动的。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 和跨生产者油田的水情。模拟物候和卫星图像用于估计整个作物季节期间以及从豆荚设置开始到生理成熟结束的时间跨度期间的入射 (IPAR) 和吸收 (APAR) 光合有效辐射。在每个 TED 中,种子产量因早播(+13 至 +39 kg ha-1d-1)而增加,这在生理上是由作物周期和关键期持续时间的增加以及更高的 APAR 驱动的。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 和跨生产油田的水情。模拟物候和卫星图像用于估计整个作物季节期间以及从豆荚设置开始到生理成熟结束的时间跨度期间的入射 (IPAR) 和吸收 (APAR) 光合有效辐射。在每个 TED 中,种子产量因早播(+13 至 +39 kg ha-1d-1)而增加,这在生理上是由作物周期和关键期持续时间的增加以及更高的 APAR 驱动的。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 模拟物候和卫星图像用于估计整个作物季节期间以及从豆荚设置开始到生理成熟结束的时间跨度期间的入射 (IPAR) 和吸收 (APAR) 光合有效辐射。在每个 TED 中,种子产量因早播(+13 至 +39 kg ha-1d-1)而增加,这在生理上是由作物周期和关键期持续时间的增加以及更高的 APAR 驱动的。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 模拟物候和卫星图像用于估计整个作物季节期间以及从豆荚设置开始到生理成熟结束的时间跨度期间的入射 (IPAR) 和吸收 (APAR) 光合有效辐射。在每个 TED 中,种子产量因早播(+13 至 +39 kg ha-1d-1)而增加,这在生理上是由作物周期和关键期持续时间的增加以及更高的 APAR 驱动的。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 和更高的 APAR。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p 和更高的 APAR。叶面杀菌剂和/或杀虫剂的季节性施用也导致显着的产量增加(+0.35 Mg ha−1,p
更新日期:2020-10-01
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