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Spatiotemporal normalized ratio methodology to evaluate the impact of field-scale variable rate application
Precision Agriculture ( IF 5.4 ) Pub Date : 2022-03-09 , DOI: 10.1007/s11119-022-09877-4
L. Katz 1, 2, 3, 4 , I. Bahat 1, 5 , V. Alchanatis 1 , Y. Cohen 1 , M. I. Litaor 3, 6 , A. Naor 3 , A. Ben-Gal 4 , M. Peres 7 , Y. Netzer 8, 9 , A. Peeters 10
Affiliation  

Wide assimilation of precision agriculture among farmers is currently dependent on the ability to demonstrate its efficiency at the field-scale. Yet, most experiments that compare variable-rate vs uniform application (VRA and UA) are performed in strips, concentrated in a small portion of the field with limited extrapolation to the field scale. A spatiotemporal normalized ratio (STNR) methodology is proposed to evaluate the impact of VRA compared with UA for on-farm trials at the field scale. It incorporates a base year in which the whole plot is managed with UA and consecutive years in which half of the plot is managed with UA and the other half is managed with VRA. Additionally, a novel normalized relative comparison index (NRCI) is presented where the ratios of VRA/UA sub-plots are compared between a base year and a consecutive year, for any measured parameter. The NRCI determines the impact of VRA on variability using statistical measures of dispersion (variability measures) and on performance with statistical measures of central tendency (performance measures). Variability measures with NRCI values lower or higher than 1 indicate VRA management decreased or increased variability. Performance measures with NRCI lower or higher than 1 indicate subplot impairment or improvement, respectively due to VRA management. The methodology was demonstrated on a commercial drip irrigated peach orchard and a wine grape vineyard. NRCI results showed that VRA drip irrigation reduced water status in-field variability but did not necessarily increase yield. The benefits and limitations of the proposed design are discussed.



中文翻译:

时空归一化比率方法评估现场规模可变利率应用的影响

目前,农民对精准农业的广泛认同取决于在田间规模展示其效率的能力。然而,大多数比较可变速率与均匀应用(VRA 和 UA)的实验都是在条带中进行的,集中在一小部分领域,对领域规模的外推有限。提出了一种时空归一化比率( STNR ) 方法来评估 VRA 与 UA 相比对田间规模的农场试验的影响。它包括一个基准年,其中整个地块由 UA 管理,连续年一半地块由 UA 管理,另一半由 VRA 管理。此外,一种新的归一化相对比较指数NRCI) 用于比较任何测量参数的基准年和连续年之间的 VRA/UA 子图的比率。NRCI 使用离散度的统计测量(变异性测量)确定 VRA 对变异性的影响,以及使用集中趋势的统计测量(绩效测量)对性能的影响。)。NRCI 值低于或高于 1 的变异性测量表明 VRA 管理降低或增加了变异性。NRCI 低于或高于 1 的绩效指标分别表示由于 VRA 管理而导致的子区受损或改善。该方法在一个商业滴灌桃园和一个酿酒葡萄园进行了演示。NRCI 结果表明,VRA 滴灌降低了田间水分状况的变异性,但不一定会增加产量。讨论了建议设计的优点和局限性。

更新日期:2022-03-09
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