Context

Untangling the most relevant factors underpinning sorghum (Sorghum bicolor L.) yields is critical to identify, within the target environments, the best management practices to increase production and reverse the negative trend in planted area across the United States (US).

Objective

This study aims to provide new insights of the effects of environment (E) and management (M) on sorghum yields. Specific goals for this study were linked to i) describe the relevance of E factors (mainly heat and drought), and ii) explore the effect of M component on yield variability across different US sorghum producing regions.

Methods

The US National Sorghum Producer (NSP) Yield Contest self-reported farmer-based dataset, spanning 24 states from 2013 to 2017 period (n = 782) was split in yield terciles. Three different approaches were employed to independently explore each yield tercile: i) crop modeling simulation to quantify the impact of heat and drought on yield, ii) conditional inference tree to rank the most relevant management practices, and lastly, iii) fuzzy C means spatial clustering to identify critical management practices linked to geographical yield clusters across crop regions.

Results

The E component accounted for nearly half of the sorghum yield variation for the low-yielding group (< 7.6 Mg ha^-1), while the M factor (mainly planting date and irrigation) played a key role for the high-yielding group (> 9.7 Mg ha^-1). Geographically-relevant yield clusters identified three main regions, i) east (with earlier planting dates, early May, and high N fertilization rates), ii) west (with irrigation as the main factor) within the continental area, and iii) coastal zone (with planting dates before April 1, southeast Texas). For the low-yielding group, row spacing, and plant density were key variables accounting for yield variation.

Conclusions

These outcomes provide foundational insights on the major E and M factors limiting attainable yields within farmers targeting high yields in the main US sorghum producing regions.

中文翻译：

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高粱生产者产量竞赛：主要管理和环境驱动因素的综合分析

语境

理清支撑高粱 ( Sorghum bicolor L.) 产量的最相关因素对于在目标环境中确定最佳管理实践以提高产量和扭转美国 (US) 种植面积的负面趋势至关重要。

客观的

本研究旨在提供有关环境 (E) 和管理 (M) 对高粱产量影响的新见解。本研究的具体目标与 i) 描述 E 因素（主要是高温和干旱）的相关性，以及 ii) 探讨 M 成分对美国不同高粱产区产量变异性的影响。

方法

美国国家高粱生产者 (NSP) 产量竞赛自我报告的基于农民的数据集，跨越 24 个州，从 2013 年到 2017 年期间 (n = 782) 按产量三分位划分。采用三种不同的方法独立探索每个产量三分位数：i) 作物建模模拟以量化高温和干旱对产量的影响，ii) 条件推理树对最相关的管理实践进行排名，最后，iii) 模糊 C 表示空间聚类以确定与跨作物区域的地理产量集群相关的关键管理实践。

结果

E 分量占低产组（< 7.6 Mg ha ^-1）高粱产量变化的近一半，而 M 因子（主要是种植日期和灌溉）对高产组起着关键作用（> 9.7 毫克公顷^-1 )。地理相关的产量集群确定了三个主要区域，i) 东部（播种日期较早，5 月初，施氮肥率高），ii) 西部（以灌溉为主要因素）在大陆地区，以及 iii) 沿海地区（播种日期在 4 月 1 日之前，得克萨斯州东南部）。对于低产组，行距和植物密度是影响产量变化的关键变量。

结论

这些结果为限制美国主要高粱产区高产农民可实现产量的主要 E 和 M 因素提供了基础见解。