Agricultural Engineering Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt.
Department of Plant Production, College of Food and Agriculture Sciences, King Saud University, Riyadh 11451, Saudi Arabia.
Sensors (Basel). 2020 Nov 17;20(22):6569. doi: 10.3390/s20226569.
Proximal hyperspectral sensing tools could complement and perhaps replace destructive traditional methods for accurate estimation and monitoring of various morpho-physiological plant indicators. In this study, we assessed the potential of thermal imaging (TI) criteria and spectral reflectance indices (SRIs) to monitor different vegetative growth traits (biomass fresh weight, biomass dry weight, and canopy water mass) and seed yield (SY) of soybean exposed to 100%, 75%, and 50% of estimated crop evapotranspiration (ETc). These different plant traits were evaluated and related to TI criteria and SRIs at the beginning bloom (R1) and full seed (R6) growth stages. Results showed that all plant traits, TI criteria, and SRIs presented significant variations ( < 0.05) among irrigation regimes at both growth stages. The performance of TI criteria and SRIs for assessment of vegetative growth traits and SY fluctuated when relationships were analyzed for each irrigation regime or growth stage separately or when the data of both conditions were combined together. TI criteria and SRIs exhibited a moderate to strong relationship with vegetative growth traits when data from different irrigation regimes were pooled together at each growth stage or vice versa. The R6 and R1 growth stages are suitable for assessing SY under full (100% ETc) and severe (50% ETc) irrigation regimes, respectively, using SRIs. The overall results indicate that the usefulness of the TI and SRIs for assessment of growth, yield, and water status of soybean under arid conditions is limited to the growth stage, the irrigation level, and the combination between them.
近红外光谱传感工具可以补充甚至取代传统的破坏性方法，用于准确估计和监测各种形态生理植物指标。在本研究中，我们评估了热成像 (TI) 标准和光谱反射率指数 (SRI) 监测不同植物生长特性（生物量鲜重、生物量干重和冠层水质量）和大豆种子产量 (SY) 的潜力，大豆暴露于估计作物蒸散量 (ETc) 的 100%、75%和 50%。在初花期 (R1) 和全种子期 (R6)，评估了这些不同的植物特性，并将其与 TI 标准和 SRI 相关联。结果表明，在两个生长阶段，所有植物特性、TI 标准和 SRI 在不同灌溉制度之间均呈现显著变化（<0.05）。在分别分析每个灌溉制度或生长阶段的关系时，或当将两种情况的数据合并在一起时，TI 标准和 SRI 评估植物生长特性和 SY 的性能波动。当将不同灌溉制度的数据汇集在一起时，TI 标准和 SRI 在每个生长阶段或反之亦然时，与植物生长特性之间存在中度至强关系。在 R6 和 R1 生长阶段，分别使用 SRI 可以评估全灌溉（100%ETc）和严重灌溉（50%ETc）制度下的 SY。总体结果表明，TI 和 SRI 用于评估干旱条件下大豆的生长、产量和水分状况的有用性仅限于生长阶段、灌溉水平以及它们之间的组合。
