Mid-season prediction of grain yield and protein content of spring barley cultivars using high-throughput spectral sensing
Mid-season prediction of grain yield and protein content of spring barley cultivars using high-throughput spectral sensing
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DOI：
10.1016/j.eja.2017.07.005
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发表时间：
2017-10-01
影响因子：
5.2
通讯作者：
Schmidhalter, Urs
中科院分区：
文献类型：
--
作者：
Barmeier, Gero;Hofer, Katharina;Schmidhalter, Urs
预测春大麦的谷物产量和蛋白质含量的能力对麦芽和酿造行业以及植物育种特别有意义。然而，早期预测谷物产量和蛋白质含量的方法理想上应该是省时、非破坏性和廉价的。在这项利用移动表型平台PhenoTrac 4进行的为期3年的研究中，34个品种的近距离遥感反射率数据被用来制定植被指数和校准PLSR模型，随后在独立的田间试验中进行验证。通过对PLSR、NDVI和REIP指数以及最优植被指数的比较表明，PLSR和REIP(R2=0.71~0.95)对粮食产量具有较好的预测效果。此外，还可以区分不同品种的表现。相比之下，蛋白质含量不能可靠地预测。作为另一种选择，对开花期叶片氮素吸收的PLSR模型进行了检验，以预测籽粒蛋白质含量。相关系数R-2=0.61，但蛋白质含量被高估。结果表明，基于拖拉机的近距离遥感是一种高通量、非破坏性、高精度的春大麦产量预测方法，可以为酿酒行业和植物育种工作者提供信息。
The ability to forecast grain yields and protein contents of spring barley is of particular interest for the malting and brewing industry, as well as for plant breeding. However, methods for early prediction of grain yield and protein content should ideally be timesaving, non-destructive and inexpensive. In this 3-year study using the mobile phenotyping platform PhenoTrac 4, proximally sensed reflectance data of 34 cultivars were used to develop vegetation indices and to calibrate PLSR models, followed by subsequent validation in independent field trials. A comparison among PLSR, the NDVI and REIP indices and an optimized vegetation index indicated that PLSR and REIP (R-2 = 0.71-0.95) gave superior predictions of grain yield. Furthermore, it was possible to distinguish the performance of different cultivars. In contrast, protein content could not be predicted reliably. As an alternative, a PLSR model of leaf N uptake at anthesis was tested to predict grain protein content. Satisfactory correlations were obtained with R-2 = 0.61, but protein content was considerably overestimated. The results show that tractor-based proximal sensing is a high-throughput, non-destructive and precise method to predict the grain yield of spring barley and could be a suitable tool to deliver information for the brewing industry and plant breeders.