小麦茎秆生物力学特性无损检测技术

针对当前小麦生物量的无损检测技术存在精度低、效率低等问题，采用力学传感技术和多元回归分析构建了小麦地上鲜生物量的预测模型，并探究了模型对不同生育期小麦生物量的预测效果。研究结果显示，在测量高度40 cm时，模型的预测效果最好；对抽穗期小麦生物量的预测效果最好，其测试集R2=0.623，RMSE=0.216 kg；融合测量高度和株高等特征参量并不能显著提高小麦生物量的预测效果。这次研究在小麦育种的快速无损检测研究中具有一定的参考价值。 

Nondestructive Testing Technology for Biomechanical Properties of Wheat Stem

At present，the non-destructive detection technology of wheat biomass has problems of low precision and low efficiency.Mechanical sensing technology and multiple regression analysis were used to construct prediction model of wheat aboveground fresh biomass，and prediction effect of wheat biomass in different growth stages was explored.Results showed that prediction effect of the model was the best when measurement height was 40 cm；prediction effect of the model was the best when measurement height was 40 cm.R2 value of the test set was 0.623，and RMSE value was 0.216 kg.Combination of measurement height and plant height characteristic parameters could not significantly improve prediction effect of wheat biomass.This study has a certain reference value in the rapid and non-destructive detection of wheat breeding.