小麦是我国的主要粮食作物之一, 对国民经济发展具有显著的影响。 然而, 高温与紫外线胁迫导致其产量大幅下降。 胁迫发生时, 细胞壁内多糖物质会发生不同程度的转变。 作为此类多糖重要组成成分的果胶, 在决定细胞间孔隙度、 识别病菌、 维持结构完整等方面扮演着重要角色。 当前, 常见的果胶检测方法有重量法、 滴定法、 酸提取法等, 这些方法多为有损检测, 测定步骤繁琐, 样本损耗量大。 近年来, 光谱检测因其检测速度快、 分辨率高、 实时性强等优点, 在植物生理信息检测领域得到了广泛应用。 因此, 研究采用光谱检测果胶含量。 以济麦22为研究对象, 采取水培方式, 通过调控人工气候培养箱温度及紫外线灯辐照强度对小麦生长过程中遇到的高温及紫外线胁迫环境进行模拟; 在小麦分蘖期, 分别采集叶片高光谱数据与叶绿素荧光光谱数据, 测定叶片果胶含量, 通过小波分析方法对两种原始光谱数据进行平滑与降噪处理, 采用相关系数分析法得到两种光谱数据与果胶含量相关系数最高的重合波段(620, 651), 取该波段内两光谱数据平均值, 重塑双光谱曲线; 按照3:1比例划分训练集和验证集, 采用PLS最小二乘法分别建立高光谱反演果胶模型、 荧光光谱反演果胶模型及双光谱反演果胶模型。 结果表明: 双光谱模型反演的小麦叶片果胶含量效果较好, 对应模型的训练集与验证集相关系数分别为0.944 9及0.944 5。 该研究有助于探究逆境胁迫下小麦细胞壁内多糖物质响应情况, 并为大田作物所处胁迫环境和程度的预测及种植环境的精准管控提供参考和帮助。

Wheat is one of China's main food crops, which significantly impacts the development of the national economy. However, high temperature and UV stress led to a significant decline in its yield.When stresses occur, the polysaccharides in the cell wall will change to different degrees. As an important component of such polysaccharides, pectin plays a major role in determining intercellular porosity, identifying pathogens, and maintaining structural integrity. At present, common pectin detection methods include a gravimetric method, titration method, acid extraction method, etc. Most of these methods are damaging detection, whose determination steps are cumbersome, and the sample's loss is large. In recent years, spectral detection technology has been widely used in the field of plant physiological information detection due to its advantages of simplicity, rapidity, high resolution, and strong real-time performance. Therefore, in this study, the hyperspectral and chlorophyll fluorescence spectrum detection technology were used to determine pectin's content. Taking Ningmai 13 as the research object, the hydroponics method was adopted. The high temperature and UV stress environment was simulated during wheat growth by adjusting the temperature of the artificial climate incubator and the irradiation intensity of the UV lamp. At the tillering stage of wheat, hyperspectral data and chlorophyll fluorescence spectrum data of leaves were collected, and the pectin content in leaves was determined. The two original spectral data were smoothed and denoised by wavelet analysis. The coincidence band with the highest correlation coefficient between the two spectral data and pectin content was (620, 651) by correlation coefficient analysis. The training set and the validation set were divided in a ratio of 3:1.The hyperspectral inversion pectin model, the fluorescence spectrum inversion pectin model and the double spectrum inversion pectin model were established by the PLS least squares method. The research results show that the inversion effect of pectin content in wheat leaves by double spectrum is good. The model's correlation coefficients of the training set and verification set are 0.994 9 and 0.944 5. The conclusions of this study are helpful in explore the response of polysaccharides in the cell wall of wheat under adversity stress. They also can provide references and help for predicting the degree of stress environment of field crops and controlling the planting environment accurately.