小麦盐与物理损伤胁迫下果胶高光谱反演模型

小麦是我国的主要粮食作物，在国民经济发展中具有举足轻重的地位。然而，盐与物理损伤等非生物胁迫，逐渐成为制约小麦产量和品质的重要因素。研究表明，细胞壁是植物细胞直接抵御逆境胁迫的重要防线。盐胁迫下，细胞渗透压增大，质膜的透性会受到一定程度的影响。为了维持细胞的形态和结构，植物细胞壁中的果胶等多糖物质会发生不同程度的转化和改变。物理损伤，会加深植物细胞膜脂过氧化的程度，使膜通透性增大，导致营养物质的流失和降解。受到损伤的部位及其周边细胞还会发生栓化以阻塞病菌的侵入。构成植物细胞壁主要成分且能够反映细胞壁以及膜系统完整性和透过性的果胶，可以作为研究胁迫下植物内部物质响应规律的重要指标。目前，质量法、比色法、液相色谱法等常用的果胶检测方法操作繁琐、实时性不强且对样本损耗较大。亟需一种操作简便、检测速度快、无损的检测方法。将烟农0428小麦作为研究对象，采用水培方式，以向培养液中施加氯化钠(NaCl)溶液和对小麦第一片叶主脉两侧针刺分别模拟盐胁迫和昆虫叮咬造成的物理损伤，并完成小麦叶片果胶及高光谱信息的采集与处理。利用相关分析法筛选光谱敏感波段，将主成分回归(PCR)、偏最小二乘法(PLS)、逐步多元线性回归(SMLR)三种建模方法分别与多元散射校正(MSC)、标准正态变换(SNV)、一阶导数(FD)、卷积平滑(S-G)、Norris导数滤波(NDF)等预处理技术相结合，建立果胶含量反演模型。最终，选定PLS+SNV+FD+NDF方法建立的模型为最优模型，并对其性能进行了测试。结果表明：果胶含量的预测值与实测值一致性较高，拟合系数(R2)和均方根误差(RMSE)分别为0.997 6和0.35；预测值重复性较好，相对标准偏差(RSD)为1.2%。该研究以新方法实现小麦果胶的高精度、快速、无损检测，有助于小麦响应逆境胁迫机理的深入探索，并为大田作物胁迫程度预测及种植环境的精准管控提供参考。

Hyperspectral Inversion Model of Pectin Content in Wheat Under Salt and Physical Damage Stresses

Wheat is the primary grain crop in our country and plays a pivotal role in developing the national economy. However, abiotic stress factors such as salt and physical damage have gradually become essential factors restricting wheat yield and quality. Studies have shown that the cell wall is an important line of defence for plant cells to resist adversity and stress directly. Under salt stress, cell osmotic pressure increases, and the permeability of the plasma membrane will be affected to a certain extent. In order to maintain cell morphology and structure, pectin and other polysaccharides in plant cell walls will be transformed and changed to varying degrees. Physical damage will deepen the degree of lipid peroxidation of plant cell membranes, increase membrane permeability, and lead to the loss and degradation of nutrients. The damaged site and its surrounding cells will also be embolized to block the invasion of bacteria. Pectin, which is the main component of cell wall and can reflect the integrity and permeability of the plant cell wall and membrane system, can be used as an important factor in studying the response mechanism of plant internal substances under stress. At present, commonly used pectin detection methods such as Gravimetric Colorimetric, Liquid chromatography, etc. are cumbersome to operate, not real-time, and large sample consume. There is an urgent need for a simple, fast and non-destructive detection method. This paper used hydroponics to research the wheat (Yannong 0428). The sodium chloride (NaCl) solution was applied to culture medium, and acupuncture was carried out on both sides of the main vein of the first leaf of wheat to simulate the salt damage and the physical damage caused by insect bites, respectively. The pectin and its hyperspectral information of wheat leaf were also collected and processed. The correlation analysis method was used to screen the sensitive spectral band. The three modeling methods of principal component regression (PCR), partial least squares (PLS), and stepwise multiple linear regression (SMLR) were combined with multiple scattering correction processing (MSC), standard normal transformation processing (SNV), first derivative processing (FD), convolution smoothing (SG), and Norris derivative filter processing (NDF) to establish a pectin content inversion model. Finally, the model established by PLS+SNV+FD+NDF method was selected as the optimal model, and its performance was also tested. The results showed that the predicted value of pectin content was consistent with the measured value, and the coefficient of determination (R2) and root mean square error (RMSE) were determined to be 0.997 6 and 0.35, respectively. The repeatability of the predicted value was good, and the relative standard deviation (RSD) was 1.2%. This study uses a new method to realize the high-precision, fast and non-destructive detection of wheat pectin, which is helpful to the in-depth study of the mechanism of the wheat response to stress and provides a reference for the prediction of the stress degree of field crops and the accurate control of planting environment.