ABSTRACT

Betalains (Bt) are a collective group of natural, edible, red-yellow plant pigments, and are an important biochemical parameter in vegetable growth. Betalains are believed to have fungicidal activity and their presence in plants is a key to explaining the physiological response and resistance of plants caused by different environmental stress factors or seasonal fluctuations. Hyperspectral remote sensing has proven potential to understand many biochemical processes widely used in investigating vegetation growth condition. To better understand vegetation containing betalain pigments, for growth monitoring and agronomic decision-making, a novel betalain source, Suaeda salsa (S. salsa) was studied by extracting betalain at different phenological periods, and registering the results with time-course measurements of canopy spectral reflectance via hyperspectral remote imaging. Partial least squares regression (PLSR) analysis was undertaken with three spectral transformation methods (the raw hyperspectral reflectance (R), first derivative reflectance (FDR) and second derivative reflectance (SDR). The variable importance in projection (VIP) score resulting from PLSR model was used to determine the key spectral wavelengths and reduce the dimensionality of the hyperspectral reflectance data matrix. The study results demonstrated that Bt content had a significant correlation with the effective wavelength (FD-R_436nm, R_847nm, R_848nm, R_860nm, R_871nm, R_971nm and SD-R_437nm, R_496nm, R_499nm, R_508nm, R_740nm, R_772nm, R_774nm, R_780nm) and optimized spectral indices (simple normalized difference spectral indices (NDSI_{(802nm,408nm)}, NDSI_{(781nm,776nm)}), normalized polarization indices (NPDI_{(781nm,775nm)}, NPDI_{(781nm,776nm)}), ratio spectral indices (RSI_{(781nm,776nm)}, RSI_{(781nm,775nm)}), chlorophyll indices(CI_{(781nm,776nm)}, CI_{(781nm, 775nm)}) derived from first derivative spectral reflectance. The PLSR-5 (constructed with the spectral indices) model resulted in an R²_val (determination coefficient) of 0.79 and root mean square error (RMSE_val) was 0.81 μg cm⁻². Compared to PLSR-3 model built by sensitive bands, the PLSR-5 model estimation accuracy increased 15%. These results suggest the possibility of estimating Bt content using hyperspectral indices, which contain sufficient information for a successful estimation. Study findings will help researchers in deciding suitable Bt indices for S. salsa growth status and stress assessment, and will facilitate detection growth condition of the vegetables with betalain pigments.

摘要

Betalains（Bt）是一组天然的，可食用的红黄色植物色素，是蔬菜生长中的重要生化参数。人们认为甜菜碱具有杀真菌活性，它们在植物中的存在是解释由不同环境胁迫因素或季节性波动引起的植物的生理反应和抗性的关键。高光谱遥感已被证明具有理解许多广泛用于调查植被生长状况的生化过程的潜力。为了更好地了解含有甜菜碱色素的植被，以便进行生长监测和农艺决策，一种新颖的甜菜碱来源为Suaeda salsa（S. salsa）的研究方法是在不同的物候期提取甜菜碱，然后通过高光谱远程成像将结果记录在冠层光谱反射率的时程测量中。使用三种光谱变换方法（原始高光谱反射率（R），一阶导数反射率（FDR）和二阶导数反射率（SDR））进行了偏最小二乘回归（PLSR）分析。用该模型确定关键光谱波长并降低高光谱反射率数据矩阵的维数，研究结果表明，Bt含量与有效波长（FD- R _436nm，R _847nm）有显着相关性。，R _848nm，R _860nm，R _871nm，R _971nm和SD- R _437nm，R _496nm，R _499nm，R _508nm，R _740nm，R _772nm，R _774nm，R _780nm）和优化的光谱指数（简单的归一化差异光谱指数（ NDSI _{（802nm，408nm）}，NDSI _{（781nm，776nm）}），归一化偏振指数（NPDI _{（781nm，775nm）}，NPDI_{（781nm，776nm）} ），比谱指数（RSI _{（781nm，776nm）}，RSI _{（781nm，775nm）} ），叶绿素指数（CI _{（781nm，776nm）}，CI _{（781nm，775nm）} ）从一阶导数光谱反射率的。PLSR-5（由光谱指数构建）模型得出的R ² _val（测定系数）为0.79，均方根误差（RMSE _val）为0.81μgcm ^-2。与敏感频段建立的PLSR-3模型相比，PLSR-5模型的估计精度提高了15％。这些结果表明使用高光谱指数估算Bt含量的可能性，其中高光谱指数包含用于成功估算的足够信息。研究结果将有助于研究人员确定合适的Bt指数，以用于S. salsa生长状况和压力评估，并有助于检测含有甜菜碱色素的蔬菜的生长状况。