Estimation of biometric, physiological, and nutritional variables in lettuce seedlings using multispectral images

ABSTRACT The formation of seedlings is one of the most important phases of lettuce cultivation. Therefore, any strategy that aims to obtain high-quality seedlings can increase productivity. One of these strategies is the prediction of morphophysiological attributes based on optical properties. The objective of this study was to quantitatively estimate the biometric variables of lettuce from parametric and non-parametric models based on the response of multispectral camera images. The experiment was conducted in a greenhouse in the municipality of Uberaba, Minas Gerais State, Brazil. Twenty days after sowing, multispectral images of the plants were captured using a MAPIR Survey 3 camera. To compose the estimation models, along with the original bands of the camera, the multispectral vegetation indices were calculated using the calibrated original camera bands. Bands B550, B660, and B850 and the near-infrared indices contributed significantly to estimating the physiological variable models, with B850 contributing the most to the biometric and nutritional variables. From the near-infrared band (B850) and derived indices, it was possible to estimate all the agronomic variables from the models generated by the M5 algorithm, with an accuracy of up to 1.6% for the maximum quantum yield. Thus, it is possible to quantify the biometric, physiological, and nutritional variables of lettuce using a multispectral camera. Among the Mapir camera bands, B660 exhibited the greatest variability, showing that the red range was the most sensitive.

摘要：幼苗培育是生菜栽培过程中至关重要的阶段之一。因此，任何旨在培育优质壮苗的策略均可提升生产效益。其中一类策略为基于光学特性预测生菜的形态生理属性。本研究旨在基于多光谱相机（multispectral camera）的成像响应，通过参数化模型与非参数化模型定量估算生菜的生物特征变量。本试验于巴西米纳斯吉拉斯州乌贝拉巴市的温室中开展。播种20天后，采用MAPIR Survey 3相机采集植株的多光谱图像。为构建估算模型，除使用相机原始波段外，还基于校准后的原始相机波段计算了多光谱植被指数（multispectral vegetation indices）。波段B550、B660及B850与近红外指数对生理变量模型的构建贡献显著，其中B850对生物特征与营养变量的估算贡献最大。借助近红外波段（B850）及其衍生指数，可通过M5算法生成的模型估算所有农艺变量，其中最大量子产率（maximum quantum yield）的估算精度可达1.6%。综上，利用多光谱相机可定量检测生菜的生物特征、生理及营养相关变量。在Mapir相机的波段中，B660的变异性最强，表明红光波段敏感性最高。