Non-destructive Measurements of Toona sinensis Chlorophyll and Nitrogen Content Under Drought Stress Using Near Infrared Spectroscopy

Abstract

Drought is a climatic event that considerably impacts plant growth, reproduction and productivity. Toona sinensis is a tree species with high economic, edible and medicinal value, and has drought resistance. Thus, the objective of this study was to dynamically monitor the physiological indicators of T. sinensis in real time to ensure the selection of drought-resistant varieties of T. sinensis. In this study, we used near-infrared spectroscopy as a high-throughput method along with five preprocessing methods combined with four variable selection approaches to establish a cross-validated partial least squares regression model to establish the relationship between the near infrared reflectance spectroscopy (NIRS) spectrum and physiological characteristics (i.e., chlorophyll content and nitrogen content) of T. sinensis leaves. We also tested optimal model prediction for the dynamic changes in T. sinensis chlorophyll and nitrogen content under five separate watering regimes to mimic non-destructive and dynamic detection of plant leaf physiological changes. Among them, the accuracy of the chlorophyll content prediction model was as high as 72%, with root mean square error (RMSE) of 0.25, and the RPD index above 2.26. Ideal nitrogen content prediction model should have R2 of 0.63, with RMSE of 0.87, and the RPD index of 1.12. The results showed that the PLSR model has a good prediction effect. Overall, under diverse drought stress treatments, the chlorophyll content of T. sinensis leaves showed a decreasing trend over time. Furthermore, the chlorophyll content was the most stable under the 75% field capacity treatment. However, the nitrogen content of the plant leaves was found to have a different and variable trend, with the greatest drop in content under the 10% field capacity treatment. This study showed that NIRS has great potential for analyzing chlorophyll nitrogen and other elements in plant leaf tissues in non-destructive dynamic monitoring.

Classification of Toona sinensis Young Leaves Using Machine Learning and UAV-Borne Hyperspectral Imagery

“…Moreover, evaluating the yield of T. sinensis by picking is not applicable in a large area. Among the spectroscopic studies of T. sinensis , most studies focus on the estimation of leaf biochemistry (e.g., chlorophyll and nitrogen content) and wood chemicals (e.g., heartwood extract content; Li et al, 2020 ; Liu et al, 2021b ). However, few studies discuss how to quickly distinguish young and old leaves of T. sinensis, which plays an important role in breeding and estimating relative T. sinensis yield and provides a technical basis for machine picking of T. sinensis .…”

Three-Dimensional Quantification and Visualization of Leaf Chlorophyll Content in Poplar Saplings under Drought Using SFM-MVS

“…Figure 9c shows the changes in the three-dimensional chlorophyll distribution of four poplar varieties within 15 days before and after mild drought stress. From the visual model shown in pictures ( 8), ( 9), ( 10), (11), before the onset of drought stress (upper dotted The first to fourth sub-pictures in Figure 9a are the chlorophyll three-dimensional visualization models from the first to the fourth week when data collection begins. Under natural growth conditions, the chlorophyll content of poplar saplings gradually accumulates with the time of photosynthesis.…”

“…Figure 9c shows the changes in the three-dimensional chlorophyll distribution of four poplar varieties within 15 days before and after mild drought stress. From the visual model shown in pictures ( 8), ( 9), ( 10), (11), before the onset of drought stress (upper dotted line box), the poplar trees of the four genotypes all showed a longitudinal gradient distribution of chlorophyll. The difference in chlorophyll distribution between different varieties was not obvious, but significant changes occurred after drought stress (lower dotted line box), at this time, the average chlorophyll content of the four varieties was 895 > SY-1 > 110 > 3804.…”

“…The distribution among various plant organs is still unclear. Some scholars use methods, such as chlorophyll fluorescence and spectral reflectance, to visualize the chlorophyll content of plant canopy leaves, but most can only achieve a two-dimensional scale, and integrated fluorescence analyzers and spectral sensors also have high requirements for the imaging environment and high price, thus limiting its application to a wide range [11]. At the same time, due to the limitation of data dimension and spatial resolution, the image and spectral information from an overhead view or a single perspective can only reflect the phenotypic information of plants projected at a certain static angle, and it is difficult to perceive the stereoscopic changes of plant phenotype between different organs caused by physiological stress, water, and fertilizer deficiency and other reasons.…”

Sequencing and analysis of the complete mitochondrial genomes of Toona sinensis and Toona ciliata reveal evolutionary features of Toona

“…T.sinensis is not only an excellent vegetable but also a natural green nutritious food of medicinal and food origin. It has somewhat high happiness of flavone and other pharmacologically dynamic mixtures [8,9]. T.ciliata is a Grade II safeguarded plant, an important timber tree, and a therapeutic plant that has acquired broad consideration as of late [10][11][12][13].…”