Yao Zhang

Chlorophyll a (Chla) and chlorophyll b (Chlb) in plant leaves play distinct physiological and ecological roles, but most portable chlorophyll meters, such as SPAD meters, mainly provide relative chlorophyll indices rather than the individual contents of Chla and Chlb in vivo leaf conditions. This limitation restricts the acquisition of component-specific pigment information from living leaves and reduces the usefulness of field measurements for validating satellite-derived vegetation biochemical parameters. One key difficulty is that the spectral responses of the two pigments are highly overlapped in vivo , making it difficult to quantitatively characterize their individual absorption contributions and determine suitable sensitive bands for low-cost optical detection. In this study, a Beer–Lambert-inspired pseudo-absorption framework was developed to characterize and effectively separate the overlapping absorption-related spectral responses of Chla and Chlb in leaves of broadleaf species under in vivo conditions. Unlike conventional spectral-index-based approaches, the proposed method provided a physically interpretable empirical basis for sensitive-band selection. Using leaf hyperspectral data, 700 nm and 650 nm were identified as the sensitive bands for Chla and Chlb, respectively, while 900 nm was selected as the reference band for optical path normalization. The algorithm achieved RMSE values of 3.001 μg·cm ^-2 for Chla and 1.805 μg·cm ^-2 for Chlb. Based on the selected bands and optimized channel bandwidths, a low-cost, non-destructive detector for leaf Chla and Chlb contents, named CabD, was developed by integrating controllable spectral generation from multi-band light sources with photoelectric detection. Validation showed that CabD achieved RMSE values of 1.743 μg·cm ^-2 for Chla and 0.871 μg·cm ^-2 for Chlb, respectively, with relative accuracy values of 94.746% and 92.789%. In situ validation using 84 intact leaves yielded RMSE values of 2.245 and 1.530 μg·cm ^-2 , with corresponding relative accuracies of 93.86% and 90.24% for Chla and Chlb, respectively. These results demonstrate that the Beer–Lambert-inspired pseudo-absorption framework can support a physically interpretable empirical strategy for sensitive-band selection in low-cost in vivo chlorophyll detector design. The developed CabD provides a practical tool for non-destructive acquisition of component-specific chlorophyll information and can support field monitoring and remote sensing validation of vegetation biochemical parameters.

High-sensitivity fluorescence monitoring has been widely used in agriculture and environmental science. However, the active fluorescence detection information of leaf segments mainly focuses on total chlorophyll, and the fluorescence information of chlorophyll a, chlorophyll b, and some other pigments has not been explored. This only considers the fluorescence spectrum characteristics at a single wavelength or the fluorescence integral from a range of wavelength regions and does not completely consider the linkage relation between the excitation, emission, and interference information. In this paper, the three-dimensional fluorescence spectrum, containing the excitation and emission fluorescence spectra, and the corresponding multiple pigment characteristics from the upgraded LOPEX_ZJU database were collected. The linkages of excitation and emission of the three-dimensional fluorescence spectra of these pigments were analyzed for the newly built multiple pigment 3-D fluorescence spectral indices (3-D FSIs), including those of chlorophyll a, chlorophyll b, carotenoid, anthocyanin, and flavonoid 3-D FSIs. Then, these pigment inversion models were established and validated. The results show that the 3-D FSIs performances for the photosynthetic pigment content inversion (including chlorophyll a and b, and carotenoids) were much better than those for the photo-protective pigments (including anthocyanins and flavonoids) from the 3-D fluorescence spectra of these plant leaves. Here, the 3-D fluorescence normalization index (FNI ((F_430,690 − F_430,763)/(F_430,690 + F_430,763))) for the chlorophyll a inversion model has a high accuracy, the RMSE is 2.96 μg/cm², and the 3-D fluorescence reciprocal difference index (FRI (F_650,704/F_650,668) for the chlorophyll b model has an encouraging RMSE (2.01 μg/cm²). The RMSE of the 3-D fluorescence ratio index (FRI (F_500,748/F_500,717)) for the carotenoid inversion is 3.77 μg/cm² RMSE. Only FRI (F_370,615/F_370,438) was selected for the modeling and validating evaluation of the leaf Flas content inversion, but the evaluation metrics were not good, with an RMSE (151.13 μg/cm²). For Ants, although there was a 3-D FSI (FRDI (1/F_540,679 − 1/F_540,557)), and its evaluation metrics, with an RMSE (2.8 μg/cm²), were at or over 0.05 level, the validating evaluation metric VC (98.3577%) was not encouraging. These results showed that fluorescence, as a nondestructive and efficient detection method, could determine the contents of chlorophyll a, chlorophyll b, and carotenoid in plant leaves, providing a new method to detect plant information. It can also provide a potential chance for the fluorescence images of fine photo-protective pigments, especially chlorophyll a and b, using the special active fluorescence excitation light source and a few fluorescence imaging channels from the optimal FSIs.

The digitalization of information is crucial for the upgrading of the bayberry digital agriculture industry, while the low-cost information detection sensing equipment for bayberry are a bottleneck for the digital development of the industry. The existing rapid and non-destructive detection devices for fruit acidity and sugar content mainly use near-infrared and mid-infrared spectral characteristic for detection. These devices use expensive InGaAs sensor, which are difficult to promote and apply in the bayberry digital industry. This study is based on the high-spectral range of 454–998 nm in bayberry fruit to study the mechanism of fruit sugar and acidity content detection and to develop a portable bayberry fruit sugar and acidity detection device using Si-sensor in order to achieve low-cost quality parameter detection of bayberry fruit. The research results show that: Based on the hyperspectral of bayberry fruit, the sensitive wavelength for sugar content inversion is 610 nm, and the inversion accuracy (RMSE) is 1.399Brix; the sensitive wavelength for pH inversion is 570 nm, and the inversion accuracy (RMSE) is 0.1329. Based on the above spectroscopic detection mechanism and spectral dimension reduction methods, combined with low-cost Si-sensor (400–1000 nm), a low-cost non-destructive portable bayberry fruit sugar and acidity detection device has been developed, with detection accuracies of 94.74% and 97.14%, respectively. This bayberry fruit sugar and acidity detector provides a low-cost portable non-destructive quality detection instrument of bayberry, which is in line with the industrial group of low consumption in which the bayberry is mainly cultivated on a small scale, accelerating the digitalization process of the bayberry industry.

At present, spring tea yield is mainly estimated through a manual sampling survey. Obtaining yield information is time consuming and laborious for the whole spring tea industry, especially at the regional scale. Remote sensing yield estimation is a popular method used in large-scale grain crop fields, and few studies on the estimation of spring tea yield from remote sensing data have been reported. This is a similar spectrum of fresh tea yield components to that of the tea tree canopy. In this study, two types of unmanned aerial vehicle (UAV) hyperspectral images from the unpicked and picked Anji white tea tree canopies are collected, and research on the estimation of the spring tea fresh yield is performed using the differences identified in the single and combined chlorophyll spectral indices (CSIs) or leaf area spectral indices (LASIs) while also considering the changes in the green coverage of the tea tree canopy by way of a linear or piecewise linear function. The results are as follows: (1) in the linear model with a single index variable (LMSV), the accuracy of spring tea fresh yield models based on the selected CSIs was better than that based on the selected LASIs as a whole, in which the model based on the curvature index (CUR) was the best with regard to the accuracy metrics; (2) compared to the LMSVs, the accuracy performance of the piecewise linear model with the same index variables (PLMSVs) was obviously improved, with an encouraging root mean square error (RMSE) and validation determination coefficient (VR²); and (3) in the piecewise model with the combined index variables (PLMCVs), its evaluation metrics are also improved, in which the best performance of them was the CUR&CUR model with a RMSE (124.602 g) and VR² (0.625). It showed that the use of PLMSVs or PLMCVs for fresh tea yield estimation could reduce the vegetation index saturation of the tea tree canopy. These results show that the spectral difference discovered through hyperspectral remote sensing can provide the potential capability of estimating the fresh yield of spring tea on a large scale.

The PROSPECT leaf optical radiative transfer models, including PROSPECT-MP, have addressed the contributions of multiple photosynthetic pigments (chlorophyll a and b, and carotenoids) to leaf optical properties, but photo-protective pigment (anthocyanins), another important indicator of vegetation physiological and ecological functions, has not been simultaneously combined within a leaf optical model. Here, we present a new calibration and validation of PROSPECT-MP+ that separates the contributions of multiple photosynthetic and photo-protective pigments to leaf spectrum in the 400–800 nm range using a new empirical dataset that contains multiple photosynthetic and photo-protective pigments (LOPEX_ZJU dataset). We first provide multiple distinct in vivo individual photosynthetic and photo-protective pigment absorption coefficients and leaf average refractive index of the leaf interior using the LOPEX_ZJU dataset. Then, we evaluate the capabilities of PROSPECT-MP+ for forward modelling of leaf directional hemispherical reflectance and transmittance spectra and for retrieval of pigment concentrations by model inversion. The main result of this study is that the absorption coefficients of chlorophyll a and b, carotenoids, and anthocyanins display the physical principles of absorption spectra. Moreover, the validation result of this study demonstrates the potential of PROSPECT-MP+ for improving capabilities in remote sensing of leaf photosynthetic pigments (chlorophyll a and b, and carotenoids) and photo-protective pigment (anthocyanins).

Rice false smut is known as the cancer of rice. The disease is becoming increasingly prominent and is one of the major diseases in rice. However, prevention and treatment of this disease relies on “Centralized pesticide spraying”. However, indiscriminate spraying leads to more pesticide residue, and impacts ecological and food safety. To obtain more objective results, different experimental planting forms are necessary. This study collected data at a complex planting environment based on “near earth remote sensing” using a frame-based hyperspectral device. We used mixed detection methods to differentiate between healthy rice and U. virens infected rice. There were 49 arrangements and more than 196 differentiation models between healthy and diseased rice, including 7 sowing data plots, 2 farm management types, and 23 pattern recognition methods. Finally, the real accuracy was mostly above 95%. In particular, with the increase of epoch and iteration, feature sequences based on deep learning could achieve better results; most of the accuracies were 100% with 100 epochs. We also found that differentiation accuracy was not necessarily correlated with the sowing dates and farm management. Finally, the detection method was verified according to the actual investigation results in the field. The prescription map of disease incidence was generated, which provided a theoretical basis for the follow-up precision plant protection work.

The in vivo features of the absorption of leaf photosynthetic and photo-protective pigments are closely linked to the leaf spectrum in the 400–800 nm regions. However, this information is difficult to obtain because the overlapping leaf pigments can mask the contribution of individual pigments to the leaf spectrum. Here, to limit the masking phenomenon between these pigments, the separation technology for leaf spectral overlapping was employed in the PROSPECT model with the ZJU dataset. The main results of this study include the following aspects: (1) the absorption coefficients of separated chlorophyll a and b, carotenoids and anthocyanins in the leaf in vivo display the physical principles of forming an absorption spectrum similar to those in an organic solution; (2) the differences in the position of each absorption peak of pigments between the leaf in vivo and in an organic solution can be described by a spectral displacement parameter; and (3) the overlapping characteristics between the separated pigments in the leaf in vivo are clearly drawn by a range of absorption feature (RAF) parameter. Moreover, the absorption coefficients of the separated pigments were successfully applied in leaf spectral modeling and pigment retrieval. The results show that the separated multiple pigment absorption coefficients from the leaf spectrum in vivo are effective and provide a framework for future refinements in describing leaf optical properties.

The aim of this study was to assess the biomechanical efficacy of transepithelial collagen crosslinking using the femtosecond laser pocket technique compared with that using the standard crosslinking (CXL) technique. Forty ex vivo porcine eyes were divided into 4 groups with 10 samples each. Group 1 comprised the untreated controls. Group 2 was the standard CXL group with debridement, instillation of 0.1% riboflavin-dextran solution for 15 minutes before and every 5 minutes during the 30 minutes of irradiation with ultraviolet A (UVA) light of 370 nm and an irradiance of 3 mW/cm². Group 3 pertained to the femtolaser pocket control with an intrastromal pocket but without riboflavin/UVA. Group 4 was the femtolaser pocket CXL group with an intrastromal pocket of an 8-mm diameter at a 180-μm depth, riboflavin/dextran application for 15 minutes and subsequent exposure to UVA light for 30 minutes. Postoperatively, biomechanical stress-strain measurements were performed. In the standard CXL group, the stress at 10% strain was 207.8 ± 64.1 × 10 Pa (+79.45% vs. controls; P = 0.021) compared with 115.8 ± 20.8 × 10 Pa in the untreated control group; in the crosslinked femtolaser pocket group, it was 159.5 ± 30.4 × 10 Pa (+37.74%; P = 0.049), in the non-cross-linked femtolaser pocket group, it was 103.5 ± 17.3 × 10 Pa (-10.62%; P = 0.103). The Young modulus was 5.4 MPa (+100% vs. controls) in the standard CXL group, 3.7 MPa (+37.04%) in the crosslinked femtolaser pocket group, and 2.4 MPa (-11.12%) in the non-cross-linked femtolaser pocket group compared with 2.7 MPa in the untreated control group. The biomechanical effect of CXL using the femtolaser pocket technique is about 50% less pronounced than that after standard CXL. Future studies will show whether the efficacy of the technique can still be improved and whether the clinical effect is sufficient for stabilizing ectatic corneas.