Near-infrared (NIR) spectroscopy was applied for the determination of total soluble solid contents (SSC) of single Ruby Seedless grape berries using both benchtop Fourier transform (VECTOR 22/N) and portable grating scanning (SupNIR-1500) spectrometers in this study. The results showed that the best SSC prediction was obtained by VECTOR 22/N in the range of 12,000 to 4000 cm⁻¹ (833–2500 nm) for Ruby Seedless with determination coefficient of prediction (R_p²) of 0.918, root mean squares error of prediction (RMSEP) of 0.758% based on least squares support vector machine (LS-SVM). Calibration transfer was conducted on the same spectral range of two instruments (1000–1800 nm) based on the LS-SVM model. By conducting Kennard-Stone (KS) to divide sample sets, selecting the optimal number of standardization samples and applying Passing-Bablok regression to choose the optimal instrument as the master instrument, a modified calibration transfer method between two spectrometers was developed. When 45 samples were selected for the standardization set, the linear interpolation-piecewise direct standardization (linear interpolation-PDS) performed well for calibration transfer with R_p² of 0.857 and RMSEP of 1.099% in the spectral region of 1000–1800 nm. And it was proved that re-calculating the standardization samples into master model could improve the performance of calibration transfer in this study. This work indicated that NIR could be used as a rapid and non-destructive method for SSC prediction, and provided a feasibility to solve the transfer difficulty between totally different NIR spectrometers.

At present, detection methods for rice microbial indicators are usually based on microbial culture or sensory detection methods, which are time‐consuming or require expertise and thus cannot meet the needs of on‐site rice testing when the rice is taken out of storage or traded. In order to develop a fast and non‐destructive method for detecting rice mildew, in this paper, micro‐computer vision technology is used to collect images of mildewed rice samples from 9 image locations. Then, a YOLO‐V5 convolutional neural network model is used to detect moldy areas of rice, and the mold coverage area is estimated. The relationship between the moldy areas and the total number of bacterial colonies in the image is obtained. The results show that the precision and the recall of the established YOLO‐v5 model in identifying the mildewed areas of rice in the validation set were 82.1% and 86.5%, respectively. Based on the mean mildewed area identified by the YOLO‐v5 model, the precision and recall for light mold detection were 100% and 95.3%, respectively. The proposed method based on micro‐computer vision and the YOLO convolutional neural network can be applied to the rapid detection of mildew in rice taken out of storage or traded.

The Chinese alligator (Alligator sinensis), found only in a small region in southeastern Anhui Province, is listed as critically endangered (CR) by the International Union for Conservation of Nature (IUCN) due to its current declining population trend. Any abnormalities in the physical properties of an egg can decrease the hatching rate. In particular, eggshells play an essential role in embryo development, motivating us to analyze the microstructures of the eggshells of Chinese alligators. In this study, we categorized the eggshells into two groups, based on the hatching rates, and analyzed the relationship between the eggshell parameters (eggshell thickness, calcium content, and number of pores in erosion craters) and the hatching rate, as well as the relationships between the eggshell parameters. We found that the shells of the eggs with high hatching rates were thicker than those of the eggs with low hatching rates. There were also fewer erosion-crater pores on the surfaces of the eggs with high hatching rates than on the surfaces of the eggs with low hatching rates. Moreover, the shell Ca content was significantly higher in the eggs with high hatching rates than in the eggs with low hatching rates. Cluster modeling indicated that the highest hatching rate occurred when the eggshell thickness was 200–380 µm and there were 1–12 pores. These results suggest that eggs with adequate Ca contents, thicker shells, and less air permeability are more likely to hatch. Furthermore, our findings can inform future studies, which will be vital for the survival of the critically endangered Chinese alligator species.

Habitat adaptation critically influences relocation success in endangered reptiles. Forestland is the dominant landscape in most of the nature reserves that are used for the relocation of the Chinese alligator. To evaluate habitat suitability and utilization, we analysed movement rates and home range of Chinese alligators within a core habitat of the nature reserve, concurrently assessing habitat suitability and carrying capacity. Results indicate severely restricted annual home ranges (average 7.415 ± 7.347 × 10 ⁴ m ² per alligator) and limited seasonal activity (March–October), with peak utilization confined to June–August in some individuals. Forestland cover significantly impeded the movement of Chinese alligators, and only 4.62% of the study area qualified as high-suitability habitat, supporting a carrying capacity of 147 individual Chinese alligators. Unsuitable habitat and climate drastically reduced the spatial and temporal utilization of the habitat. Conservation strategies should prioritize enhancing habitat quality and addressing the survival requirements and migration patterns of the Chinese alligator during the active period within nature reserves.

Orchidaceae are one of the two largest families of flowering plants, new orchid genera are being described at a rate of about 13 per year. Bletilla sinensis is one of five species in the Bletilla. It has high medicinal value and can promote blood circulation and anti-inflammation. However, its phylogenetic status is controversial. In this study, the chloroplast genes of B. sinensis were sequenced and assembled, and download 73 complete chloroplast genes of orchid plants from NCBI to construct a molecular evolutionary tree, which provided new clues for the classification of B. sinensis. The results showed that the length of chloroplast genes was 156,941 bp, the GC content was 37.12%, and it contained 139 genes. The results of the molecular evolutionary tree show that the genus Bletilla is a single branch and has an independent evolutionary status. However, our sample is not in the same branch as the Bletilla, indicating that this sample may have an independent and effective taxonomic status. Based on the chloroplast genome structure and composition of this species, it also supports its independent taxonomic status from the Bletilla. Judging from the genetic distance between genera of Orchidaceae, the genetic distance between this sample and any other genera is greater than 0.02, which is greater than the genetic distance between the other two identified genera. In addition, the integration of morphological data from the Flora of China found that there are certain differences in morphology from other species of the genus Bletilla. Therefore, the above results suggest that this group should be a new genus of Orchidaceae.