Identifying the Growth Status of Hydroponic Lettuce Based on YOLO-EfficientNet.

Hydroponic lettuce was prone to pest and disease problems after transplantation. Manual identification of the current growth status of each hydroponic lettuce not only consumed time and was prone to errors but also failed to meet the requirements of high-quality and efficient lettuce cultivation. In response to this issue, this paper proposed a method called YOLO-EfficientNet for identifying the growth status of hydroponic lettuce. Firstly, the video data of hydroponic lettuce were processed to obtain individual frame images. And 2240 images were selected from these frames as the image dataset A. Secondly, the YOLO-v8n object detection model was trained using image dataset A to detect the position of each hydroponic lettuce in the video data. After selecting the targets based on the predicted bounding boxes, 12,000 individual lettuce images were obtained by cropping, which served as image dataset B. Finally, the EfficientNet-v2s object classification model was trained using image dataset B to identify three growth statuses (Healthy, Diseases, and Pests) of hydroponic lettuce. The results showed that, after training image dataset A using the YOLO-v8n model, the accuracy and recall were consistently around 99%. After training image dataset B using the EfficientNet-v2s model, it achieved excellent scores of 95.78 for Val-acc, 94.68 for Test-acc, 96.02 for Recall, 96.32 for Precision, and 96.18 for F1-score. Thus, the method proposed in this paper had potential in the agricultural application of identifying and classifying the growth status in hydroponic lettuce.

Comparative proteomic analysis of pepper (Capsicum annuum L.) seedlings under selenium stress.

Selenium (Se) is an essential trace element for human and animal health. Se fertilizer has been used to increase the Se content in crops to meet the Se requirements in humans and animals. To address the challenge of Se poisoning in plants, the mechanisms underlying Se-induced stress in plants must be understood. Here, to elucidate the effects of Se stress on the protein levels in pepper, we used an integrated approach involving tandem mass tag labeling, high performance liquid chromatography fractionation, and mass spectrometry-based analysis. A total of 4,693 proteins were identified, 3,938 of which yielded quantitative information. Among them, the expression of 172 proteins was up-regulated, and the expression of 28 proteins was down-regulated in the Se/mock treatment comparison. According to the above data, we performed a systematic bioinformatics analysis of all identified proteins and differentially expressed proteins (DEPs). The DEPs were most strongly associated with the terms "metabolic process," "posttranslational modification, protein turnover, chaperones," and "protein processing in endoplasmic reticulum" according to Gene Ontology, eukaryotic orthologous groups classification, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, respectively. Furthermore, several heat shock proteins were identified as DEPs. These results provide insights that may facilitate further studies on the pepper proteome expressed downstream of the Se stress response. Our data revealed that the responses of pepper to Se stress involve various pathways.