Detection of Chilling Injury in Pickling Cucumbers Using Dual-Band Chlorophyll Fluorescence Imaging

Dissecting postharvest chilling injuries in pome and stone fruit through integrated omics

Lowering the storage temperature is an effective method to extend the postharvest and shelf life of fruits. Nevertheless, this technique often leads to physiological disorders, commonly known as chilling injuries. Apples and pears are susceptible to chilling injuries, among which superficial scald is the most economically relevant. Superficial scald is due to necrotic lesions of the first layers of hypodermis manifested through skin browning. In peaches and nectarines, chilling injuries are characterized by internal symptoms, such as mealiness. Fruits with these aesthetic or compositional/structural defects are not suitable for fresh consumption. Genetic variation is a key factor in determining fruit susceptibility to chilling injuries; however, physiological, or technical aspects such as harvest maturity and storage conditions also play a role. Multi-omics approaches have been used to provide an integrated explanation of chilling injury development. Metabolomics in pome fruits specifically targets the identification of ethylene, phenols, lipids, and oxidation products. Genomics and transcriptomics have revealed interesting connections with metabolomic datasets, pinpointing specific genes linked to cold stress, wax synthesis, farnesene metabolism, and the metabolic pathways of ascorbate and glutathione. When applied to Prunus species, these cutting-edge approaches have uncovered that the development of mealiness symptoms is linked to ethylene signaling, cell wall synthesis, lipid metabolism, cold stress genes, and increased DNA methylation levels. Emphasizing the findings from multi-omics studies, this review reports how the integration of omics datasets can provide new insights into understanding of chilling injury development. This new information is essential for successfully creating more resilient fruit varieties and developing novel postharvest strategies.

Saline-Alkaline Stress Resistance of Cabernet Sauvignon Grapes Grafted on Different Rootstocks and Rootstock Combinations

Grafting the wine grape variety Cabernet Sauvignon onto salinity-tolerant rootstocks can improve salinity tolerance and grape yields in regions with high salinity soils. In this experiment, the effects of different rootstocks and rootstock combinations on the saline-alkaline stress (modified Hoagland nutrient solution + 50 mmol L-1 (NaCl + NaHCO3)) of Cabernet Sauvignon were studied. Correlation and principal component analyses were conducted on several physiological indicators of saline-alkaline stress. Salinity limited biomass accumulation, induced damage to the plant membrane, reduced the chlorophyll content and photosynthetic capacity of plants, and increased the content of malondialdehyde, sodium (Na+)/potassium (K+) ratio, and antioxidant enzyme activities (superoxide dismutase, peroxidase, and catalase). Significant differences in several indicators were observed among the experimental groups. The results indicate that the saline-alkaline tolerance of Cabernet Sauvignon after grafting was the same as that of the rootstock, indicating that the increased resistance of Cabernet Sauvignon grapes to saline-alkaline stress stems from the transferability of the saline-alkaline stress resistance of the rootstock to the scion.

Image-Based High-Throughput Phenotyping in Horticultural Crops

Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

Intelligent detection for fresh-cut fruit and vegetable processing: Imaging technology

Fresh-cut fruits and vegetables are healthy and convenient ready-to-eat foods, and the final quality is related to the raw materials and each step of the cutting unit. It is necessary to integrate suitable intelligent detection technologies into the production chain so as to inspect each operation to ensure high product quality. In this paper, several imaging technologies that can be applied online to the processing of fresh-cut products are reviewed, including: multispectral/hyperspectral imaging (M/HSI), fluorescence imaging (FI), X-ray imaging (XRI), ultrasonic imaging, thermal imaging (TI), magnetic resonance imaging (MRI), terahertz imaging, and microwave imaging (MWI). The principles, advantages, and limitations of these imaging technologies are critically summarized. The potential applications of these technologies in online quality control and detection during the fresh-cut processing are comprehensively discussed, including quality of raw materials, contamination of cutting equipment, foreign bodies mixed in the processing, browning and microorganisms of the cutting surface, quality/shelf-life evaluation, and so on. Finally, the challenges and future application prospects of imaging technology in industrialization are presented.