Cold stress is known as the important yield-limiting factor of heading type Kimchi cabbage (HtKc, Brassica rapa L. ssp. pekinensis), which is an economically important crop worldwide. However, the biochemical and molecular responses to cold stress in HtKc are largely unknown. In this study, we conducted transcriptome analyses on HtKc grown under normal versus cold conditions to investigate the molecular mechanism underlying HtKc responses to cold stress. A total of 2131 genes (936 up-regulated and 1195 down-regulated) were identified as differentially expressed genes and were significantly annotated in the category of “response to stimulus.” In addition, cold stress caused the accumulation of polyphenolic compounds, including p-coumaric, ferulic, and sinapic acids, in HtKc by inducing the phenylpropanoid pathway. The results of the chemical-based antioxidant assay indicated that the cold-induced polyphenolic compounds improved the free-radical scavenging activity and antioxidant capacity, suggesting that the phenylpropanoid pathway induced by cold stress contributes to resistance to cold-induced reactive oxygen species in HtKc. Taken together, our results will serve as an important base to improve the cold tolerance in plants via enhancing the antioxidant machinery.

In higher plants, several lines of evidence suggest that long non-coding RNAs (lncRNAs) may play important roles in the regulation of various biological processes by regulating gene expression. In this study, we identified a total of 521 lncRNAs, classified as intergenic, intronic, sense, and natural antisense lncRNAs, from RNA-seq data of drought-exposed tomato leaves. A further 244 drought-responsive tomato lncRNAs were predicted to be putative targets of 92 tomato miRNAs. Expression pattern and preliminary functional analysis of potential mRNA targets suggested that drought-responsive tomato lncRNAs play important roles in a variety of biological processes via lncRNA–mRNA co-expression. Taken together, these data present a comprehensive view of drought-responsive tomato lncRNAs that serve as a starting point for understanding the role of long intergenic non-coding RNAs in the regulatory mechanisms underlying drought responses in crops.

Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate the potential of a snapshot-based visible-near infrared multispectral imaging system for detecting the early stage of heat injury during the growth of Chinese cabbage. Two classification models based on partial least squares-discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) were developed to identify heat stress. Various vegetation indices (VIs), including the normalized difference vegetation index (NDVI), red-edge ratio (RE/R), and photochemical reflectance index (PRI), which are closely related to plant heat stress, were acquired from sample images, and their values were compared with the developed models for the evaluation of their discriminant performance of developed models. The highest classification accuracies for LS-SVM, PLS-DA, NDVI, RE/R, and PRI were 93.6%, 92.4%, 72.5%, 69.6%, and 58.1%, respectively, without false-positive errors. Among these methods for identifying plant heat stress, the developed LS-SVM and PLS-DA models showed more reliable discriminant performance than the traditional VIs. This clearly demonstrates that the developed models are much more effective and efficient predictive tools for detecting heat stress in Chinese cabbage in the early stages compared to conventional methods. The developed technique shows promise as an accurate and cost-effective screening tool for rapid identification of heat stress in Chinese cabbage.

The aim of this study was to develop and validate growth and photosynthetic models of Kimchi cabbages under extreme temperature conditions at different growth stages. Kimchi cabbage plants were subjected to low and high air temperatures 7–10 days after transplanting (DAT) and 40–43 DAT using extreme weather simulators. Except during these periods, the air temperature, relative humidity, solar radiation, and precipitation were set according to previous meteorological data. The experiments were performed over two years: in the first year, data were used to develop the models; the second-year experimental data were used for validation. The growth parameters and relative growth rate of Kimchi cabbage decreased due to low and high air temperature treatments. Photosynthetic CO2 response curves, which were measured using a portable gas exchange system, were used to calculate three biochemical parameters from measured data: photochemical efficiency, carboxylation conductance, and dark respiration. These parameters were used to develop the photosynthetic models (modified Thornley’s models) representing predictions of net photosynthetic rate by CO2 concentration and growth stage. The simulated photosynthetic rate with extreme high temperature treatment (35/31 °C) was 19.7 μmol m−2 s−1 which was evaluated approximately 3% deduction compared with control. Results of this study indicate that the growth and photosynthetic models developed here could be applied to evaluate retarded growth and net photosynthetic rate under extreme temperature conditions.

No abstract