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<jats:p>Melatonin is an important, multifunctional protective agent against a variety of abiotic and biotic stressors in plants. Caffeic acid O-methyltransferase (COMT) catalyzes the last step of melatonin synthesis in plants and reportedly participates in the regulation of stress response and tolerance. However, few studies have reported its function in melatonin-mediated drought resistance. In this study, <jats:italic>CrCOMT</jats:italic> was identified and was strongly induced by drought stress in <jats:italic>Carex rigescens</jats:italic>. <jats:italic>CrCOMT</jats:italic> overexpression in transgenic tobacco increased tolerance to drought stress with high levels of seed germination, relative water content, and survival rates. <jats:italic>CrCOMT</jats:italic> overexpression in tobacco improved membrane stability, and plants exhibited lower relative electrolytic leakage and malondialdehyde content, as well as higher photochemical efficiency than the wildtype (WT) under drought stress. The transgenic plants also had higher levels of proline accumulation and antioxidant enzyme activity, which decreased oxidative stress damage due to reactive oxygen species (ROS) hyperaccumulation under drought stress. The transcription of drought stress response and ROS scavenging genes was significantly higher in the <jats:italic>CrCOMT</jats:italic> overexpression plants than in the WT plants. In addition, <jats:italic>CrCOMT</jats:italic> transgenic tobacco plants exhibited higher melatonin content under drought stress conditions. Exogenous melatonin was applied to <jats:italic>C. rigescens</jats:italic> under drought stress to confirm the function of melatonin in mediating drought tolerance; the relative water content and proline content were higher, and the relative electrolytic leakage was lower in melatonin-treated <jats:italic>C. rigescens</jats:italic> than in the untreated plants. In summary, these results show that <jats:italic>CrCOMT</jats:italic> plays a positive role in plant drought stress tolerance by regulating endogenous melatonin content.</jats:p>

<jats:p>Development of an efficient and eco-friendly technique to break tuber dormancy in potato (<jats:italic>Solanum tuberosum</jats:italic> L.) is highly demanded due to the production of two or more crops annually. Several physiological and hormonal changes have been found to be related to the breaking of tuber dormancy; however, their consistency with genotypes and different protocols have not been well clarified. This study aims to evaluate the effectiveness of four dormancy-breaking methods, that is, plant growth regulator (PGR) dipping in 30, 60, or 90 mgL<jats:sup>−1</jats:sup> benzyl amino purine (BAP) and 10, 20, or 30 mgL<jats:sup>−1</jats:sup> gibberellic acids (GA3) alone and in the combination of optimized concentrations; electric current application at 20, 40, 60, or 80 Vs; cold pre-treatment at 2, 4, or 6 °C; irradiation at 1, 1.5, 2, 2.5, 3, or 3.5 kGy. In addition, changes in endogenous levels of abscisic acid (ABA), zeatin (ZT), and gibberellin A<jats:sub>1</jats:sub> (GA<jats:sub>1</jats:sub>) in six potato genotypes after subjecting to these methods were investigated. Overall, the highest effective method for dormancy duration was the PGR application which shortened the duration by 18 days, followed by electric current (13 days), cold pre-treatment (9 days), and then irradiation (7 days). The solution of 60 mgL<jats:sup>−1</jats:sup> BAP significantly reduced the dormancy duration in all genotypes but did not have a significant effect on the sprout length. While 20 mgL<jats:sup>−1</jats:sup> GA<jats:sub>3</jats:sub> produced maximum sprout length with a non-significant effect on dormancy duration. The genotype × PGR interaction for dormancy duration was more pronounced in short- and medium-term dormancy genotypes than in long-term dormancy genotypes. The genotypes displayed a significant positive correlation between dormancy duration and ABA levels but exhibited a negative correlation between dormancy duration and ZT as well as GA<jats:sub>1</jats:sub> levels. From the first to the third week of storage, ABA was decreased in tubers while, however, ZT and GA<jats:sub>1</jats:sub> were increased. The obtained results could be useful for the postharvest storage of potato tuber and the related field of physiological investigation in future.</jats:p>

<jats:p>Terpenoids constitute one of the largest and most diverse classes of plant metabolites. While some terpenoids are involved in essential plant processes such as photosynthesis, respiration, growth, and development, others are specialized metabolites playing roles in the interaction of plants with their biotic and abiotic environment. Due to the distinct functions and properties of specific terpenoid compounds, there is a growing interest to introduce or modify their production in plants by metabolic engineering for agricultural, pharmaceutical, or industrial applications. The MVA and MEP pathways and the prenyltransferases providing the general precursors for terpenoid formation, as well as the enzymes of the various downstream metabolic pathways leading to the formation of different groups of terpenoid compounds have been characterized in detail in plants. In contrast, the molecular mechanisms directing the metabolic flux of precursors specifically toward one of several potentially competing terpenoid biosynthetic pathways are still not well understood. The formation of metabolons, multi-protein complexes composed of enzymes catalyzing sequential reactions of a metabolic pathway, provides a promising concept to explain the metabolic channeling that appears to occur in the complex terpenoid biosynthetic network of plants. Here we provide an overview about examples of potential metabolons involved in plant terpenoid metabolism that have been recently characterized and the first attempts to utilize metabolic channeling in terpenoid metabolic engineering. In addition, we discuss the gaps in our current knowledge and in consequence the need for future basic and applied research.</jats:p>

<jats:p>Geitonogamy is inevitable in hermaphrodite and monecious. Even for self-incompatible species, the negative effects of self-pollen are unavoidable when geitonogamous or self-mating occurs. However, the influence of self-pollen on consecutive development of flowers (e.g., fruiting and seeding) was seldom evaluated. Here, the self-incompatible monecious species, <jats:italic>Akebia quinata</jats:italic>, was used to estimate the influence of self-pollen deposition. We evaluated the extent of pollen limitation and geitonogamous mating under natural conditions by count of stigmatic pollen load and pollen tracking experiment. Hand pollination with different amount and combinations of self vs. cross pollen grains was applied to detect the response of fruit and seed set. The results showed that geitonogamy and pollen limitation occurred under natural conditions in <jats:italic>A. quinata</jats:italic>. Carpel numbers, ratio of self- and cross-pollen, and the interactive effect of ratio of self- and cross-pollen and total mixed pollen numbers, and not total pollen grain number, determined the effect of self-pollen on female reproductive success. The effect of self-pollen depended on its intensity. In general, the transfer of self-pollen significantly affected young fruit set. However, a little self-pollen together with cross-pollen did not reduce young fruit production. Although self-incompatible plants have evolved physiological mechanisms that reduce self-fertilization, our results provide new insights into the effects of self-pollen and the adaptive significance of self-incompatible monecious species.</jats:p>

<jats:p>As a promising method, unmanned aerial vehicle (UAV) multispectral remote sensing (RS) has been extensively studied in precision agriculture. However, there are numerous problems to be solved in the data acquisition and processing, which limit its application. In this study, the Micro-MCA12 camera was used to obtain images at different altitudes. The piecewise empirical line (PEL) method suitable for predicting the reflectance of different ground objects was proposed to accurately acquire the reflectance of multi-altitude images by comparing the performance of the conventional methods. Several commonly utilized vegetation indices (VIs) were computed to estimate the rice growth parameters and yield. Then the rice growth monitoring and yield prediction were implemented to verify and evaluate the effects of radiometric calibration methods (RCMs) and UAV flying altitudes (UAV-FAs). The results show that the variation trends of reflectance and VIs are significantly different due to the change in component proportion observed at different altitudes. Except for the milking stage, the reflectance and VIs in other periods fluctuated greatly in the first 100 m and remained stable thereafter. This phenomenon was determined by the field of view of the sensor and the characteristic of the ground object. The selection of an appropriate calibration method was essential as a result of the marked differences in the rice phenotypes estimation accuracy based on different RCMs. There were pronounced differences in the accuracy of rice growth monitoring and yield estimation based on the 50 and 100 m-based variables, and the altitudes above 100 m had no notable effect on the results. This study can provide a reference for the application of UAV RS technology in precision agriculture and the accurate acquisition of crop phenotypes.</jats:p>

<jats:p>Citrus fruits are susceptible to fungal infection after harvest. To reduce the economic loss, it is necessary to reject the infected citrus fruit before storage and transportation. However, the infected area in the early stage of decay is almost invisible on the fruit surface, so the detection of early decayed citrus is very challenging. In this study, a structured-illumination reflectance imaging (SIRI) system combined with a visible light-emitting diode (LED) lamp and a monochrome camera was developed to detect early fungal infection in oranges. Under sinusoidal modulation illumination with spatial frequencies of 0.05, 0.15, and 0.25 cycles mm<jats:sup>–1</jats:sup>, three-phase-shifted images with phase offsets of − 2π/3, 0, and 2π/3 were acquired for each spatial frequency. The direct component (DC) and alternating component (AC) images were then recovered by image demodulation using a three-phase-shifting approach. Compared with the DC image, the decayed area can be clearly identified in the AC image and RT image (AC/DC). The optimal spatial frequency was determined by analyzing the AC image and pixel intensity distribution. Based on the texture features extracted from DC, AC, and RT images, four kinds of classification models including partial least square discriminant analysis (PLS-DA), support vector machine (SVM), least squares-support vector machine (LS-SVM), and k-nearest neighbor (KNN) were established to detect the infected oranges, respectively. Model optimization was also performed by extracting important texture features. Compared to all models, the PLS-DA model developed based on eight texture features of RT images achieved the optimal classification accuracy of 96.4%. This study showed for the first time that the proposed SIRI system combined with appropriate texture features and classification model can realize the early detection of decayed oranges.</jats:p>

<jats:p>Plants dynamically manipulate their gene expression in acclimation to the challenging environment. Hereinto, the histone methylation tunes the gene transcription <jats:italic>via</jats:italic> modulation of the chromatin accessibility to transcription machinery. Osmotic stress, which is caused by water deprivation or high concentration of ions, can trigger remarkable changes in histone methylation landscape and genome-wide reprogramming of transcription. However, the dynamic regulation of genes, especially how stress-inducible genes are timely epi-regulated by histone methylation remains largely unclear. In this review, recent findings on the interaction between histone (de)methylation and osmotic stress were summarized, with emphasis on the effects on histone methylation profiles imposed by stress and how histone methylation works to optimize the performance of plants under stress.</jats:p>

<jats:p>Fruit and vegetable picking robots are affected by the complex orchard environment, resulting in poor recognition and segmentation of target fruits by the vision system. The orchard environment is complex and changeable. For example, the change of light intensity will lead to the unclear surface characteristics of the target fruit; the target fruits are easy to overlap with each other and blocked by branches and leaves, which makes the shape of the fruits incomplete and difficult to accurately identify and segment one by one. Aiming at various difficulties in complex orchard environment, a two-stage instance segmentation method based on the optimized mask region convolutional neural network (mask RCNN) was proposed. The new model proposed to apply the lightweight backbone network MobileNetv3, which not only speeds up the model but also greatly improves the accuracy of the model and meets the storage resource requirements of the mobile robot. To further improve the segmentation quality of the model, the boundary patch refinement (BPR) post-processing module is added to the new model to optimize the rough mask boundaries of the model output to reduce the error pixels. The new model has a high-precision recognition rate and an efficient segmentation strategy, which improves the robustness and stability of the model. This study validates the effect of the new model using the persimmon dataset. The optimized mask RCNN achieved mean average precision (mAP) and mean average recall (mAR) of 76.3 and 81.1%, respectively, which are 3.1 and 3.7% improvement over the baseline mask RCNN, respectively. The new model is experimentally proven to bring higher accuracy and segmentation quality and can be widely deployed in smart agriculture.</jats:p>

<jats:p>Medicinal plants have been used to cure human diseases since decades. <jats:italic>Silybum marianum</jats:italic>, a medicinal plant, is regarded as a source of secondary metabolites with therapeutic value against liver diseases and diabetes. The present study was conducted to enrich the production of secondary metabolites in the vegetative parts of <jats:italic>Silybum marianum</jats:italic> using elicitation strategy in hydroponic system with different elicitors. The elicitors of fungus <jats:italic>Aspergillus niger</jats:italic> (0.2 g/L), methyl jasmonate (MeJA) (100 μM) and silver nanoparticles (AgNPs) (1 ppm) were added in hydroponic medium, individually and in combination form to the 15 days old plant. The elicitor-treated plants were harvested at different time points (24–144 h; increment 24 h) and their biochemical parameters like phenolics, flavonoids, nitric oxide (NO), and superoxide dismutase (SOD) were analyzed. The results showed hyper-accumulation of these biochemical contents, especially in response to MeJA (100 μM), followed by AgNPs (1 ppm) and co-treatment of AgNPs (1 ppm) with other elicitors. The results revealed that the treatment with MeJA (100 μM) exhibited the highest flavonoid (304 μg g<jats:sup>–1</jats:sup>), phenolic (372 μg g<jats:sup>–1</jats:sup>), and SOD (16.2 U g<jats:sup>–1</jats:sup>) contents. For NO levels, the maximum value of 198.6 nmole g<jats:sup>–1</jats:sup> was achieved in response to the treatment with MeJA + Green synthesized AgNPs (100 μM + 1 ppm). Our findings depicted an enhanced production of medicinally important plant secondary metabolites and antioxidants; hence, the method applied in this study can play a significant role to improve therapeutic values of the plants.</jats:p>

<jats:p>Predicting the germination behavior of parthenium weed against different conditions of temperature and osmotic stress is helpful for studying the growth and development history of parthenium in different ecological contexts. Sustainable weed control strategies based on population-based threshold (PBT) models are profitable tools for crop planting date, herbicide application, and tillage operation time. To predict the emergence of parthenium by using thermal time (TT), hydrotime (HT), and hydrothermal time (HTT) analyses, seeds were exposed to varying constant temperatures (5, 10, 15, 20, 25, 30, 35, and 40°C) and water potentials (− 0.25, − 0.5, − 0.75, and − 1.0 MPa) under a controlled environment. Parthenium seeds showed better responses in terms of higher germination percentage and lower germination time at 20 and 25°C. The use of the germination modeling approach proposed the base temperature (7.2°C), optimum temperature (20°C), and ceiling temperature (42.8°C) for this weed. Moreover, germination behavior was also studied at different water potentials under different temperature regimes (10, 20, and 30°C). The HTT model predicted higher germination percentages (82.8 and 54.8%) of parthenium seeds at water potentials from 0 to −0.25 MPa, respectively, under a temperature of 20°C, and also identified a base water potential (Ψb<jats:sub>(50</jats:sub>) of − 0.54 MPa for germination. In conclusion, the use of the HTT modeling approach is helpful for predicting the emergence response of parthenium in a changing climate and ultimately supportive in time scheduling of parthenium weed management in cropping systems.</jats:p>