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<jats:p>Salinity-induced stress is widely considered a main plant-growth-limiting factor. The positive effects of melatonin in modulating abiotic stresses have led this hormone to be referred to as a growth regulator in plants. This study aims to show how melatonin protects fenugreek against the negative effects of salt stress. Different amounts of melatonin (30, 60, and 90 ppm), salinity stress (150 mM and 300 mM), and the use of both salinity and melatonin were used as treatments. The results showed that applying different melatonin levels to salinity-treated fenugreek plants effectively prevented the degradation of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid contents compared with salinity treatment without melatonin application. Besides, melatonin increases the biosynthesis of enzymatic and non-enzymatic antioxidants, thereby adjusting the content of reactive oxygen species, free radicals, electrolyte leakage, and malondialdehyde content. It was observed that applying melatonin increased the activity of potassium-carrying channels leading to the maintenance of ionic homeostasis and increased intracellular water content under salinity stress. The results revealed that melatonin activates the defense signaling pathways in fenugreek through the nitric oxide, auxin, and abscisic acid-dependent pathways. Melatonin, in a similar vein, increased the expression of genes involved in the biosynthesis pathway of diosgenin, a highly important steroidal sapogenin in medical and food industries, and hence the diosgenin content. When 150 mM salinity stress and 60 ppm melatonin were coupled, the diosgenin concentration rose by more than 5.5 times compared to the control condition. In conclusion, our findings demonstrate the potential of melatonin to enhance the plant tolerance to salinity stress by stimulating biochemical and physiological changes.</jats:p>

<jats:p>Phosphorus (P) deficiency and aluminum (Al) toxicity often coexist and are two major limiting factors for crop production in acid soils. The purpose of this study was to characterize the function of <jats:italic>GmBBE-like43</jats:italic>, a berberine bridge enzyme-like protein-encoding gene, in soybean (<jats:italic>Glycine max</jats:italic>) adaptation to Al and low P stresses. Present quantitative real-time PCR (qRT-PCR) assays confirmed the phosphate (Pi)-starvation enhanced and Al-stress up-regulated expression pattern of <jats:italic>GmBBE-like43</jats:italic> in soybean roots. Meanwhile, the expression of a <jats:italic>GmBBE-like43-GFP</jats:italic> chimera in both common bean hairy roots and tobacco leaves demonstrated its cell wall localization. Moreover, both transgenic Arabidopsis and soybean hairy roots revealed the function of <jats:italic>GmBBE-like43</jats:italic> in promoting root growth under both Al and low P stresses. <jats:italic>GmBBE-like43</jats:italic>-overexpression also resulted in more H<jats:sub>2</jats:sub>O<jats:sub>2</jats:sub> production on transgenic soybean hairy root surface with oligogalacturonides (OGs) application and antagonized the effects of Al on the expression of two <jats:italic>SAUR-like</jats:italic> genes. Taken together, our results suggest that <jats:italic>GmBBE-like43</jats:italic> might be involved in the soybean's coordinated adaptation to Al toxicity and Pi starvation through modulation of OGs-oxidation in the cell wall.</jats:p>

<jats:p>Microplastics affect plants and soil biota and the processes they drive. However, the legacy effect of microplastics on plant–soil feedbacks is still unknown. To address this, we used soil conditioned from a previous experiment, where <jats:italic>Daucus carota</jats:italic> grew with 12 different microplastic types (conditioning phase). Here, we extracted soil inoculum from those 12 soils and grew during 4 weeks a native <jats:italic>D. carota</jats:italic> and a range-expanding plant species <jats:italic>Calamagrostis epigejos</jats:italic> in soils amended with this inoculum (feedback phase). At harvest, plant biomass and root morphological traits were measured. Films led to positive feedback on shoot mass (higher mass with inoculum from soil conditioned with microplastics than with inoculum from control soil). Films may decrease soil water content in the conditioning phase, potentially reducing the abundance of harmful soil biota, which, with films also promoting mutualist abundance, microbial activity and carbon mineralization, would positively affect plant growth in the feedback phase. Foams and fragments caused positive feedback on shoot mass likely <jats:italic>via</jats:italic> positive effects on soil aeration in the conditioning phase, which could have increased mutualistic biota and soil enzymatic activity, promoting plant growth. By contrast, fibers caused negative feedback on root mass as this microplastic may have increased soil water content in the conditioning phase, promoting the abundance of soil pathogens with negative consequences for root mass. Microplastics had a legacy effect on root traits: <jats:italic>D. carota</jats:italic> had thicker roots probably for promoting mycorrhizal associations, while <jats:italic>C. epigejos</jats:italic> had reduced root diameter probably for diminishing pathogenic infection. Microplastic legacy on soil can be positive or negative depending on the plant species identity and may affect plant biomass primarily <jats:italic>via</jats:italic> root traits. This legacy may contribute to the competitive success of range-expanding species <jats:italic>via</jats:italic> positive effects on root mass (foams) and on shoot mass (PET films). Overall, microplastics depending on their shape and polymer type, affect plant–soil feedbacks.</jats:p>

<jats:p>Plant phenotyping is essential in plant breeding and management. High-throughput data acquisition and automatic phenotypes extraction are common concerns in plant phenotyping. Despite the development of phenotyping platforms and the realization of high-throughput three-dimensional (3D) data acquisition in tall plants, such as maize, handling small-size plants with complex structural features remains a challenge. This study developed a miniaturized shoot phenotyping platform MVS-Pheno V2 focusing on low plant shoots. The platform is an improvement of MVS-Pheno V1 and was developed based on multi-view stereo 3D reconstruction. It has the following four components: Hardware, wireless communication and control, data acquisition system, and data processing system. The hardware sets the rotation on top of the platform, separating plants to be static while rotating. A novel local network was established to realize wireless communication and control; thus, preventing cable twining. The data processing system was developed to calibrate point clouds and extract phenotypes, including plant height, leaf area, projected area, shoot volume, and compactness. This study used three cultivars of wheat shoots at four growth stages to test the performance of the platform. The mean absolute percentage error of point cloud calibration was 0.585%. The squared correlation coefficient <jats:italic>R</jats:italic><jats:sup>2</jats:sup> was 0.9991, 0.9949, and 0.9693 for plant height, leaf length, and leaf width, respectively. The root mean squared error (RMSE) was 0.6996, 0.4531, and 0.1174 cm for plant height, leaf length, and leaf width. The MVS-Pheno V2 platform provides an alternative solution for high-throughput phenotyping of low individual plants and is especially suitable for shoot architecture-related plant breeding and management studies.</jats:p>

<jats:p>Cultivated potato is a vegetatively propagated crop, and most varieties are autotetraploid with high levels of heterozygosity. Reducing the ploidy and breeding potato at the diploid level can increase efficiency for genetic improvement including greater ease of introgression of diploid wild relatives and more efficient use of genomics and markers in selection. More recently, selfing of diploids for generation of inbred lines for F1 hybrid breeding has had a lot of attention in potato. The current study provides genomics resources for nine legacy non-inbred adapted diploid potato clones developed at Agriculture and Agri-Food Canada. <jats:italic>De novo</jats:italic> genome sequence assembly using 10× Genomics and Illumina sequencing technologies show the genome sizes ranged from 712 to 948 Mbp. Structural variation was identified by comparison to two references, the potato DMv6.1 genome and the phased RHv3 genome, and a k-mer based analysis of sequence reads showed the genome heterozygosity range of 1 to 9.04% between clones. A genome-wide approach was taken to scan 5 Mb bins to visualize patterns of heterozygous deleterious alleles. These were found dispersed throughout the genome including regions overlapping segregation distortions. Novel variants of the <jats:italic>StCDF1</jats:italic> gene conferring earliness of tuberization were found among these clones, which all produce tubers under long days. The genomes will be useful tools for genome design for potato breeding.</jats:p>

<jats:p>Soybean [<jats:italic>Glycine max</jats:italic> (L.) Merr.] and cotton (<jats:italic>Gossypium hirsutum</jats:italic> L.) are the major row crops in the USA, and growers are tending toward the twin-row system and irrigation to increase productivity. In a 2-year study (2018 and 2019), we examined the gas exchange and chlorophyll fluorescence parameters to better understand the regulatory and adaptive mechanisms of the photosynthetic components of cotton and soybean grown under varying levels of irrigations and planting geometries in a split-plot experiment. The main plots were three irrigation regimes: (i) all furrows irrigation (AFI), (ii) alternate or skipped furrow irrigation (SFI), and iii) no irrigation or rainfed (RF), and the subplots were two planting patterns, single-row (SR) and twin-row (TR). The light response curves at vegetative and reproductive phases revealed lower photosynthesis rates in the RF crops than in AFI and SFI. A higher decrease was noticed in RF soybean for light compensation point (LCP) and light saturation point (LSP) than that of RF cotton. The decrease in the maximum assimilation rate (Amax) was higher in soybean than cotton. A decrease of 12 and 17% in Amax was observed in RF soybean while the decrease is limited to 9 and 6% in RF cotton during the 2018 and 2019 seasons, respectively. Both stomatal conductance (gs) and transpiration (E) declined under RF. The moisture deficit stress resulted in enhanced operating quantum efficiency of PSII photochemistry (ΦPSII), which is probably due to increased photorespiration. The non-photochemical quenching (NPQ), a measure of thermal dissipation of absorbed light energy, and quantum efficiency of dissipation by down-regulation (ΦNPQ) increased significantly in both crops up to 50% under RF conditions. The photochemical quenching declined by 28% in soybean and 26% in cotton. It appears soybean preferentially uses non-photochemical energy dissipation while cotton uses elevated electron transport rate (ETR) under RF conditions for light energy utilization. No significant differences among SR and TR systems were observed for LCP, LSP, AQE, Amax, gs, E, ETR, and various chlorophyll fluorescence parameters. This study reveals preferential use of non-photochemical energy dissipation in soybean while cotton uses both photochemical and non-photochemical energy dissipation to protect PSI and PSII centers and ETR, although they fall under C3 species when exposed to moisture limited environments.</jats:p>

<jats:p>Glyphosate is one of the most widely used non-selective herbicides, and the creation of glyphosate-resistant cultivars solves the problem of limited spraying area. Therefore, it is of great significance to quickly identify resistant cultivars without destruction during the development of superior cultivars. This work took maize seedlings as the experimental object, and the spectral indices of leaves were calculated to construct a model with good robustness that could be used in different experiments. Compared with no transfer strategies, transferability of support vector machine learning model was improved by randomly selecting 14% of source domain from target domain to train and applying transfer component analysis algorithm, the accuracy on target domain reached 83% (increased by 71%), recall increased from 10 to 100%, and F1-score increased from 0.17 to 0.86. The overall results showed that both transfer component analysis algorithm and updating source domain could improve the transferability of model among experiments, and these two transfer strategies could complement each other’s advantages to achieve the best classification performance. Therefore, this work is beneficial to timely understanding of the physiological status of plants, identifying glyphosate resistant cultivars, and ultimately provides theoretical basis and technical support for new cultivar creation and high-throughput selection.</jats:p>

<jats:p>Across-season biomass assessment is crucial in the cultivar selection process to accurately evaluate the yield performance of lines under different growing conditions. However, it has been difficult to have an accurate, reliable, and repeated fresh biomass (FM) estimation of large populations of plants in the field without destructive harvesting, which incurs significant labor and operation costs. Sensor-based phenotyping platforms have advanced in the data collection of structural and vegetative information of plants, but the developed prediction models are still limited by low correlations at different growth stages and seasons. In this study, our objective was to develop and validate the global prediction models for across-season harvested fresh biomass (FM) yield based on the ground- and air-based sensor data including ground-based LiDAR, ground-based ultrasonic, and air-based multispectral camera to extract LiDAR plant volume (LV), LiDAR point density (LV_Den), height, and Normalized Difference Vegetative Index (NDVI). The study was conducted in a row-plot field trial with 480 rows (3 rows in a plot per cultivar) throughout the whole 2020 growing season up to the reproductive stage. We evaluated the performance of each plant parameter, their relationship, and the best subset prediction models using statistical stepwise selection at the row and plot levels through the seasonal and combined seasonal datasets. The best performing model: <jats:inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>F</mml:mi><mml:mi>M</mml:mi><mml:mo>~</mml:mo><mml:mi>L</mml:mi><mml:mi>V</mml:mi><mml:mo>∗</mml:mo><mml:mi>L</mml:mi><mml:mi>V</mml:mi><mml:mo>_</mml:mo><mml:mi>D</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mo>∗</mml:mo><mml:mi>N</mml:mi><mml:mi>D</mml:mi><mml:mi>V</mml:mi><mml:mi>I</mml:mi></mml:mrow></mml:math></jats:inline-formula> had a determination of coefficient <jats:italic>R</jats:italic><jats:sup>2</jats:sup> of at least 0.9 in vegetative stages and 0.8 in the reproductive stage. Similar results can be achieved in a simpler model with just two LiDAR variables—<jats:inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>F</mml:mi><mml:mi>M</mml:mi><mml:mo>~</mml:mo><mml:mi>L</mml:mi><mml:mi>V</mml:mi><mml:mo>∗</mml:mo><mml:mi>L</mml:mi><mml:mi>V</mml:mi><mml:mo>_</mml:mo><mml:mi>D</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi></mml:mrow></mml:math></jats:inline-formula>. In addition, LV and LV_Den showed a robust correlation with FM on their own over seasons and growth stages, while NDVI only performed well in some seasons. The simpler model based on only LiDAR data can be widely applied over season without the need of additional sensor data and may thus make the in-field across-season biomass assessment more feasible and practical for fast and cost-effective development of higher biomass yield cultivars.</jats:p>

<jats:p>Gluten proteins are responsible for the unique viscoelastic properties of wheat dough, but they also trigger the immune response in celiac disease patients. RNA interference (RNAi) wheat lines with strongly silenced gliadins were obtained to reduce the immunogenic response of wheat. The E82 line presents the highest reduction of gluten, but other grain proteins increased, maintaining a total nitrogen content comparable to that of the wild type. To better understand the regulatory mechanisms in response to gliadin silencing, we carried out a transcriptomic analysis of grain and leaf tissues of the E82 line during grain filling. A network of candidate transcription factors (TFs) that regulates the synthesis of the seed storage proteins (SSPs), α-amylase/trypsin inhibitors, lipid transfer proteins, serpins, and starch in the grain was obtained. Moreover, there were a high number of differentially expressed genes in the leaf of E82, where processes such as nutrient availability and transport were enriched. The source-sink communication between leaf and grain showed that many down-regulated genes were related to protease activity, amino acid and sugar metabolism, and their transport. In the leaf, specific proline transporters and lysine-histidine transporters were down- and up-regulated, respectively. Overall, the silencing of gliadins in the RNAi line is compensated mainly with lysine-rich globulins, which are not related to the proposed candidate network of TFs, suggesting that these proteins are regulated independently of the other SSPs. Results reported here can explain the protein compensation mechanisms and contribute to decipher the complex TF network operating during grain filling.</jats:p>

<jats:p>The plant-specific module of calcineurin B-like proteins (CBLs) and CBL-interacting protein kinases (CIPKs) play a crucial role in plant adaptation to different biotic and abiotic stresses in various plant species. Despite the importance of the CBL-CIPK module in regulating plant salt tolerance, few halophyte CIPK orthologs have been studied. We identified <jats:italic>NbCIPK25</jats:italic> in the halophyte <jats:italic>Nitraria billardieri</jats:italic> as a salt-responsive gene that may improve salt tolerance in glycophytes. Sequence analyses indicated that <jats:italic>NbCIPK25</jats:italic> is a typical CIPK family member with a conserved NAF motif, which contains the amino acids: asparagine, alanine, and phenylalanine. <jats:italic>NbCIPK25</jats:italic> overexpression in salt-stressed transgenic <jats:italic>Arabidopsis</jats:italic> seedlings resulted in enhanced tolerance to salinity, a higher survival rate, longer newly grown roots, more root meristem cells, and less damaged root cells in comparison to wild-type (WT) plants. H<jats:sub>2</jats:sub>O<jats:sub>2</jats:sub> accumulation and malondialdehyde (MDA) content were both deceased in <jats:italic>NbCIPK25</jats:italic>-transgenic plants under salt treatment. Furthermore, their proline content, an important factor for scavenging reactive oxygen species, accumulated at a significantly higher level. In concordance, the transcription of genes related to proline accumulation was positively regulated in transgenic plants under salt condition. Finally, we observed a stronger auxin response in salt-treated transgenic roots. These results provide evidence for <jats:italic>NbCIPK25</jats:italic> improving salt tolerance by mediating scavenging of reactive oxygen species, thereby protecting cells from oxidation and maintaining plant development under salt stress. These findings suggest the potential application of salt-responsive <jats:italic>NbCIPK25</jats:italic> for cultivating glycophytes with a higher salt tolerance through genetic engineering.</jats:p>