Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater-groundwater within or near the crop rooting zone-as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

Time-Course Analysis and Transcriptomic Identification of a Group III ERF CmTINY2 Involved in Waterlogging Tolerance in Chrysanthemums × morifolium Ramat

'Hangju' is a variety of Chrysanthemum × morifolium Ramat. with both edible and medicinal value, cultivated as a traditional Chinese medicine for four centuries. The cultivation of 'Hangju' is currently at risk due to waterlogging, yet there is a lack of comprehensive understanding regarding its response to waterlogging stress. This study compared the waterlogging-tolerant 'Hangju' variety Enhanced Waterlogging Tolerance (EWT) with the waterlogging-sensitive variety CK ('zaoxiaoyangju'). EWT exhibited a more developed aeration tissue structure and demonstrated rapid growth regarding the adventitious roots following waterlogging. The time-course transcriptome analysis indicated that EWT could swiftly adjust the expression of the genes involved in the energy metabolism signaling pathways to acclimate to the waterlogged environment. Through WGCNA analysis, we identified Integrase-Type DNA-Binding Protein (CmTINY2) as a key factor in regulating the waterlogging tolerance in EWT. CmTINY2, a transcription factor belonging to the ethylene-responsive factor (ERF) subfamily III, operated within the nucleus and activated downstream gene expression. Its role in enhancing the waterlogging tolerance might be linked to the control of the stomatal aperture via the Ethylene-Responsive Element (ERE) gene. In summary, our research elucidated that the waterlogging tolerance displayed by EWT is a result of a combination of the morphological structure and molecular regulatory mechanisms. Furthermore, the study of the functions of CmTINY2 from ERF subfamily III also broadened our knowledge of the role of the ERF genes in the waterlogging signaling pathways.

6-BA Reduced Yield Loss under Waterlogging Stress by Regulating the Phenylpropanoid Pathway in Wheat

Waterlogging stress causes substantial destruction to plant growth and production under climatic fluctuations globally. Plants hormones have been widely explored in numerous crops, displaying an imperative role in crop defense and growth mechanism. However, there is a paucity of research on the subject of plant hormones regulating waterlogging stress responses in wheat crop. In this study, we clarified the role of 6-BA in waterlogging stress through inducing phenylpropanoid biosynthesis in wheat. The application of 6-BA (6-benzyladenine) enhanced the growth and development of wheat plants under waterlogging stress, which was accompanied by reduced electrolyte leakage, high chlorophyll, and soluble sugar content. ROS scavenging was also enhanced by 6-BA, resulting in reduced MDA and H2O2 accumulation and amplified antioxidant enzyme activities. Additionally, under the effect of 6-BA, the acceleration of lignin content and accumulation in the cell walls of wheat tissues, along with the activation of PAL (phenylalanine ammonia lyase), TAL (tyrosine ammonia lyase), and 4CL (4-hydroxycinnamate CoA ligase) activities and the increase in the level of transcription of the TaPAL and Ta4CL genes, were observed under waterlogging stress. Also, 6-BA improved the root growth system under waterlogging stress conditions. Further qPCR analysis revealed increased auxin signaling (TaPR1) in 6-BA-treated plants under waterlogging stress that was consistent with the induction of endogenous IAA hormone content under waterlogging stress conditions. Here, 6-BA also reduced yield loss, as compared to control plants. Thus, the obtained data suggested that, under the application of 6-BA, phenylpropanoid metabolism (i.e., lignin) was stimulated, playing a significant role in reducing the negative effects of waterlogging stress on yield, as evinced by the improved plant growth parameters.

Moderately reducing N input to mitigate heat stress in maize

In a warming climate, high temperature stress greatly threatens crop yields. Maize is critical to food security, but frequent extreme heat events coincide temporally and spatially with the period of kernel number determination (e.g., flowering stage), greatly limiting maize yields. In this context, how to increase or at least maintain maize yield has become more important. Nitrogen fertilizer (N) is widely used to improve maize yields, but its effect in heat stress is unclear. For this, we collected 1536 pairs of comparisons from 113 studies concerning N conducted in the past 20 years over China. We classified the data into two groups - without high temperature stress (NHT) and with high temperature stress during the critical period for maize kernel number determination (HT) - based on the national meteorological data. We comprehensively evaluated N effects on grain yield under HT and NHT using meta-analysis. The effect of N on maize yield became significantly smaller in HT than that in NHT. In NHT, soil characteristics, crop management practices, and climatic conditions all significantly affected N effects on maize yield, but in HT, only a few factors such as soil organic matter and mean annual precipitation significantly affected N effects. Hence, it is difficult to improve N effect by improving soil characteristics and crop management when meeting with high temperature stress during flowering. On average, N effect increased with increased N input, but there were respective N input thresholds in NHT and HT, beyond which N effects on maize yield remained stable. According to the thresholds, it is speculated that moderately reducing N input (~20 %) likely increased high temperature tolerance of maize during flowering. These findings have important implications for the optimization of N management under a warming climate.

Pathways to identify and reduce uncertainties in agricultural climate impact assessments

Both climate and impact models are essential for understanding and quantifying the impact of climate change on agricultural productivity. Multi-model ensembles have highlighted considerable uncertainties in these assessments, yet a systematic approach to quantify these uncertainties is lacking. We propose a standardized approach to attribute uncertainties in multi-model ensemble studies, based on insights from the Agricultural Model Intercomparison and Improvement Project. We find that crop model processes are the primary source of uncertainty in agricultural projections (over 50%), excluding unquantified hidden uncertainty that is not explicitly measured within the analyses. We propose multidimensional pathways to reduce uncertainty in climate change impact assessments.

Prediction of wheat SPAD using integrated multispectral and support vector machines

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69-0.79, RMSE was 2.30-12.94, and RE was 0.10%-1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Comprehensive Assessment of the Effect of Multi-Cropping on Agroecosystems

Multi-cropping is becoming an increasingly popular technique in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility loss, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensively assessing the impact of multi-cropping intensity on agroecosystems is a new and still under-researched approach that can provide a better understanding of the impact of individual indicators on the overall functioning of biodiverse agroecosystems. Data from a stationary field experiment using multi-cropping at the Vytautas Magnus University Experimental Station between 2020 and 2022 were used to carry out this study. The study included maize, hemp, and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these crops on the agroecosystem, the interrelationships between the main indicators, and the strength of their effects. It was found that the ternary maize-hemp-faba bean crop had the most positive effect on the agroecosystem. The effectiveness of other crops was 2 to 35% less. The lowest value was calculated for the maize-faba bean crop.

Transcriptome and metabolome analyses reveal molecular insights into waterlogging tolerance in Barley

Waterlogging stress is one of the major abiotic stresses affecting the productivity and quality of many crops worldwide. However, the mechanisms of waterlogging tolerance are still elusive in barley. In this study, we identify key differentially expressed genes (DEGs) and differential metabolites (DM) that mediate distinct waterlogging tolerance strategies in leaf and root of two barley varieties with contrasting waterlogging tolerance under different waterlogging treatments. Transcriptome profiling revealed that the response of roots was more distinct than that of leaves in both varieties, in which the number of downregulated genes in roots was 7.41-fold higher than that in leaves of waterlogging sensitive variety after 72 h of waterlogging stress. We also found the number of waterlogging stress-induced upregulated DEGs in the waterlogging tolerant variety was higher than that of the waterlogging sensitive variety in both leaves and roots in 1 h and 72 h treatment. This suggested the waterlogging tolerant variety may respond more quickly to waterlogging stress. Meanwhile, phenylpropanoid biosynthesis pathway was identified to play critical roles in waterlogging tolerant variety by improving cell wall biogenesis and peroxidase activity through DEGs such as Peroxidase (PERs) and Cinnamoyl-CoA reductases (CCRs) to improve resistance to waterlogging. Based on metabolomic and transcriptomic analysis, we found the waterlogging tolerant variety can better alleviate the energy deficiency via higher sugar content, reduced lactate accumulation, and improved ethanol fermentation activity compared to the waterlogging sensitive variety. In summary, our results provide waterlogging tolerance strategies in barley to guide the development of elite genetic resources towards waterlogging-tolerant crop varieties.

The potential of proline as a key metabolite to design real-time plant water deficit and low-light stress detector in ornamental plants

Nowadays, people are interested to use plants, especially air-purifying plants, in residential and other indoor settings to purify indoor air and increase the green area in the building. In this study, we investigated the effect of water deficit and low light intensity on the physiology and biochemistry of popular ornamental plants, including Sansevieria trifasciata, Episcia cupreata and Epipremnum aureum. Plants were grown under low light intensity in the range of 10-15 μmol quantum m-2 s-1 and 3 days of water deficit. The results showed that these three ornamental plants responded to water deficit with different pathways. Metabolomic analysis indicated that water deficit affected Episcia cupreata and Epipremnum aureum by inducing a 1.5- to 3-fold increase of proline and a 1.1- to 1.6-fold increase in abscisic acid compared to well-watered conditions, which led to hydrogen peroxide accumulation. This resulted in a reduction of stomatal conductance, photosynthesis rate and transpiration. Sansevieria trifasciata responded to water deficit by significantly increasing gibberellin by around 2.8-fold compared to well-watered plants and proline contents by around 4-fold, while stomatal conductance, photosynthesis rate and transpiration were maintained. Notably, proline accumulation under water deficit stress could be attributed to both gibberellic acid and abscisic acid, depending on plant species. Therefore, the enhancement of proline accumulation in ornamental plants under water deficit could be detected early from day 3 after water deficit conditions, and this compound can be used as a key compound for real-time biosensor development in detecting plant stress under water deficit in a future study.

Unraveling Key Factors for Hypoxia Tolerance in Contrasting Varieties of Cotton Rose by Comparative Morpho-physiological and Transcriptome Analysis

The cotton rose (Hibiscus mutabilis) is a plant species commonly found in tropical and subtropical regions. It is remarkably resilient to waterlogging stress; however, the underlying mechanism behind this trait is yet unknown. This study used hypoxia-tolerant "Danbanhong" (DBH) and more hypoxia-sensitive "Yurui" (YR) genotypes and compared their morpho-physiological and transcriptional responses to hypoxic conditions. Notably, DBH had a higher number of adventitious roots (20.3) compared to YR (10.0), with longer adventitious roots in DBH (18.3 cm) than in YR (11.2 cm). Furthermore, the formation of aerenchyma was 3-fold greater in DBH compared to YR. Transcriptomic analysis revealed that DBH had more rapid transcriptional responses to hypoxia than YR. Identification of a greater number of differentially expressed genes (DEGs) for aerenchyma, adventitious root formation and development, and energy metabolism in DBH supported that DBH had better morphological and transcriptional adaptation than YR. DEG functional enrichment analysis indicated the involvement of variety-specific biological processes in adaption to hypoxia. Plant hormone signaling transduction, MAPK signaling pathway and carbon metabolism played more pronounced roles in DBH, whereas the ribosome genes were specifically induced in YR. These results show that effective multilevel coordination of adventitious root development and aerenchyma, in conjunction with plant hormone signaling and carbon metabolism, is required for increased hypoxia tolerance. This study provides new insights into the characterization of morpho-physiological and transcriptional responses to hypoxia in H. mutabilis, shedding light on the molecular mechanisms of its adaptation to hypoxic environments.

A Comparative Analysis of XGBoost and Neural Network Models for Predicting Some Tomato Fruit Quality Traits from Environmental and Meteorological Data

The tomato as a raw material for processing is globally important and is pivotal in dietary and agronomic research due to its nutritional, economic, and health significance. This study explored the potential of machine learning (ML) for predicting tomato quality, utilizing data from 48 cultivars and 28 locations in Hungary over 5 seasons. It focused on °Brix, lycopene content, and colour (a/b ratio) using extreme gradient boosting (XGBoost) and artificial neural network (ANN) models. The results revealed that XGBoost consistently outperformed ANN, achieving high accuracy in predicting °Brix (R² = 0.98, RMSE = 0.07) and lycopene content (R² = 0.87, RMSE = 0.61), and excelling in colour prediction (a/b ratio) with a R² of 0.93 and RMSE of 0.03. ANN lagged behind particularly in colour prediction, showing a negative R² value of -0.35. Shapley additive explanation's (SHAP) summary plot analysis indicated that both models are effective in predicting °Brix and lycopene content in tomatoes, highlighting different aspects of the data. SHAP analysis highlighted the models' efficiency (especially in °Brix and lycopene predictions) and underscored the significant influence of cultivar choice and environmental factors like climate and soil. These findings emphasize the importance of selecting and fine-tuning the appropriate ML model for enhancing precision agriculture, underlining XGBoost's superiority in handling complex agronomic data for quality assessment.

Deciphering Physio-Biochemical Basis of Tolerance Mechanism for Sesame (Sesamum indicum L.) Genotypes under Waterlogging Stress at Early Vegetative Stage

Waterlogging represents a substantial agricultural concern, inducing harmful impacts on crop development and productivity. In the present study, 142 diverse sesame genotypes were examined during the early vegetative phase to assess their response under waterlogging conditions. Based on the severity of symptoms observed, 2 genotypes were classified as highly tolerant, 66 as moderately tolerant, 69 as susceptible, and 5 as highly susceptible. Subsequent investigation focused on four genotypes, i.e., two highly tolerant (JLT-8 and GP-70) and two highly susceptible (R-III-F6 and EC-335003). These genotypes were subjected to incremental stress periods (0 h, 24 h, 48 h, 72 h, and 96 h) to elucidate the biochemical basis of tolerance mechanisms. Each experiment was conducted as a randomized split-plot design with three replications, and the statistical significance of the treatment differences was determined using the one-way analysis of variance (ANOVA) followed by the Fisher least significant difference (LSD) test at p ≤ 0.05. The influence of waterlogging stress on morphological growth was detrimental for both tolerant and susceptible genotypes, with more severe consequences observed in the latter. Although adventitious roots were observed in both sets of genotypes above flooding levels, the tolerant genotypes exhibited a more rapid and vigorous development of these roots after 48 h of stress exposure. Tolerant genotypes displayed higher tolerance coefficients compared to susceptible genotypes. Furthermore, tolerant genotypes maintained elevated antioxidant potential, thereby minimizing oxidative stress. Conversely, susceptible genotypes exhibited higher accumulation of hydrogen peroxide (H2O2) and malondialdehyde content. Photosynthetic efficiency was reduced in all genotypes after 24 h of stress treatment, with a particularly drastic reduction in susceptible genotypes compared to their tolerant counterparts. Tolerant genotypes exhibited significantly higher activities of anaerobic metabolism enzymes, enabling prolonged survival under waterlogging conditions. Increase in proline content was observed in all the genotypes indicating the cellular osmotic balance adjustments in response to stress exposure. Consequently, the robust antioxidant potential and efficient anaerobic metabolism observed in the tolerant genotypes served as key mechanisms enabling their resilience to short-term waterlogging exposure. These findings underscore the promising potential of specific sesame genotypes in enhancing crop resilience against waterlogging stress, offering valuable insights for agricultural practices and breeding programs.

Climate Change-The Rise of Climate-Resilient Crops

Climate change disrupts food production in many regions of the world. The accompanying extreme weather events, such as droughts, floods, heat waves, and cold snaps, pose threats to crops. The concentration of carbon dioxide also increases in the atmosphere. The United Nations is implementing the climate-smart agriculture initiative to ensure food security. An element of this project involves the breeding of climate-resilient crops or plant cultivars with enhanced resistance to unfavorable environmental conditions. Modern agriculture, which is currently homogeneous, needs to diversify the species and cultivars of cultivated plants. Plant breeding programs should extensively incorporate new molecular technologies, supported by the development of field phenotyping techniques. Breeders should closely cooperate with scientists from various fields of science.

Appropriately Reduced Nitrogen and Increased Phosphorus in Ratooning Rice Increased the Yield and Reduced the Greenhouse Gas Emissions in Southeast China

Reducing greenhouse gas emissions while improving productivity is the core of sustainable agriculture development. In recent years, rice ratooning has developed rapidly in China and other Asian countries, becoming an effective measure to increase rice production and reduce greenhouse gas emissions in these regions. However, the lower yield of ratooning rice caused by the application of a single nitrogen fertilizer in the ratooning season has become one of the main reasons limiting the further development of rice ratooning. The combined application of nitrogen and phosphorus plays a crucial role in increasing crop yield and reducing greenhouse gas emissions. The effects of combined nitrogen and phosphorus application on ratooning rice remain unclear. Therefore, this paper aimed to investigate the effect of combined nitrogen and phosphorus application on ratooning rice. Two hybrid rice varieties, 'Luyou 1831' and 'Yongyou 1540', were used as experimental materials. A control treatment of nitrogen-only fertilization (187.50 kg·ha-1 N) was set, and six treatments were established by reducing nitrogen fertilizer by 10% (N1) and 20% (N2), and applying three levels of phosphorus fertilizer: N1P1 (168.75 kg·ha-1 N; 13.50 kg·ha-1 P), N1P2 (168.75 kg·ha-1 N; 27.00 kg·ha-1 P), N1P3 (168.75 kg·ha-1 N; 40.50 kg·ha-1 P), N2P1 (150.00 kg·ha-1 N; 13.50 kg·ha-1 P), N2P2 (150.00 kg·ha-1 N; 27.00 kg·ha-1 P), and N2P3 (150.00 kg·ha-1 N; 40.50 kg·ha-1 P). The effects of reduced nitrogen and increased phosphorus treatments in ratooning rice on the yield, the greenhouse gas emissions, and the community structure of rhizosphere soil microbes were examined. The results showed that the yield of ratooning rice in different treatments followed the sequence N1P2 > N1P1 > N1P3 > N2P3 > N2P2 > N2P1 > N. Specifically, under the N1P2 treatment, the average two-year yields of 'Luyou 1831' and 'Yongyou 1540' reached 8520.55 kg·ha-1 and 9184.90 kg·ha-1, respectively, representing increases of 74.30% and 25.79% compared to the N treatment. Different nitrogen and phosphorus application combinations also reduced methane emissions during the ratooning season. Appropriately combined nitrogen and phosphorus application reduced the relative contribution of stochastic processes in microbial community assembly, broadened the niche breadth of microbial communities, enhanced the abundance of functional genes related to methane-oxidizing bacteria and soil ammonia-oxidizing bacteria in the rhizosphere, and decreased the abundance of functional genes related to methanogenic and denitrifying bacteria, thereby reducing greenhouse gas emissions in the ratooning season. The carbon footprint of ratooning rice for 'Luyou 1831' and 'Yongyou 1540' decreased by 25.82% and 38.99%, respectively, under the N1P2 treatment compared to the N treatment. This study offered a new fertilization pattern for the green sustainable development of rice ratooning.

The mechanisms behind the contrasting responses to waterlogging in black-grass (Alopecurus myosuroides) and wheat (Triticum aestivum)

Black-grass (Alopecurus myosuroides ) is one of the most problematic agricultural weeds of Western Europe, causing significant yield losses in winter wheat (Triticum aestivum ) and other crops through competition for space and resources. Previous studies link black-grass patches to water-retaining soils, yet its specific adaptations to these conditions remain unclear. We designed pot-based waterlogging experiments to compare 13 biotypes of black-grass and six cultivars of wheat. These showed that wheat roots induced aerenchyma when waterlogged whereas aerenchyma-like structures were constitutively present in black-grass. Aerial biomass of waterlogged wheat was smaller, whereas waterlogged black-grass was similar or larger. Variability in waterlogging responses within and between these species was correlated with transcriptomic and metabolomic changes in leaves of control or waterlogged plants. In wheat, transcripts associated with regulation and utilisation of phosphate compounds were upregulated and sugars and amino acids concentrations were increased. Black-grass biotypes showed limited molecular responses to waterlogging. Some black-grass amino acids were decreased and one transcript commonly upregulated was previously identified in screens for genes underpinning metabolism-based resistance to herbicides. Our findings provide insights into the different waterlogging tolerances of these species and may help to explain the previously observed patchiness of this weed's distribution in wheat fields.

Effects of Waterlogging at Flowering Stage on the Grain Yield and Starch Quality of Waxy Maize

Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses, and this stage frequently overlapped the plum rain season in the middle and lower reaches of Yangtze river in China and affect the yield and quality of spring-sown maize severely. In the present study, the soil moisture content under control and waterlogging conditions at the flowering stage was controlled by a negative-pressure water supply and controlling pot device in a pot trial in 2014-2015. The grain yield, starch content, and starch structural and functional properties under two soil moisture levels were compared using Suyunuo5 (SYN5) and Yunuo7 (YN7) as materials, which are the control hybrids of National waxy maize hybrid regional trials in Southern China. The results observed that the grain yield was reduced by 29.1% for SYN5 with waterlogging due to the decreased grain weight and numbers, which was significantly higher than that of YN7 (14.7%), indicated that YN7 was more tolerant to waterlogging. The grain starch content in YN7 was decreased by 9.4% when plants suffered waterlogging at the flowering stage, whereas the content in SYN5 was only decreased in 2014 and unaffected in 2015. The size of starch granules and proportion of small-molecule amylopectin with waterlogging at the flowering stage increased in SYN5 and decreased in YN7 in both years. The type of starch crystalline structure was not changed by waterlogging, whereas the relative crystallinity was reduced in SYN5 and increased in YN7. The pasting viscosities were decreased, and the pasting temperature was unaffected by waterlogging in general. The gelatinization enthalpy was unaffected by waterlogging in both hybrids in both years, whereas the retrogradation enthalpy and percentage in both hybrids were reduced by waterlogging in 2014 and unaffected in 2015. Between the two hybrids, YN7 has high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for more viscous and less retrograde food. In conclusion, waterlogging at the flowering stage reduced the grain yield, restricted starch accumulation, and deteriorated the pasting viscosity of waxy maize. Results provide information for utilization of waxy maize grain in food production.

The Population Divergence and Genetic Basis of Local Adaptation of Wild Soybean (Glycine soja) in China

Glycine soja is the wild relative species of cultivated soybean. In this study, we investigated the population divergence and genetic basis of the local adaptation of wild soybean in China using genome-wide single-nucleotide polymorphisms (SNPs) of a population of 72 G. soja accessions. Using phylogenetic analysis, we observed that G. soja accessions clustered into three distinct groups, each corresponding to a specific geographic region, the northeastern region (NER), central region (CR), and southern region (SR), consistent with previous studies. Notably, we found a significant positive correlation between genetic and geographic distances. Further population structure analysis revealed each group was associated with an ancestral population and a specific geographic area. By utilizing the genome sequencing data of accessions from 16 different locations, we inferred the population history of these wild soybean groups. Our results indicate that the three groups diverged ~25,000 years ago, coinciding with the time of the last glacial maximum. The effective population size of the SR group expanded first, and subsequently, the NER and CR groups expanded approximately 5000 and 2500 years ago, respectively. Moreover, 83, 104, and 101 significant associated loci (SALs) were identified using genome-wide association analysis for annual mean temperature, annual precipitation, and latitude, respectively. Functional analysis of genes located in SALs highlighted candidate genes related to local adaptation. This study highlights the significant role of geographic isolation and environmental factors in shaping the genetic structure and adaptability of wild soybean populations. Furthermore, it emphasizes the value of wild soybean as a crucial genetic resource for enhancing the adaptability of cultivated soybeans, which have experienced a loss of genetic diversity due to domestication and intensive breeding practices. The insights gained from our research provide valuable information for the protection, conservation, and utilization of this important genetic resource.

Physiological Properties of Perennial Rice Regenerating Cultivation in Two Years with Four Harvests

Crop perennialization has garnered global attention recently due to its role in sustainable agriculture. However, there is still a lack of detailed information regarding perennial rice's regenerative characteristics and physiological mechanisms in crop ratooning systems with different rice stubble heights. In addition, the response of phytohormones to varying stubble heights and how this response influences the regenerative characteristics of ratoon rice remains poorly documented. Here, we explored the regenerative characteristics and physiological mechanisms of an annual hybrid rice, AR2640, and a perennial rice, PR25, subjected to different stubble heights (5, 10, and 15 cm). The response of phytohormones to varying stubble heights and how this response influences the regenerative characteristics of ratoon rice were also investigated. The results show that PR25 overwintered successfully and produced the highest yield, especially in the second ratoon season, mainly due to its extended growth duration, higher number of mother stems, tillers at the basal nodes, higher number of effective panicles, and heavier grain weight when subjected to lower stubble heights. Further analysis revealed that PR25 exhibited a higher regeneration rate from the lower-position nodes in the stem with lower stubble heights. this was primarily due to the higher contents of phytohormones, especially auxin (IAA) and gibberellin (GA3) at an early stage and abscisic acid (ABA) at a later stage after harvesting of the main crop. Our findings reveal how ratoon rice enhances performance based on different stubble heights, which provides valuable insights and serves as crucial references for delving deeper into cultivating high-yielding perennial rice.

Plant Adaptation to Flooding Stress under Changing Climate Conditions: Ongoing Breakthroughs and Future Challenges

Climate-change-induced variations in temperature and rainfall patterns are a serious threat across the globe. Flooding is the foremost challenge to agricultural productivity, and it is believed to become more intense under a changing climate. Flooding is a serious form of stress that significantly reduces crop yields, and future climatic anomalies are predicted to make the problem even worse in many areas of the world. To cope with the prevailing flooding stress, plants have developed different morphological and anatomical adaptations in their roots, aerenchyma cells, and leaves. Therefore, researchers are paying more attention to identifying developed and adopted molecular-based plant mechanisms with the objective of obtaining flooding-resistant cultivars. In this review, we discuss the various physiological, anatomical, and morphological adaptations (aerenchyma cells, ROL barriers (redial O2 loss), and adventitious roots) and the phytohormonal regulation in plants under flooding stress. This review comprises ongoing innovations and strategies to mitigate flooding stress, and it also provides new insights into how this knowledge can be used to improve productivity in the scenario of a rapidly changing climate and increasing flood intensity.

Crop sensitivity to waterlogging mediated by soil temperature and growth stage

Waterlogging constrains crop yields in many regions around the world. Despite this, key drivers of crop sensitivity to waterlogging have received little attention. Here, we compare the ability of the SWAGMAN Destiny and CERES models in simulating soil aeration index, a variable contemporaneously used to compute three distinct waterlogging indices, denoted hereafter as WI Destiny, WIASD1, and WIASD2. We then account for effects of crop growth stage and soil temperature on waterlogging impact by introducing waterlogging severity indices, WI Growth, which accommodates growth stage tolerance, and WI Plus, which accounts for both soil temperature and growth stage. We evaluate these indices using data collected in pot experiments with genotypes "Yang mai 11" and "Zheng mai 7698" that were exposed to both single and double waterlogging events. We found that WI Plus exhibited the highest correlation with yield (-0.82 to -0.86) suggesting that waterlogging indices which integrate effects of temperature and growth stage may improve projections of yield penalty elicited by waterlogging. Importantly, WI Plus not only allows insight into physiological determinants, but also lends itself to remote computation through satellite imagery. As such, this index holds promise in scalable monitoring and forecasting of crop waterlogging.

Optimizing Nitrogen Fertilization to Enhance Productivity and Profitability of Upland Rice Using CSM-CERES-Rice

Nitrogen (N) deficiency can limit rice productivity, whereas the over- and underapplication of N results in agronomic and economic losses. Process-based crop models are useful tools and could assist in optimizing N management, enhancing the production efficiency and profitability of upland rice production systems. The study evaluated the ability of CSM-CERES-Rice to determine optimal N fertilization rate for different sowing dates of upland rice. Field experimental data from two growing seasons (2018-2019 and 2019-2020) were used to simulate rice responses to four N fertilization rates (N30, N60, N90 and a control-N0) applied under three different sowing windows (SD1, SD2 and SD3). Cultivar coefficients were calibrated with data from N90 under all sowing windows in both seasons and the remaining treatments were used for model validation. Following model validation, simulations were extended up to N240 to identify the sowing date's specific economic optimum N fertilization rate (EONFR). Results indicated that CSM-CERES-Rice performed well both in calibration and validation, in simulating rice performance under different N fertilization rates. The d-index and nRMSE values for grain yield (0.90 and 16%), aboveground dry matter (0.93 and 13%), harvest index (0.86 and 7%), grain N contents (0.95 and 18%), total crop N uptake (0.97 and 15%) and N use efficiencies (0.94-0.97 and 11-15%) during model validation indicated good agreement between simulated and observed data. Extended simulations indicated that upland rice yield was responsive to N fertilization up to 180 kg N ha-1 (N180), where the yield plateau was observed. Fertilization rates of 140, 170 and 130 kg N ha-1 were identified as the EONFR for SD1, SD2 and SD3, respectively, based on the computed profitability, marginal net returns and N utilization. The model results suggested that N fertilization rate should be adjusted for different sowing windows rather than recommending a uniform N rate across sowing windows. In summary, CSM-CERES-Rice can be used as a decision support tool for determining EONFR for seasonal sowing windows to maximize the productivity and profitability of upland rice production.

Effects of 6-Benzyladenine (6-BA) on the Filling Process of Maize Grains Placed at Different Ear Positions under High Planting Density

Increasing grain weight under dense planting conditions can further improve maize yield. 6-BA is known to be involved in regulating grain development and influencing grain weight. Maize grain development is closely linked to starch accumulation and hormone levels. In this work, the effects of applying 6-BA at the flowering stage under high density on the grain filling characteristics, starch content, starch synthesis critical enzyme activity, and endogenous hormones levels of maize grains (including inferior grains (IGs) and superior grains (SGs)) of two high-yielding summer maize varieties widely cultivated in China were investigated. The findings indicated that applying 6-BA significantly improved maize yield compared to the control, mainly as a result of increased grain weight due to a faster grain filling rate. Additionally, the activities of enzymes associated with starch synthesis, including sucrose synthase (SuSy), ADP-glucose pyrophosphorylase (AGPase), granule-bound starch synthase (GBSS), soluble starch synthase (SSS), and starch branching enzyme (SBE), were all increased following 6-BA application, thus facilitating starch accumulation in the grains. Applying 6-BA also increased the zeatin riboside (ZR), indole-3-acetic acid (IAA), and abscisic acid (ABA) levels, and reduced the gibberellin (GA3) level in the grains, which further improved grain filling. It is worth noting that IG had a poorer filling process than SG, possibly due to the low activities of critical enzymes for starch synthesis and imbalanced endogenous hormones levels. However, IG responded more strongly to exogenous 6-BA than SG. It appears that applying 6-BA is beneficial in improving filling characteristics, promoting starch accumulation by enhancing the activities of critical enzymes for starch synthesis, and altering endogenous hormones levels in the grains, thus improving grain filling and increasing the final grain weight and yield of maize grown under crowded conditions. These results provide theoretical and technical support for the further utilization of exogenous hormones in high-density maize production.

"Bet hedging" against climate change in developing and adult animals: roles for stochastic gene expression, phenotypic plasticity, epigenetic inheritance and adaptation

Animals from embryos to adults experiencing stress from climate change have numerous mechanisms available for enhancing their long-term survival. In this review we consider these options, and how viable they are in a world increasingly experiencing extreme weather associated with climate change. A deeply understood mechanism involves natural selection, leading to evolution of new adaptations that help cope with extreme and stochastic weather events associated with climate change. While potentially effective at staving off environmental challenges, such adaptations typically occur very slowly and incrementally over evolutionary time. Consequently, adaptation through natural selection is in most instances regarded as too slow to aid survival in rapidly changing environments, especially when considering the stochastic nature of extreme weather events associated with climate change. Alternative mechanisms operating in a much shorter time frame than adaptation involve the rapid creation of alternate phenotypes within a life cycle or a few generations. Stochastic gene expression creates multiple phenotypes from the same genotype even in the absence of environmental cues. In contrast, other mechanisms for phenotype change that are externally driven by environmental clues include well-understood developmental phenotypic plasticity (variation, flexibility), which can enable rapid, within-generation changes. Increasingly appreciated are epigenetic influences during development leading to rapid phenotypic changes that can also immediately be very widespread throughout a population, rather than confined to a few individuals as in the case of favorable gene mutations. Such epigenetically-induced phenotypic plasticity can arise rapidly in response to stressors within a generation or across a few generations and just as rapidly be "sunsetted" when the stressor dissipates, providing some capability to withstand environmental stressors emerging from climate change. Importantly, survival mechanisms resulting from adaptations and developmental phenotypic plasticity are not necessarily mutually exclusive, allowing for classic "bet hedging". Thus, the appearance of multiple phenotypes within a single population provides for a phenotype potentially optimal for some future environment. This enhances survival during stochastic extreme weather events associated with climate change. Finally, we end with recommendations for future physiological experiments, recommending in particular that experiments investigating phenotypic flexibility adopt more realistic protocols that reflect the stochastic nature of weather.

Comparison of Policosanol Profiles of the Sprouts of Wheat Mutant Lines and the Effect of Differential LED Lights on Selected Lines

Policosanols (PCs) are long-chain linear aliphatic alcohols that are present in the primary leaves of cereal crops, such as barley and wheat, sugar cane wax, and beeswax. PCs have been used as a nutraceutical for improving hyperlipidemia and hypercholesterolemia. However, the PC content in mutant wheat lines has not been investigated. To select highly functional wheat sprouts with a high content of PCs in wheat mutant lines developed via gamma-irradiated mutation breeding, we cultivated the sprouts of wheat mutant lines in a growth chamber with white LED light (6000 K) and analyzed the PC content in these samples using GC-MS. We studied the PC content in 91 wheat sprout samples: the original variety (Woori-mil × D-7; WS01), commercially available cv. Geumgang (WS87) and cv. Cheongwoo (WS91), and mutant lines (WS02-WS86 and WS88-WS90) developed from WS01 and WS87. Compared to WS01, 18 mutant lines exhibited a high total PC content (506.08-873.24 mg/100 g dry weight). Among them, the top 10 mutant lines were evaluated for their PC production after cultivating under blue (440 nm), green (520 nm), and red (660 nm) LED light irradiation; however, these colored LED lights reduced the total PC production by 35.8-49.7%, suggesting that the cultivation with white LED lights was more efficient in promoting PCs' yield, compared to different LED lights. Therefore, our findings show the potential of radiation-bred wheat varieties as functional foods against hyperlipidemia and obesity and the optimal light conditions for high PC production.

Lemnaceae as Novel Crop Candidates for CO2 Sequestration and Additional Applications

Atmospheric carbon dioxide (CO2) is projected to be twice as high as the pre-industrial level by 2050. This review briefly highlights key responses of terrestrial plants to elevated CO2 and compares these with the responses of aquatic floating plants of the family Lemnaceae (duckweeds). Duckweeds are efficient at removing CO2 from the atmosphere, which we discuss in the context of their exceptionally high growth rates and capacity for starch storage in green tissue. In contrast to cultivation of terrestrial crops, duckweeds do not contribute to CO2 release from soils. We briefly review how this potential for contributions to stabilizing atmospheric CO2 levels is paired with multiple additional applications and services of duckweeds. These additional roles include wastewater phytoremediation, feedstock for biofuel production, and superior nutritional quality (for humans and livestock), while requiring minimal space and input of light and fertilizer. We, furthermore, elaborate on other environmental factors, such as nutrient availability, light supply, and the presence of a microbiome, that impact the response of duckweed to elevated CO2. Under a combination of elevated CO2 with low nutrient availability and moderate light supply, duckweeds' microbiome helps maintain CO2 sequestration and relative growth rate. When incident light intensity increases (in the presence of elevated CO2), the microbiome minimizes negative feedback on photosynthesis from increased sugar accumulation. In addition, duckweed shows a clear propensity for absorption of ammonium over nitrate, accepting ammonium from their endogenous N2-fixing Rhizobium symbionts, and production of large amounts of vegetative storage protein. Finally, cultivation of duckweed could be further optimized using hydroponic vertical farms where nutrients and water are recirculated, saving both resources, space, and energy to produce high-value products.

Light-Induced TaHY5-7A and TaBBX-3B Physically Interact to Promote PURPLE PERICARP-MYB 1 Expression in Purple-Grained Wheat

Purple-grained wheat (Triticum aestivum L.) is an important germplasm source in crop breeding. Anthocyanin biosynthesis in the pericarps of purple-grained wheat is largely light-dependent; however, the regulatory mechanisms underlying light-induced anthocyanin accumulation in the wheat pericarp remain unknown. Here we determined that anthocyanins rapidly accumulate in the pericarps of the purple-grained wheat cultivar Heixiaomai 76 (H76) at 16 days after pollination under light treatment. Using transcriptome sequencing, differential gene expression analysis, and phylogenetic analysis, we identified two key genes involved in light signaling in wheat: ELONGATED HYPOCOTYL 5-7A (TaHY5-7A) and B-BOX-3B (TaBBX-3B). TaHY5-7A and TaBBX-3B were highly expressed in purple-grained wheat pericarps. The heterologous expression of TaHY5-7A partially restored the phenotype of the Arabidopsis (Arabidopsis thaliana) hy5 mutant, resulting in increased anthocyanin accumulation and a shortened hypocotyl. The heterologous expression of TaBBX-3B in wild-type Arabidopsis had similar effects. TaHY5-7A and TaBBX-3B were nucleus-localized, consistent with a function in transcription regulation. However, TaHY5-7A, which lacks a transactivation domain, was not sufficient to activate the expression of PURPLE PERICARP-MYB 1 (TaPpm1), the key anthocyanin biosynthesis regulator in purple pericarps of wheat. TaHY5-7A physically interacted with TaBBX-3B in yeast two-hybrid and bimolecular fluorescence complementation assays. Additionally, TaHY5-7A, together with TaBBX-3B, greatly enhanced the promoter activity of TaPpm1 in a dual luciferase assay. Overall, our results suggest that TaHY5-7A and TaBBX-3B collaboratively activate TaPpm1 expression to promote light-induced anthocyanin biosynthesis in purple-pericarp wheat.

Optimizing Grain Yield and Radiation Use Efficiency through Synergistic Applications of Nitrogen and Potassium Fertilizers in Super Hybrid Rice

The remarkable yield performance of super hybrid rice has played a crucial role in ensuring global food security. However, there is a scarcity of studies investigating the contribution of radiation use efficiency (RUE) to hybrid rice yields under different nitrogen and potassium treatments. In this three-year field experiment, we aimed to evaluate the impact of two hybrid rice varieties (Y-liangyou 900: YLY900 and Quanyouhuazhan: QYHZ) under varying nitrogen regimes (N90: 90 kg N ha-1, N120: 120 kg N ha-1, N180: 180 kg N ha-1) and potassium regimes (K120: 120 kg K2O ha-1, K160: 160 kg K2O ha-1, K210: 210 kg K2O ha-1) on grain yield and its physiological determinants, including RUE, intercepted photosynthetically active radiation (IPAR), aboveground biomass production, and harvest index (HI). Our results revealed that both rice varieties exhibited significantly higher yields when coupled with nitrogen and potassium fertilization. Compared to the N90 × K120 treatment, the N120 × K160 and N180 × K210 combinations resulted in substantial increases in grain yield (12.0% and 21.1%, respectively) and RUE (11.9% and 21.4%, respectively). The YLY900 variety showed notable yield improvement due to enhanced aboveground biomass production resulting from increased IPAR and RUE. In contrast, the QYHZ variety's aboveground biomass accumulation was primarily influenced by RUE rather than IPAR, resulting in higher RUE and grain yields of 9.2% and 5.3%, respectively, compared to YLY900. Importantly, fertilization led to significant increases in yield, biomass, and RUE, while HI remained relatively constant. Both varieties demonstrated a positive relationship between grain yield and IPAR and RUE. Multiple regression analysis indicated that increasing RUE was the primary driver of yield improvement in hybrid rice varieties. By promoting sustainable agriculture and enhancing fertilizer management, elevating nitrogen and potassium levels from a low base would synergistically enhance rice yield and RUE, emphasizing the critical importance of RUE in hybrid rice productivity compared to HI.

Ethylene enhanced waterlogging tolerance by changing root architecture and inducing aerenchyma formation in maize seedlings

Waterlogging negatively affects maize growth and yield. In this study, we found that ethylene played a vital role in plant adaptation to waterlogging. ET promotes better growth in seedlings under waterlogging conditions by altering root architecture and increasing lateral root formation by 42.1%. What's more, plants with high endogenous ethylene levels exhibited reduced sensitivity to waterlogging stress. ET also induced the formation of aerenchyma, a specialized tissue that facilitates gas exchange, in a different pattern compared to aerenchyma formed under waterlogging. Aerenchyma induced by ET was mainly located in the medial cortex of the roots and was not prone to decay. ethylene inhibited root elongation under normal conditions, but this inhibition was not alleviated under waterlogging stress. Upon activation of the ET signaling pathway, the transcription factor EREB90 promoted aerenchyma formation by enhancing the programmed cell death process. Overexpression of EREB90 resulted in increased waterlogging tolerance compared to wild type plants. Our findings suggest that pre-treatment of maize seedlings with ET before waterlogging stress can trigger the programmed cell death process and induce aerenchyma formation, thus improving waterlogging resistance.

Developing functional relationships between waterlogging and cotton growth and physiology-towards waterlogging modeling

Cotton crop is known to be poorly adapted to waterlogging, especially during the early growth stages. Developing functional relationships between crop growth and development parameters and the duration of waterlogging is essential to develop or improve existing cotton crop models for simulating the impact of waterlogging. However, there are only limited experimental studies conducted on cotton specifically aimed at developing the necessary functional relationships required for waterlogging modeling. Further research is needed to understand the effects of waterlogging on cotton crops and improve modeling capabilities in this area. The current study aimed to conduct waterlogging experiments and develop functional relationships between waterlogging and cotton growth and physiology. The experiments were conducted in pots, and the waterlogging was initiated by plugging the drain hole at the bottom of the pot using a wooden peg. In the experiments, eight waterlogging treatments, including the control treatment, were imposed at the vegetative growth stage (15 days after sowing). Control treatment had zero days of water-logged condition; other treatments had 2, 4, 6, 8, 10, 12, and 14 days of waterlogging. It took five days to reach zero oxygen levels and one to two days to return to control after the treatment. After a total treatment duration of 14 days (30 days after sowing), the growth, physiological, reproductive, and nutrient analysis was conducted. All physiological parameters decreased with the number of days of waterlogging. Flavonoid and anthocyanin index increased with increased duration of waterlogging. Photosynthesis and whole plant dry weight in continuously waterlogged conditions were 75% and 78% less compared to 0, and 2-day water-logged plants. Plant height, stem diameter, number of main stem leaves, leaf area, and leaf length also decreased with waterlogging duration. When waterlogging duration increased, leaf, stem, and root macronutrients decreased, while micronutrients showed mixed trends. Based on the experimental study, functional relationships (linear, quadratic, and exponential decay) and waterlogging stress response indices are developed between growth and development parameters and the duration of waterlogging. This can serve as a base for developing or improving process-based cotton models to simulate the impact of waterlogging.

Genetic resources and precise gene editing for targeted improvement of barley abiotic stress tolerance

Abiotic stresses, predominately drought, heat, salinity, cold, and waterlogging, adversely affect cereal crops. They limit barley production worldwide and cause huge economic losses. In barley, functional genes under various stresses have been identified over the years and genetic improvement to stress tolerance has taken a new turn with the introduction of modern gene-editing platforms. In particular, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) is a robust and versatile tool for precise mutation creation and trait improvement. In this review, we highlight the stress-affected regions and the corresponding economic losses among the main barley producers. We collate about 150 key genes associated with stress tolerance and combine them into a single physical map for potential breeding practices. We also overview the applications of precise base editing, prime editing, and multiplexing technologies for targeted trait modification, and discuss current challenges including high-throughput mutant genotyping and genotype dependency in genetic transformation to promote commercial breeding. The listed genes counteract key stresses such as drought, salinity, and nutrient deficiency, and the potential application of the respective gene-editing technologies will provide insight into barley improvement for climate resilience.

Drying Temperature Precision Control System Based on Improved Neural Network PID Controller and Variable-Temperature Drying Experiment of Cantaloupe Slices

A drying temperature precision control system was studied to provide technical support for developing and further proving the superiority of the variable-temperature drying process. In this study, an improved neural network (INN) proportional-integral-derivative (PID) controller (INN-PID) was designed. The dynamic performance of the PID, neural network PID (NN-PID) and INN-PID controllers was simulated with unit step signals as an input in MATLAB software. A drying temperature precision control system was set up in an air impingement dryer, and the drying temperature control experiment was carried out to verify the performance of the three controllers. Linear variable-temperature (LVT) and constant-temperature drying experiments of cantaloupe slices were carried out based on the system. Moreover, the experimental results were evaluated comprehensively with the brightness (L value), colour difference (ΔE), vitamin C content, chewiness, drying time and energy consumption (EC) as evaluation indexes. The simulation results show that the INN-PID controller outperforms the other two controllers in terms of control accuracy and regulation time. In the drying temperature control experiment at 50 °C-55 °C, the peak time of the INN-PID controller is 237.37 s, the regulation time is 134.91 s and the maximum overshoot is 4.74%. The INN-PID controller can quickly and effectively regulate the temperature of the inner chamber of the air impingement dryer. Compared with constant-temperature drying, LVT is a more effective drying mode as it ensures the quality of the material and reduces the drying time and EC. The drying temperature precision control system based on the INN-PID controller meets the temperature control requirements of the variable-temperature drying process. This system provides practical and effective technical support for the variable-temperature drying process and lays the foundation for further research. The LVT drying experiments of cantaloupe slices also show that variable-temperature drying is a better process than constant-temperature drying and is worthy of further study to be applied in production.

QTL Mapping of Agronomic and Physiological Traits at the Seedling and Maturity Stages under Different Nitrogen Treatments in Barley

Nitrogen (N) stress seriously constrains barley (Hordeum vulgare L.) production globally by influencing its growth and development. In this study, we used a recombinant inbred line (RIL) population of 121 crosses between the variety Baudin and the wild barley accession CN4027 to detect QTL for 27 traits at the seedling stage in hydroponic culture trials and 12 traits at the maturity stage in field trials both under two N treatments, aiming to uncover favorable alleles for N tolerance in wild barley. In total, eight stable QTL and seven QTL clusters were detected. Among them, the stable QTL Qtgw.sau-2H located in a 0.46 cM interval on the chromosome arm 2HL was a novel QTL specific for low N. Notably, Clusters C4 and C7 contained QTL for traits at both the seedling and maturity stages. In addition, four stable QTLs in Cluster C4 were identified. Furthermore, a gene (HORVU2Hr1G080990.1) related to grain protein in the interval of Qtgw.sau-2H was predicted. Correlation analysis and QTL mapping showed that different N treatments significantly affected agronomic and physiological traits at the seedling and maturity stages. These results provide valuable information for understanding N tolerance as well as breeding and utilizing the loci of interest in barley.

Metabolic Responses in Leaves of 15 Italian Olive Cultivars in Correspondence to Variable Climatic Elements

This study aims to evaluate the metabolic changes that occurred in olive leaves as responses over time to variations in climatic elements. Rainfall, temperature, and solar radiation data were collected over 4 months (August-November) to assess the impact of different climatic trends on the metabolism of the leaves of 15 Italian olive cultivars, cultivated at the experimental farm of the University of Florence. The net photosynthetic rate (AN) and stomatal conductance (gs), measured as main indicators of primary metabolism, were mainly influenced by the "cultivar" effect compared to the "climate" effect. The lowest AN value was showed by "Bianchera", while "Ascolana" recorded the highest (8.6 and 13.6 µmol CO2 m-2s-1, respectively). On the other hand, the secondary metabolism indicators, volatile organic compound (VOC) and oleuropein (OL) content, were much more influenced by climate trends, especially rainfall. A phase of high rainfall caused a significant increase in the VOCs emission from leaves, even with different behaviors among the genotypes. The highest differences were observed between "Maiatica di Ferrandina", with the highest average values (~85,000 npcs), and "Frantoio", which showed the lowest (~22,700 npcs). The OL content underwent considerable fluctuations in relation to the rainfall but also appeared to be controlled by the genotype. "Coratina" always showed the highest OL concentration (reaching the maximum ~98 mg g-1), indicating the great potential of this cultivar for the industrial recovery of OL.

Identification of Superior Barley Genotypes Using Selection Index of Ideal Genotype (SIIG)

The main objective of the study was to evaluate and select the superior barley genotypes based on grain yield and some pheno-morphological traits using a new proposed selection index (SIIG). For this purpose, one-hundred-eight pure and four local cultivars (Norouz, Auxin, Nobahar, and WB-97-11) were evaluated as reference genotypes in four warm regions of Iran, including Ahvaz, Darab, Zabol, and Gonbad, during the 2020-2021 cropping seasons. The results of REML analysis showed that the heritability of all traits (except plant height) was higher in Gonbad than in other environments, while the lowest values were estimated in Ahvaz and Zabol environments. In addition, among the measured traits, the thousand kernel weight and grain filling period showed the highest and lowest values of heritability (0.83 and 0.01, respectively). The results showed that the seed yield of genotypes 1, 108, 3, 86, 5, 87, 19, 16, 15, 56, and 18 was higher than the four reference genotypes, and, on the other hand, the SIIG index of these genotypes was greater than or equal to 0.60. Based on the SIIG discriminator index, 4, 8, 31, and 28 genotypes with values greater than or equal to 0.60 were identified as superior for Darab, Ahvaz, Zabol, and Gonbad environments, respectively. As a conclusion, our results revealed that the SIIG index has ideal potential to identify genotypes with high yield and desirable traits. Therefore, the use of this index can be beneficial in screening better genotypes in the early stages of any breeding program for any crop.

Silicon, by promoting a homeostatic balance of C:N:P and nutrient use efficiency, attenuates K deficiency, favoring sustainable bean cultivation

BACKGROUND

In many regions of the world, K is being depleted from soils due to agricultural intensification a lack of accessibility, and the high cost of K. Thus, there is an urgent need for a sustainable strategy for crops in this environment. Si is an option for mitigating stress due to nutritional deficiency. However, the underlying effects of Si in mitigating K deficiency C:N:P homeostasis still remains unknown for bean plants. This is a species of great worldwide importance. Thus, this study aims to evaluate whether i) K deficiency modifies the homeostatic balance of C, N and P, and, if so, ii) Si supply can reduce damage caused to nutritional stoichiometry, nutrient use efficiency, and production of dry mass in bean plants.

RESULTS

K deficiency caused a reduction in the stoichiometric ratios C:N, C:P, and P:Si in shoots and C:N, C:P, C:Si, N:Si, and P:Si in roots, resulting in a decrease in K content and use efficiency and reducing biomass production. The application of Si in K-deficient plants modified the ratios C:N, C:Si, N:P, N:Si, and P:Si in shoots and C:N, C:P, C:Si, N:Si, N:P, and P:Si in roots, increasing the K content and efficiency, reducing the loss of biomass. In bean plants with K sufficiency, Si also changed the stoichiometric ratios C:N, C:P, C:Si, N:P, N:Si, and P:Si in shoots and C:N, C:Si, N:Si, and P:Si in roots, increasing K content only in roots and the use efficiency of C and P in shoots and C, N, and P in roots, increasing the biomass production only in roots.

CONCLUSION

K deficiency causes damage to the C:N:P homeostatic balance, reducing the efficiency of nutrient use and biomass production. However, Si is a viable alternative to attenuate these nutritional damages, favoring bean growth. The future perspective is that the use of Si in agriculture in underdeveloped economies with restrictions on the use of K will constitute a sustainable strategy to increase food security.

Spatial-Temporal Characteristics of Spring Maize Drought in Songnen Plain, Northeast China

With the intensification of global warming, food production will face serious drought risk. In view of the insufficient applicability of the existing crop drought index, a standardized crop water deficit index (SCWDI) was constructed based on the construction idea of the standardized precipitation evapotranspiration index (SPEI) and the crop water deficit index (CWDI) in this study. On this basis, the spatial and temporal characteristics of spring maize drought in Songnen Plain were explored by the slope trend analysis and Morlet wavelet analysis methods. The results show the following: (1) Compared with the existing drought index, the SCWDI shows obvious advantages in drought monitoring of spring maize. (2) In the whole growth stage of spring maize, the change trend of SCWDI was small in the temporal series (−0.012/10a). Spatially, the drought trend of spring maize was mainly decreasing (−0.14~0/10a). The drought frequency of spring maize in each growth stage was mainly light drought in most regions. (3) The three main drought cycles of spring maize in Songnen Plain were 29 years, 10 years, and 4 years. In the next few years, the drought of spring maize in Songnen Plain was controlled by the first main cycle, and the drought years may increase, which should be prevented. The research was expected to provide technical support for crop drought monitoring and agricultural disaster prevention.