Drought stress is a significant environmental challenge impacting plant growth and productivity. This study investigates the drought tolerance mechanisms of Lespedeza davurica, a drought-tolerant legume, by analyzing root physiological responses and conducting RNA-Seq analysis under controlled drought conditions. Plants were subjected to drought stress for ten days and then rewatered to assess recovery. We measured key physiological parameters such as proline accumulation, antioxidative enzymes activity, and electrolyte leakage. RNA-Seq identified 6,482 differentially expressed genes (DEGs) under drought stress, with upregulated genes primarily involved in antioxidant processes (e.g., glutathione and ascorbate metabolism) and downregulated genes were linked to carbon metabolism. Following rewatering, gene expression was restored, with significant upregulation in nitrogen metabolism and amino sugar metabolism pathways, reflecting enhanced energy metabolism and accelerated recovery. Weighted Gene Co-expression Network Analysis (WGCNA) identified 50 core drought-tolerance genes, with LdALDH2-19 selected for functional analysis. Overexpression of LdALDH2-19 in hairy roots (OE-LdALDH2-19) significantly alleviated oxidative damage under osmotic stress, as indicated by reduced MDA levels accompanied by increased antioxidant enzyme activity compared to the control (EV). These findings suggest that LdALDH2-19 plays a critical role in drought tolerance by mitigating oxidative stress and contributing ROS homeostasis, offering insights for improving drought resistance in leguminous crop breeding.

Nitrogen is an essential element for plant growth, and low nitrogen stress significantly restricts crop yield. Therefore, cultivating crop varieties that are tolerant to low nitrogen is crucial for agricultural production. The AT-hook motif nuclear localization protein (AHL) family is vital for plant stress resistance. To investigate the potential regulatory mechanisms of the AHL family in maize under low nitrogen stress, 35 ZmAHL genes were identified from the maize genome using bioinformatics methods. The results indicated that these genes encode proteins with lengths ranging from 203 to 573 amino acids, with relative molecular weights between 20.68 and 59.68 kDa, and they are unevenly distributed across 10 chromosomes. Most proteins encoded by these genes are alkaline hydrophilic proteins, primarily localized in the nucleus. Family expansion occurred through tandem and fragment repeats, which exhibited evolutionary conservation with rice homologous genes. Transcriptome analysis revealed that the majority of ZmAHL genes in drought-tolerant maize inbred lines were significantly up-regulated under drought and low nitrogen stress, with the ZmAHL10 gene displaying the most pronounced response to low nitrogen conditions. Experiments involving transgenic Arabidopsis thaliana further confirmed that the growth status, nitrogen uptake, and photosynthetic pigment content of ZmAHL10 overexpression strains under low nitrogen conditions were superior to those of the wild type, while the mutant exhibited significant growth inhibition. Overall, this study delineated the fundamental characteristics of the maize ZmAHL gene family and established that ZmAHL10 enhances low nitrogen tolerance in plants by improving nitrogen absorption capacity and maintaining the stability of the photosynthetic system. This research provides candidate genes and a theoretical foundation for the molecular breeding of maize with enhanced low nitrogen tolerance.

The partitioning of absorbed light energy is central to crop productivity and photoprotection. However, the extent to which maize cultivars differ in energy partitioning under varying nitrogen (N) supply remains insufficiently understood. Here, we conducted a pot experiment using eight maize hybrids grown under three N levels and systematically quantified energy partitioning via pulse amplitude modulation (PAM) fluorometry, integrating both quenching and relaxation analyses. Our results showed that the photochemical compensation point (PCCP), defined as the light intensity at which photochemical and non-photochemical energy use are equal, varied significantly among cultivars at each N level, and its response to N supply was cultivar-dependent. The average PCCP values were 320.9 μmol m-2s-1 under low N (LN), 328.3 under moderate N (MN), and 294.4 under high N (HN). Energy partitioning analysis revealed that while no differences in the quantum yield of non-photochemical quenching (ΦNPQ) were observed across N treatments for any cultivar, relaxation analysis resolved NPQ into distinct components and uncovered significant differences in the quantum yield of photoinhibitory quenching (ΦqI). These results indicated that using ΦNPQ alone can mask important cultivar- and N-dependent adjustments in photoprotection. Based on these analyses and hierarchical clustering, we identified cultivars with favorable fluorescence-based energy partitioning traits (characterized by higher ΦPSII and PCCP) under different N levels: Junyu535 under LN, Kehua 666 under MN, and both Kehua 666 and Zhengdan 958 under HN. Collectively, this study provides a comprehensive quantification of energy partitioning across maize cultivars under contrasting N conditions, providing physiological indicators potentially useful for screening cultivars.

The dual challenges of climate change and food security call for innovative solutions that simultaneously enhance crop yields and promote soil carbon sequestration. Here, we propose a paradigm shift in crop breeding toward the development of “high-carbon crops”—cultivars that couple high productivity with enhanced soil carbon input and stabilization, contributing to climate mitigation rather than increased carbon emissions. We begin by evaluating progress in breeding crops for yield and biomass-related traits, with a particular emphasis on the largely untapped potential of belowground biomass. We discuss whether this decoupling between yield improvement and root growth is inevitable or if it can be overcome through breeding. We then present a trait-based framework for developing “high-carbon crops” by integrating aboveground (e.g. photosynthetic efficiency and carbon partitioning) and belowground traits (e.g. root size, architecture, exudation and lignin content). While shoot biomass contributes to soil organic carbon (SOC) accumulation when residues are retained, empirical evidence highlights the crucial role of root traits in long-term carbon stabilization. At a given level of carbon input, breeding for deeper roots, enhanced exudation, and more recalcitrant biochemical composition can substantially improve the efficiency of SOC accumulation. By aligning yield-oriented breeding with carbon-optimizing traits, we advocate a win-win strategy for sustainable agriculture that achieves both food security and carbon neutrality.

Flexible adaptation to different light intensities found in natural environments is crucial for efficient photosynthesis and yield production in crops. The ability to cope with suboptimal light conditions effectively and efficiently is clearly advantageous. In this study, increased photosynthetic ability, biomass accumulation, grain yield and high membrane lipid contents were observed in OsMGD1-overexpression plants of rice and tobacco under both low and high light conditions. Further exploration of the photosynthetic performance and xanthophyll cycle-dependent photoprotection in these transgenic plants revealed that under low light conditions, the overexpression lines maintained high levels of chlorophyll content and light harvesting capability, leading to a high photosynthetic quantum yield. While under high light conditions, the de-epoxidation status of xanthophyll cycle pigments was higher in the overexpression plants, leading to sufficient photoprotection and reduced photo-oxidative damage, resulting in an increased electron transport rate. These results indicate that OsMGD1 is involved in regulating photosynthetic processes when plants are exposed to different light intensities, providing an effective strategy for achieving improved photosynthesis and crop production under variable light conditions in nature.

Previous studies have demonstrated galactolipid modification was involved in drought-induced leaf senescence. Under drought stress, overactivation of the photosynthetic electron transfer chain leads to excessive light energy absorption, resulting in photooxidative damage to crops. The xanthophyll cycle, a key photoprotective mechanism, mitigates light-induced damage by dissipating excess energy as heat. However, the role of the xanthophyll cycle pigments and photosynthetic electron transport in the process of galactolipid modification alleviates drought-induced leaf senescence has not yet been clarified clearly. In this study, a comparative experiment was conducted to investigate changes in the xanthophyll cycle and photosynthetic electron transport during drought and re-watering in two maize varieties: a drought-tolerant variety (Liangyu66) and a senescent variety (Liangyu99). Drought stress induced more severely wilted and leaf senescence in Liangyu99, with lower shoot biomass, photosynthetic rate, chlorophyll a/b, monogalactosyldiacylglycerol (MGDG), digalactosyldiacylglycerol (DGDG) content, corresponding gene expression level and DGDG/MGDG ratio compared to Liangyu66. Furthermore, PSII electron transport rate (ETRⅡ), the PSI electron transport rate (ETRⅠ), and cyclic electron flow (CEF) in Liangyu66 were 14 %, 47 %, and 83 % higher, respectively, than in Liangyu99 under drought stress. Notably, the de-epoxidation state of the xanthophyll cycle (A + Z)/(A + Z + V) was significantly higher in Liangyu66 than in Liangyu99. Non-photochemical quenching (NPQ) increased in both varieties under drought stress, Liangyu66 displayed a higher NPQ than Liangyu99. These findings suggest that galactolipid modification alleviates drought-induced leaf senescence by enhancing the xanthophyll cycle and optimizing photosynthetic electron transport.

Saline-alkali soil imposes severe adverse effects on soil utilization and agriculture production worldwide. Amelioration of saline-alkali soil is crucial to ensure global food security and promote sustainable agricultural development. Here, the effects of the combined application of soil amendment desulfurization gypsum (G) and KIA (K, an industrial organic by-product) on soil improvement and plant growth were investigated. Two experiments, a soil column leaching test and a pot experiment for plant growth, were carried out. The results showed that the combined application of G and K reduced soil pH significantly. Although the soil Na+ contents had no change in the combined treatments, the K+, Ca2+ and Mg2+ contents were significantly higher, and the HCO3− and Cl− contents were significantly lower, compared to the control. Furthermore, maize plants exhibited a higher photosynthetic rate and greater dry weight in the combined treatments. Additionally, after plant growth, the soil enzyme activities increased. These results showed that the combined application of G and K could have a more favorable impact on soil improvement by reducing soil pH, enhancing soil ion exchange, increasing soil nutrient contents, and promoting plant growth. Our study suggests that KIA is an effective and eco-friendly soil amendment for improving saline-alkali soil.

In arid and semi-arid regions, leaf-level intrinsic water use efficiency (WUEi) and photosynthetic performance index (PIabs) are critical traits for climate resilience. WUEi depends on both the photosynthetic rate (Pn) and stomatal conductance (gs), while PIabs integrate antenna size, energy-trapping capacity, and electron transport efficiency. Genotypic variation in WUEi and PIabs has been well studied, however, the contributions of their constituent traits to this variation remain unexplored in dryland maize. To bridge this knowledge gap, we conducted a two-year field study on China's Loess Plateau, aiming to: (1) quantify genotypic variation in WUEi and PIabs across maize hybrids, and (2) identify the dominant physiological components underlying this variation using machine learning approach. Field experiments revealed 1.5- to 1.7-fold genotypic variation in Pn and WUEi, respectively. Random forest analysis identified gs as the primary modulator of WUEi differences (%IncMSE: 26.1 in 2023; 38.1 in 2024). PIabs ranged from 0.71 to 1.39 in 2023 and from 1.39 to 2.01 in 2024, with electron transport efficiency beyond QA- (ψEo) emerging as the main contributor to PIabs variation in both years. Linear regression indicated WUEi was negatively related to PIabs (2023: y=-8.26x+153.96; 2024: y=-36.36x+214.98), revealing a potential physiological trade-off between water conservation and photosynthetic performance for dryland maize. These findings clarify the contributions of individual component traits underlying genotypic variation in WUEi and PIabs, offering valuable guidance for the selection and breeding of maize hybrids optimized for dryland environments.

Increasing soil carbon sequestration is one of the main measures to mitigate greenhouse gas (GHG) emissions in agricultural systems, and straw-derived biochar returning has the potential to increase soil carbon sequestration and crop yield, mitigate GHG emissions, but its application is largely restricted due to the high input. It remains unclear whether periodic application of straw-derived biochar could effectively meet these challenges. To explore the appropriate mode of straw-derived biochar returning which aims to achieve the goal of increasing yield and carbon sequestration without reducing economic benefits, a 7-year site experiment was carried out to compare the effects of conventional tillage, wheat straw returning and straw-derived biochar returning on winter wheat yield, soil organic carbon (SOC) contents, GHG emissions and economic benefits on the Loess Plateau of China. The highest average yield over the 7-year experiment was found under straw biochar, and average yield over the 7-year experiment was increased by 9.94 % and 2.28 %, as compared with conventional tillage and wheat straw, respectively. Meanwhile, under straw biochar the SOC content was significantly increased by 24.61 % and 12.57 % than conventional tillage and wheat straw after 7 years (p < 0.05). In addition, compared to conventional tillage and wheat straw, straw biochar increased the annual cumulative CO2 emissions, but reduced the annual cumulative N2O emissions; the net global warming potential under straw biochar decreased by 7.7 and 1.1 times (p < 0.05), and the greenhouse gas emission intensity decreased by 8.6 and 1.6 times (p < 0.05), those were mainly due to the fact that straw biochar increased wheat yield and SOC, but reduced N2O emissions. The 5-year cumulative net income and cumulative net ecosystem economic benefits under straw biochar were significantly increased by 12.16 % and 20.27 % compared to the conventional tillage, while the 7year net ecosystem economic benefits was comparable to the wheat straw (p < 0.05). Taken together, our results suggest that the application of straw-derived biochar every five years could effectively increase carbon sequestration and mitigate GHG emissions, while maintaining the income simultaneously. Therefore, that the periodic straw-derived biochar returning could be an effective approach in rainfed agriculture of dryland, considering both economic and environmental effects.

Severe soil erosion has led to large-scale sloping farmland degradation and destruction in the Mollisol of Northeast China. Intercropping cover crops with the main crop is a potential agroecological practice to reduce soil erosion in the current intensive cropping systems, if the grain yield of the main crop is not compromised. In this study, we intercropped six cover crops (calopo, pigeon pea, Chinese milk vetch, oilseed rape, oilseed radish and woad) with contrasting functional traits in the furrow of maize ridge cropping system to evaluate their effects on maize grain yield and soil erosion. The field experiment was conducted in 2022 and 2023 on a 4.2 degrees slope farmland in the Mollisol region of Northeast China. The results showed that the effects of cover crop intercropping on maize grain yield and soil erosion control varied with cover crop species and their phenological and morphological characteristics. Cover crops, which emerged late and had relatively low plant height and aboveground biomass in the early growth stages of maize, had no significant effect on maize growth. In terms of soil erosion control, cover crops with higher stem density and stem diameter density provided more effective soil erosion control. Based on agronomic and environmental evaluations, Chinese milk vetch and woad are the most suitable cover crops for maize/cover crop intercropping systems, which increased maize yield by 0.6-13.5% and reduced annual soil loss by 80.6-88.3%. These results justify that intercropping suitable cover crops with maize is an effective soil erosion control strategy that ensures high yield production without changes in existing mechanized farming practices on sloping farmland in the Mollisol region of Northeast China.

The bHLH gene family, one of the most abundant transcription factor families in plants, plays crucial roles in stress resistance, growth, and development. To explore the characteristics of the potato bHLH gene family members, this study identified and analyzed a total of 134 bHLH genes. Using bioinformatics approaches, we examined their physicochemical properties, conserved structural domains, motifs, and cis-acting elements. Additionally, a phylogenetic analysis was conducted, comparing the bHLH proteins of potato with those of the model plant Arabidopsis thaliana. The study also investigated the expression patterns of StbHLH genes under different environmental conditions and growth stages. The potato bHLH gene family is enriched with various cis-acting elements associated with stress response and plant hormone signaling. The expression patterns of StbHLH genes varied significantly across different conditions, revealing their potential roles in stress resistance and developmental processes. For example, under drought and re-watering treatments, distinct expression patterns were observed, with specific genes showing upregulation or downregulation at different time points. StbHLH025 regulates tissue development and stress response in potato. These findings not only reveal the diversity and complexity of the potato bHLH gene family but also provide valuable insights for future research into the functions of StbHLH genes, particularly their roles in potato stress resistance and developmental processes.

Phosphorus (P) is essential for plant growth but is frequently limited in soils. Lespedeza species are well-known for their ecological and economic benefits, as well as their tolerance to nutrient-poor soils. This study investigated the P acquisition strategies and adaptive mechanisms of three Lespedeza species (L. davurica, L. bicolor, and L. cuneata), focusing on biomass allocation, P distribution, root exudation, and absorption kinetics under P deficiency. Under P deficiency, L. davurica and L. bicolor allocated more biomass to roots to enhance P acquisition, whereas L. cuneata increased specific root length and area. Moreover, all three species preferentially allocated P to roots, but L. bicolor showed higher P content in stems and leaves than the others. P absorption kinetics indicated that Michaelis constant (Km) and equilibrium concentration (Cmin) were significantly decreased in all three species under P deficiency, with L. bicolor exhibiting the strongest P affinity and acquisition capacity. Secretion analysis revealed that while L. davurica and L. cuneata secreted higher levels of organic acids under P deficiency, exudates from L. bicolor were significantly enriched in acid phosphatase activity. Overall, the three Lespedeza species developed distinct P acquisition and adaptive strategies to cope with P deficiency, with L. bicolor demonstrating the greatest low-P tolerance and most efficient adaptive mechanisms.

Nitrogen and water interact synergistically to affect plant growth and crop productivity. Despite intensive research, the genetic and regulatory mechanisms of water‑nitrogen interactions remain unclear. In this study, we combined meta-QTL and RNA sequencing (RNA-Seq) to identify 18 candidate genes, with ZmVQ56 selected for functional analysis. The low nitrogen and drought-tolerant genotype 'TY6' and the sensitive genotype 'GEMS9' were used under four water‑nitrogen treatments: well-watered and normal nitrogen, water stress and normal nitrogen, well-watered and low nitrogen, and water stress and low nitrogen. We identified 3430 differentially expressed genes (DEGs) in roots and 7703 DEGs in leaves. Integrating meta-QTL, gene expression, and functional annotation identified ZmVQ56 as a candidate gene involved in water‑nitrogen interactions. Since the maize transgenic material has not yet been obtained, Arabidopsis thaliana was used for functional analysis. Functional analysis in Arabidopsis showed that overexpression of ZmVQ56 reduced primary root length, fresh weight, and shoot nitrate content under low nitrogen and drought conditions, while the atsib1 mutant (homologous of ZmVQ56) exhibited opposite results. These findings provide insights into the genetic basis of water‑nitrogen interactions and suggest a role for ZmVQ56 in regulating low nitrogen and drought tolerance, offering potential for molecular breeding in maize.

Land use and land cover (LULC) has undergone drastic changes with the rapid growth of the global population, economic development, and the expansion of agricultural activities. However, the uncertainty of classification algorithms and image resolution based on satellite data for land cover mapping, particularly cropland cover mapping, needs to be investigated sufficiently. In this study, the influence of different spatial-resolution images on classification results was explored by comparing the differences between four machine learning algorithms for LULC mapping. The classification results of this model were also compared with existing global land cover datasets to determine whether the model was capable of producing reliable results. According to the results of this study, the random forest (RF) classifier outperformed the support vector machine (SVM), decision tree (DT), and artificial neural network (ANN) with an overall accuracy (OA) and kappa coefficient of 81.99% and 0.78, respectively. However, SVM and ANN showed greater accuracy on the water class and unused land class, respectively. With increasing spatial resolution, RF’s accuracy increased initially and then decreased when classifying images with five different spatial resolutions (30 m, 16 m, 10 m, 8 m, and 2 m). In particular, with an OA of 82.54% and a kappa coefficient of 0.78, RF performed the best on images with 8 m resolution. Additionally, the RF-based image with 8 m resolution produced a higher OA of 0.88 for cropland. Topography is the main factor that determines the classification performance of different-resolution images. The classification accuracies of RF10 m and RF30 m (10 m and 30 m resolution images, respectively, using RF) were higher (OAs of 93.59% and 94.59%, respectively) than those of the global land cover dataset (LC10 m and LC30 m, land cover images with 10 m and 30 m resolution, respectively), whose high-resolution images showed more details of the land cover. The results of this study highlight that classification algorithms and image resolution are the sources of uncertainty for land mapping. Obtaining reliable land cover mapping requires the use of appropriate classification algorithms and spatial resolution. With these results, it will be possible to develop a national land monitoring system and basic ecological climate models using LULC.

Exploring the effects of different additives on the improvement of newly cultivated farmland in mountainous areas can provide rational soil fertilization plans for regions lacking means of production. We conducted a paddy planting experiment in Ankang City, Shaanxi Province. Six treatments were set up, including sole chemical fertilizer (CK); fertilizer + bacteria agent (NB); chemical fertilizer + alginate bio-organic fertilizer (NO); fertilizer + fulvic acid biomass nutrient solution (NF); chemical fertilizer + acid soil conditioner (NC); fertilizer + silicon–calcium–magnesium–potassium fertilizer (NSi). We collected topsoil samples after paddy harvest, analyzed their physical, chemical, and biological properties, and selected indicators to construct a Total Data Set (TDS) and a Minimum Data Set (MDS). The Soil Quality Index (SQI) was used to evaluate the soil improvement effects after different fertilization regimes. The SQI calculated by the TDS and the MDS showed that the SQI after NF treatment was higher than that under other treatments. The SQI based on the TDS (SQITDS) and the SQI based on the MDS (SQIMDS) were significantly positively correlated with yield. The SQI calculated based on both the TDS and the MDS can objectively reflect the soil fertility quality. The paddy yield and total dry matter accumulation were the highest under the NF treatment, and the SQI was the largest. Thus, the effect of chemical fertilizer combined with fulvic acid biomass nutrient solution on soil fertility was the most significant.

In drylands, where the annual precipitation is low and erratic, improving the water storage capacity and the available water in the soil is crucial for crop production. To explore the effect of long-term agronomic management on water storage capacity and available water in the soil, four agronomic management systems were used (including the farmer’s management model (FM), the high nitrogen input model (HN), the manure amendment model (MM), and the biochar amendment model (BM)) for eight consecutive years, and the variation in wheat yield and soil hydraulic, physical, and chemical properties in the 0–100 cm soil profile were investigated. The management practices varied in terms of seeding rates, nitrogen (N)-application strategies, and the application of manure or biochar. The results showed that, under the manure amendment model (MM), the wheat yield was increased by 17–35%, and the water-use efficiency was increased by 14–29% when compared to the farmer’s management model (FM) and the high nitrogen input model (HN). However, no significant differences in wheat yield and water-use efficiency were found under the biochar amendment model (BM) compared to the HN. The high yield and water-use efficiency under the MM were mainly due to the higher saturated hydraulic conductivity, soil saturated water content, field capacity, and soil available water content, which led to an increase in the available water storage in the 0–100 cm soil profile by 29–48 mm. Furthermore, the MM also improved soil organic matter, porosity, root length density, and root weight density and reduced the soil bulk density, which are beneficial for the improvement of the above soil hydraulic properties. Therefore, it is a practical way to ensure high yield and high efficiency of crops in dryland by improving water storage capacity and the available water in the soil, which can be profoundly regulated by agronomic management.

Heat shock proteins (Hsps), acting as molecular chaperones, play a pivotal role in plant responses to environmental stress. In this study, we found a total of 192 genes encoding Hsps, which are distributed across all 12 chromosomes, with higher concentrations on chromosomes 1, 2, 3, and 5. These Hsps can be divided into six subfamilies (sHsp, Hsp40, Hsp60, Hsp70, Hsp90, and Hsp100) based on molecular weight and homology. Expression pattern data indicated that these Hsp genes can be categorized into three groups: generally high expression in almost all tissues, high tissue-specific expression, and low expression in all tissues. Further analysis of 15 representative genes found that the expression of 14 Hsp genes was upregulated by high temperatures. Subcellular localization analysis revealed seven proteins localized to the endoplasmic reticulum, while others localized to the mitochondria, chloroplasts, and nucleus. We successfully obtained the knockout mutants of above 15 Hsps by the CRISPR/Cas9 gene editing system. Under natural high-temperature conditions, the mutants of eight Hsps showed reduced yield mainly due to the seed setting rate or grain weight. Moreover, the rice quality of most of these mutants also changed, including increased grain chalkiness, decreased amylose content, and elevated total protein content, and the expressions of starch metabolism-related genes in the endosperm of these mutants were disturbed compared to the wild type under natural high-temperature conditions. In conclusion, our study provided new insights into the HSP gene family and found that it plays an important role in the formation of rice quality and yield.

Transitory starch is an important carbon source in leaves, and its biosynthesis and metabolism are closely related to grain quality and yield. The molecular mechanisms controlling leaf transitory starch biosynthesis and degradation and their effects on rice (Oryza sativa) quality and yield remain unclear. Here, we show that OsLESV and OsESV1, the rice orthologs of AtLESV and AtESV1, are associated with transitory starch biosynthesis in rice. The total starch and amylose contents in leaves and endosperms are significantly reduced, and the final grain quality and yield are compromised in oslesv and osesv1 single and oslesv esv1 double mutants. Furthermore, we found that OsLESV and OsESV1 bind to starch, and this binding depends on a highly conserved C-terminal tryptophan-rich region that acts as a starch-binding domain. Importantly, OsLESV and OsESV1 also interact with the key enzymes of starch biosynthesis, granule-bound starch synthase I (GBSSI), GBSSII, and pyruvate orthophosphote dikiase (PPDKB), to maintain their protein stability and activity. OsLESV and OsESV1 also facilitate the targeting of GBSSI and GBSSII from plastid stroma to starch granules. Overexpression of GBSSI, GBSSII, and PPDKB can partly rescue the phenotypic defects of the oslesv and osesv1 mutants. Thus, we demonstrate that OsLESV and OsESV1 play a key role in regulating the biosynthesis of both leaf transitory starch and endosperm storage starch in rice. These findings deepen our understanding of the molecular mechanisms underlying transitory starch biosynthesis in rice leaves and reveal how the transitory starch metabolism affects rice grain quality and yield, providing useful information for the genetic improvement of rice grain quality and yield.

Northeast China is known as the “Corn Belt” of China. Long-term conventional tillage has led to severe soil degradation, threatening the food production and China’s food security. Regenerative farming practices such as no-tillage and deep ploughing have proven effective in protecting soil and promoting sustainable agriculture. However, the effects of no-tillage and deep ploughing on corn yield are hotly debated, and their regional suitability in Northeast China remains unclear. As a solution, a regional machine learning aided meta-analysis was performed to assess the effects of field management practices, climate conditions, and soil properties on crop productivity of no-tillage and deep ploughing versus conventional tillage, and to evaluate the probability of yield increase under no-tillage and deep ploughing across Northeast China. The results showed that the overall effect of no-tillage and deep ploughing significantly increased corn yield by 5.1% and 6.4%, respectively, compared to conventional tillage. Climate conditions had the greatest importance on crop yield under no-tillage, while management practices were the most explainable variable under deep ploughing. Data driven models reveled that the probabilities of yield increase under no-tillage and deep ploughing had large geographical differences. No-tillage performed better in warm arid regions with alkaline soil and low initial soil organic matter. In cold and humid areas with neutral soil and high soil organic matter content, deep ploughing had the greatest possibility of increasing yield. Our study revealed the effects and importance of factors affecting crop productivity of no-tillage and deep ploughing, which helps to optimize these practices. Furthermore, our results provide a reference for agricultural managers to select appropriate tillage practices that simultaneously contribute to food production and sustainable agricultural goals in specific regions of Northeast China.

Changes of membrane lipid composition contribute to plant adaptation to various abiotic stresses. Here, a comparative study was undertaken to investigate the mechanisms of how lipid alteration affects plant growth and development under nitrogen (N) deficiency. Two wheat cultivars: the N deficiency-tolerant cultivar Xiaoyan 6 (XY) and the N deficiency-sensitive cultivar Aikang 58 (AK) were used to test if the high N-deficiency tolerance was related with lipid metabolism. The results showed that N deficiency inhibited the morpho-physiological parameters in both XY and AK cultivars, which showed a significant decrease in biomass, N content, photosynthetic efficiency, and lipid contents. However, these decreases were more pronounced in AK than XY. In addition, XY showed a notable increase in fatty acid unsaturation, relatively well-maintained chloroplast ultrastructure, and minimized damage of lipid peroxidation and enhanced PSII activity under N-deficient condition, as compared with AK. Transcription levels of many genes involved in lipid biosynthesis and fatty acid desaturation were up-regulated in response to N deficiency in two wheat cultivars, while the expressions were much higher in XY than AK under N deficiency. These results highlight the importance of alterations in lipid metabolism in N deficiency tolerance in wheat. High levels of lipid content and unsaturated fatty acids maintained the membrane structure and function, contributing to high photosynthesis and antioxidant capacities, thereby improved the tolerance to N deficiency.