Agricultural waste-based modified biochars differentially affected the soil properties, growth, and nutrient accumulation by maize (Zea mays L.) plants.

Biochar (BC) is an organic compound formed by the pyrolysis of organic wastes. Application of BCs as soil amendments has many benefits including carbon sequestration, enhanced soil fertility and sustainable agriculture production. In the present study, we acidified the different BCs prepared from rice straw, rice husk, wheat straw, cotton stalk, poultry manure, sugarcane press mud and vegetable waste; following which, we applied them in a series of pot experiments. Comparisons were made between acidified and non- acidified BCs for their effects on seed germination, soil properties (EC, pH) nutrient contents (P, K, Na) and organic matter. The treatments comprised of a control, and all above-described BCs (acidified as well as non-acidified) applied to soil at the rate of 1% (w/w). The maize crop was selected as a test crop. The results showed that acidified poultry manure BC significantly improved germination percentage, shoot length, and biomass of maize seedlings as compared to other BCs and their respective control plants. However, acidified BCs caused a significant decrease in nutrient contents (P, K, Na) of soil,maize seedlings, and the soil organic matter contents as compared to non- acidified BCs. But when compared with control treatments, all BCs treatments (acidified and non-acidified) delivered higher levels of nutrients and organic matter contents. It was concluded that none of the BCs (acidified and non-acidified) had caused negative effect on soil conditions and growth of maize. In addition, the acidification of BC prior to its application to alkaline soils might had altered soil chemistry and delivered better maize growth. Moving forward, more research is needed to understand the long-term effects of modified BCs on nutrient dynamics in different soils. In addition, the possible effects of BC application timings, application rates, particle size, and crop species have to be evaluated systemtically.

Multifractal analysis of maize and soybean DNA.

This paper investigates the complexity of DNA sequences in maize and soybean using the multifractal detrended fluctuation analysis (MF-DFA) method, chaos game representation (CGR), and the complexity-entropy plane approach. The study aims to understand the patterns and structures of these DNA sequences, which can provide insights into their genetic makeup and improve crop yield and quality. The results show that maize and soybean DNA sequences exhibit fractal properties, indicating a complex and self-organizing structure. We observe the persistence trend between sequences of base pairs, which indicates long-range correlations between base pairs. We also identified the stochastic nature of the DNA sequences of both species.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India.

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards.

Spatial and temporal distribution of optimal maize sowing dates in Nigeria.

Climate change and inter-annual variability cause variation in rainfall commencement and cessation which has consequences for the maize growing season length and thus impact yields. This study therefore sought to determine the spatially explicit optimum maize sowing dates to enable site specific recommendations in Nigeria. Gridded weather and soil data, crop management and cultivar were used to simulate maize yield from 1981-2019 at a scale of 0.5°. A total of 37 potential sowing dates between 1 March and 7 November at an interval of 7 days for each year were evaluated. The optimum sowing date was the date which maximizes yield at harvest, keeping all other management factors constant. The results show that optimum sowing dates significantly vary across the country with northern Nigeria having notably delayed sowing dates compared to southern Nigeria which has earlier planting dates. The long-term optimal sowing dates significantly (p<0.05), shifted between the 1980s (1981-1990), and current (2011-2019), for most of the country. The most optimum planting dates of southern Nigeria shifted to later sowing dates while most optimum sowing dates of central and northern Nigeria shifted to earlier sowing dates. There was more variation in optimum sowing dates in the wetter than the drier agro-ecologies. Changes in climate explain changes in sowing dates in wetter agro-ecologies compared to drier agro-ecologies. The study concludes that the optimum sowing dates derived from this study and the corresponding methodology used to generate them can be used to improve cropping calendars in maize farming in Nigeria.

Maize leaf disease recognition using PRF-SVM integration: a breakthrough technique.

The difficulty of collecting maize leaf lesion characteristics in an environment that undergoes frequent changes, suffers varying illumination from lighting sources, and is influenced by a variety of other factors makes detecting diseases in maize leaves difficult. It is critical to monitor and identify plant leaf diseases during the initial growing period to take suitable preventative measures. In this work, we propose an automated maize leaf disease recognition system constructed using the PRF-SVM model. The PRFSVM model was constructed by combining three powerful components: PSPNet, ResNet50, and Fuzzy Support Vector Machine (Fuzzy SVM). The combination of PSPNet and ResNet50 not only assures that the model can capture delicate visual features but also allows for end-to-end training for smooth integration. Fuzzy SVM is included as a final classification layer to accommodate the inherent fuzziness and uncertainty in real-world image data. Five different maize crop diseases (common rust, southern rust, grey leaf spot, maydis leaf blight, and turcicum leaf blight along with healthy leaves) are selected from the Plant Village dataset for the algorithm's evaluation. The average accuracy achieved using the proposed method is approximately 96.67%. The PRFSVM model achieves an average accuracy rating of 96.67% and a mAP value of 0.81, demonstrating the efficacy of our approach for detecting and classifying various forms of maize leaf diseases.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Sweet corn association panel and genome-wide association analysis reveal loci for chilling-tolerant germination.

Sweet corn is highly susceptible to the deleterious effects of low temperatures during the initial stages of growth and development. Employing a 56K chip, high-throughput single-nucleotide polymorphism (SNP) sequencing was conducted on 100 sweet corn inbred lines. Subsequently, six germination indicators-germination rate, germination index, germination time, relative germination rate, relative germination index, and relative germination time-were utilized for genome-wide association analysis. Candidate genes were identified via comparative analysis of homologous genes in Arabidopsis and rice, and their functions were validated using quantitative real-time polymerase chain reaction (qRT-PCR). The results revealed 35,430 high-quality SNPs, 16 of which were significantly correlated. Within 50 kb upstream and downstream of the identified SNPs, 46 associated genes were identified, of which six were confirmed as candidate genes. Their expression patterns indicated that Zm11ΒHSDL5 and Zm2OGO likely play negative and positive regulatory roles, respectively, in the low-temperature germination of sweet corn. Thus, we determined that these two genes are responsible for regulating the low-temperature germination of sweet corn. This study contributes valuable theoretical support for improving sweet corn breeding and may aid in the creation of specific germplasm resources geared toward enhancing low-temperature tolerance in sweet corn.

Titanium dioxide nanoparticles alleviates polystyrene nanoplastics induced growth inhibition by modulating carbon and nitrogen metabolism via melatonin signaling in maize.

BACKGROUND: Nanoplastics, are emerging pollutants, present a potential hazard to food security and human health. Titanium dioxide nanoparticles (Nano-TiO2), serving as nano-fertilizer in agriculture, may be important in alleviating polystyrene nanoplastics (PSNPs) toxicity. RESULTS: Here, we performed transcriptomic, metabolomic and physiological analyzes to identify the role of Nano-TiO2 in regulating the metabolic processes in PSNPs-stressed maize seedlings (Zea mays L.). The growth inhibition by PSNPs stress was partially relieved by Nano-TiO2. Furthermore, when considering the outcomes obtained from RNA-seq, enzyme activity, and metabolite content analyses, it becomes evident that Nano-TiO2 significantly enhance carbon and nitrogen metabolism levels in plants. In comparison to plants that were not subjected to Nano-TiO2, plants exposed to Nano-TiO2 exhibited enhanced capabilities in maintaining higher rates of photosynthesis, sucrose synthesis, nitrogen assimilation, and protein synthesis under stressful conditions. Meanwhile, Nano-TiO2 alleviated the oxidative damage by modulating the antioxidant systems. Interestingly, we also found that Nano-TiO2 significantly enhanced the endogenous melatonin levels in maize seedlings. P-chlorophenylalanine (p-CPA, a melatonin synthesis inhibitor) declined Nano-TiO2-induced PSNPs tolerance. CONCLUSIONS: Taken together, our data show that melatonin is involved in Nano-TiO2-induced growth promotion in maize through the regulation of carbon and nitrogen metabolism.

Maize/soybean intercropping increases nutrient uptake, crop yield and modifies soil physio-chemical characteristics and enzymatic activities in the subtropical humid region based in Southwest China.

Intercropping, a widely adopted agricultural practice worldwide, aims to increase crop yield, enhance plant nutrient uptake, and optimize the utilization of natural resources, contributing to sustainable farming practices on a global scale. However, the underlying changes in soil physio-chemical characteristics and enzymatic activities, which contribute to crop yield and nutrient uptake in the intercropping systems are largely unknown. Consequently, a two-year (2021-2022) field experiment was conducted on the maize/soybean intercropping practices with/without nitrogen (N) fertilization (i.e., N0; 0 N kg ha-1 and N1; 225 N kg ha-1 for maize and 100 N kg ha-1 for soybean ) to know whether such cropping system can improve the nutrients uptake and crop yields, soil physio-chemical characteristics, and soil enzymes, which ultimately results in enhanced crop yield. The results revealed that maize intercropping treatments (i.e., N0MI and N1MI) had higher crop yield, biomass dry matter, and 1000-grain weight of maize than mono-cropping treatments (i.e., N0MM, and N1MM). Nonetheless, these parameters were optimized in N1MI treatments in both years. For instance, N1MI produced the maximum grain yield (10,105 and 11,705 kg ha-1), biomass dry matter (13,893 and 14,093 kg ha-1), and 1000-grain weight (420 and 449 g) of maize in the year 2021 and 2022, respectively. Conversely, soybean intercropping treatments (i.e., N0SI and N1SI) reduced such yield parameters for soybean. Also, the land equivalent ratio (LER) and land equivalent ratio for N fertilization (LERN) values were always greater than 1, showing the intercropping system's benefits in terms of yield and improved resource usage. Moreover, maize intercropping treatments (i.e., N0MI and N1MI) and soybean intercropping treatments (i.e., N0SI and N1SI) significantly (p < 0.05) enhanced the nutrient uptake (i.e., N, P, K, Ca, Fe, and Zn) of maize and soybean, however, these nutrients uptakes were more prominent in N1MI and N1SI treatments of maize and soybean, respectively in both years (2021 and 2022) compared with their mono-cropping treatments. Similarly, maize-soybean intercropping treatments (i.e., N0MSI and N1MSI) significantly (p < 0.05) improved the soil-based N, P, K, NH4, NO3, and soil organic matter, but, reduced the soil pH. Such maize-soybean intercropping treatments also improved the soil enzymatic activities such as protease (PT), sucrose (SC), acid phosphatase (AP), urease (UE), and catalase (CT) activities. This indicates that maize-soybean intercropping could potentially contribute to higher and better crop yield, enhanced plant nutrient uptake, improved soil nutrient pool, physio-chemical characteristics, and related soil enzymatic activities. Thus, preferring intercropping to mono-cropping could be a preferable choice for ecologically viable agricultural development.

Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system.

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar's anthesis and physiological maturity, with observed value falling within 5% of the model's predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9-16%. The study also demonstrated the model's ability to accurately capture soil nitrate-N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop's growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

A spatial transcriptome map of the developing maize ear.

A comprehensive understanding of inflorescence development is crucial for crop genetic improvement, as inflorescence meristems give rise to reproductive organs and determine grain yield. However, dissecting inflorescence development at the cellular level has been challenging owing to a lack of specific marker genes to distinguish among cell types, particularly in different types of meristems that are vital for organ formation. In this study, we used spatial enhanced resolution omics-sequencing (Stereo-seq) to construct a precise spatial transcriptome map of the developing maize ear primordium, identifying 12 cell types, including 4 newly defined cell types found mainly in the inflorescence meristem. By extracting the meristem components for detailed clustering, we identified three subtypes of meristem and validated two MADS-box genes that were specifically expressed at the apex of determinate meristems and involved in stem cell determinacy. Furthermore, by integrating single-cell RNA transcriptomes, we identified a series of spatially specific networks and hub genes that may provide new insights into the formation of different tissues. In summary, this study provides a valuable resource for research on cereal inflorescence development, offering new clues for yield improvement.

Exploring the dynamics of ISR signaling in maize upon seed priming with plant growth promoting actinobacteria isolated from tea rhizosphere of Darjeeling.

Plant growth-promoting rhizobacteria (PGPR) offer an eco-friendly alternative to agrochemicals for better plant growth and development. Here, we evaluated the plant growth promotion abilities of actinobacteria isolated from the tea (Camellia sinensis) rhizosphere of Darjeeling, India. 16 S rRNA gene ribotyping of 28 isolates demonstrated the presence of nine different culturable actinobacterial genera. Assessment of the in vitro PGP traits revealed that Micrococcus sp. AB420 exhibited the highest level of phosphate solubilization (i.e., 445 ± 2.1 µg/ml), whereas Kocuria sp. AB429 and Brachybacterium sp. AB440 showed the highest level of siderophore (25.8 ± 0.1%) and IAA production (101.4 ± 0.5 µg/ml), respectively. Biopriming of maize seeds with the individual actinobacterial isolate revealed statistically significant growth in the treated plants compared to controls. Among them, treatment with Paenarthrobacter sp. AB416 and Brachybacterium sp. AB439 exhibited the highest shoot and root length. Biopriming has also triggered significant enzymatic and non-enzymatic antioxidative defense reactions in maize seedlings both locally and systematically, providing a critical insight into their possible role in the reduction of reactive oxygen species (ROS) burden. To better understand the role of actinobacterial isolates in the modulation of plant defense, three selected actinobacterial isolates, AB426 (Brevibacterium sp.), AB427 (Streptomyces sp.), and AB440 (Brachybacterium sp.) were employed to evaluate the dynamics of induced systemic resistance (ISR) in maize. The expression profile of five key genes involved in SA and JA pathways revealed that bio-priming with actinobacteria (Brevibacterium sp. AB426 and Brachybacterium sp. AB440) preferably modulates the JA pathway rather than the SA pathway. The infection studies in bio-primed maize plants resulted in a delay in disease progression by the biotrophic pathogen Ustilago maydis in infected maize plants, suggesting the positive efficacy of bio-priming in aiding plants to cope with biotic stress. Conclusively, this study unravels the intrinsic mechanisms of PGPR-mediated ISR dynamics in bio-primed plants, offering a futuristic application of these microorganisms in the agricultural fields as an eco-friendly alternative.

ZmNAC17 Regulates Mesocotyl Elongation by Mediating Auxin and ROS Biosynthetic Pathways in Maize.

The mesocotyl is of great significance in seedling emergence and in responding to biotic and abiotic stress in maize. The NAM, ATAF, and CUC2 (NAC) transcription factor family plays an important role in maize growth and development; however, its function in the elongation of the maize mesocotyl is still unclear. In this study, we found that the mesocotyl length in zmnac17 loss-of-function mutants was lower than that in the B73 wild type. By using transcriptomic sequencing technology, we identified 444 differentially expressed genes (DEGs) between zmnac17-1 and B73, which were mainly enriched in the "tryptophan metabolism" and "antioxidant activity" pathways. Compared with the control, the zmnac17-1 mutants exhibited a decrease in the content of indole acetic acid (IAA) and an increase in the content of reactive oxygen species (ROS). Our results provide preliminary evidence that ZmNAC17 regulates the elongation of the maize mesocotyl.

No-tillage enhances soil water storage, grain yield and water use efficiency in dryland wheat (Triticum aestivum) and maize (Zea mays) cropping systems: a global meta-analysis.

Climate change significantly affects crop production and is a threat to global food security. Conventional tillage (CT) is the primary tillage practice in rain-fed areas to conserve soil moisture. Despite previous research on the effect of tillage methods on different cropping systems, a comparison of tillage methods on soil water storage, crop yield and crop water use in wheat (Triticum aestivum ) and maize (Zea mays ) under different soil textures, precipitation and temperature patterns is needed. We reviewed 119 published articles and used meta-analysis to assess the effects of three conservation tillage practices (NT, no-tillage; RT, reduced tillage; ST, subsoil tillage), on precipitation storage efficiency (PSE), soil water storage at crop planting (SWSp), grain yield, evapotranspiration (ET) and water use efficiency (WUE) under varying precipitation and temperature patterns and soil textures in dryland wheat and maize, with CT as the control treatment. Conservation tillage methods increased PSE, SWSp, grain yield, ET and WUE in both winter wheat-fallow and spring maize cropping systems. More precipitation water was conserved in fine-textured soils than in medium-textured and coarse-textured soils, which improved ET. Conservation tillage increased soil water conservation and yield under high mean annual precipitation (MAP) and moderate mean annual temperature (MAT) conditions in winter wheat. However, soil water conservation and yield were greater under MAP <400mm and moderate MAT. We conclude that conservation tillage could be promising for increasing precipitation storage, soil water conservation and crop yield in regions with medium to low MAPs and medium to high MATs.

Exogenous application of 5-NGS increased osmotic stress resistance by improving leaf photosynthetic physiology and antioxidant capacity in maize.

Background: Drought is a critical limiting factor affecting the growth and development of spring maize (Zea mays L.) seedlings in northeastern China. Sodium 5-nitroguaiacol (5-NGS) has been found to enhance plant cell metabolism and promote seedling growth, which may increase drought tolerance. Methods: In the present study, we investigated the response of maize seedlings to foliar application of a 5-NGS solution under osmotic stress induced by polyethylene glycol (PEG-6000). Four treatment groups were established: foliar application of distilled water (CK), foliar application of 5-NGS (NS), osmotic stress + foliar application of distilled water (D), and osmotic stress + foliar application of 5-NGS (DN). Plant characteristics including growth and photosynthetic and antioxidant capacities under the four treatments were evaluated. Results: The results showed that under osmotic stress, the growth of maize seedlings was inhibited, and both the photosynthetic and antioxidant capacities were weakened. Additionally, there were significant increases in the proline and soluble sugar contents and a decrease in seedling relative water content (RWC). However, applying 5-NGS alleviated the impact of osmotic stress on maize seedling growth parameters, particularly the belowground biomass, with a dry mass change of less than 5% and increased relative water content (RWC). Moreover, treatment with 5-NGS mitigated the inhibition of photosynthesis caused by osmotic stress by restoring the net photosynthetic rate (Pn) through an increase in chlorophyll content, photosynthetic electron transport, and intercellular CO2 concentration (Ci). Furthermore, the activity of antioxidant enzymes in the aboveground parts recovered, resulting in an approximately 25% decrease in both malondialdehyde (MDA) and H2O2. Remarkably, the activity of enzymes in the underground parts exhibited more significant changes, with the contents of MDA and H2O2 decreasing by more than 50%. Finally, 5-NGS stimulated the dual roles of soluble sugars as osmoprotectants and energy sources for metabolism under osmotic stress, and the proline content increased by more than 30%. We found that 5-NGS played a role in the accumulation of photosynthates and the effective distribution of resources in maize seedlings. Conclusions: Based on these results, we determined that foliar application of 5-NGS may improve osmotic stress tolerance in maize seedlings. This study serves as a valuable reference for increasing maize yield under drought conditions.

How does climate change affect potential yields of four staple grain crops worldwide by 2030?

Global food security basically depends on potential yields of staple grain crops worldwide, especially under climate change. However, most scholars use various models of production function in which climatic factors are often considered to estimate crop yield mostly at local or regional level. Therefore, in this paper: Potential yields of rice, wheat, maize and soybean worldwide by 2030 are projected creatively using Auto-regressive Integrated Moving Average and Trend Regressed (ARIMA-TR) model in which actual yields in recent two years are used for testing the reliability of projection and Gray System (GS) model for validating the test; Especially individual impacts of climate change on the productions of rice, wheat, maize and soybean worldwide since 1961 are analyzed by using unary regression model in which global mean temperature and land precipitation are independent variable while the yield of crop being dependent one, respectively. Results show that: by 2030, the ratio between average and top yields of world rice is projected to be 50.6% increasing, while those of world wheat, world maize and world soybean are projected to be 38.0% increasing, 14.7% decreasing and 72.5% increasing, respectively. Since 1961 global warming has exerted a negative impact on average yield of world rice less than on its top, a positive effect on average yield of world wheat while a negative impact on its top, a positive effect on average yield of world maize less than on its top, and a positive influence on average yield of world soybean while a negative one on its top, which might be slightly mitigated by 'Carbon Peak' target. The fluctuation of global rainfall contributes to the productions of these crops much less than global warming during same period. Our findings indicate that: to improve global production of four staple grain crops by 2030, the priorities of input should be given to either rice or wheat in both high and low yield countries, whereas to maize in high yield countries and to soybean in low yield countries. These insights highlight some difference from previous studies, and provide academia with innovative comprehension and policy-decision makers with supportive information on sustainable production of these four staple grain crops for global food security under climate change in the future.

Promoting sustainable smallholder farming via multistakeholder collaboration.

Transforming smallholder farms is critical to global food security and environmental sustainability. The science and technology backyard (STB) platform has proved to be a viable approach in China. However, STB has traditionally focused on empowering smallholder farmers by transferring knowledge, and wide-scale adoption of more sustainable practices and technologies remains a challenge. Here, we report on a long-term project focused on technology scale-up for smallholder farmers by expanding and upgrading the original STB platform (STB 2.0). We created a formalized and standardized process by which to engage and collaborate with farmers, including integrating their feedback via equal dialogues in the process of designing and promoting technologies. Based on 288 site-year of field trials in three regions in the North China Plain over 5 y, we find that technologies cocreated through this process were more easily accepted by farmers and increased their crop yields and nitrogen factor productivity by 7.2% and 28.1% in wheat production and by 11.4% and 27.0% in maize production, respectively. In promoting these technologies more broadly, we created a "one-stop" multistakeholder program involving local government agencies, enterprises, universities, and farmers. The program was shown to be much more effective than the traditional extension methods applied at the STB, yielding substantial environmental and economic benefits. Our study contributes an important case study for technology scale-up for smallholder agriculture. The STB 2.0 platform being explored emphasizes equal dialogue with farmers, multistakeholder collaboration, and long-term investment. These lessons may provide value for the global smallholder research and practitioners.

Response of soil organic carbon to straw return in farmland soil in China: A meta-analysis.

Straw return is an effective measure to promote sustainable agriculture by significantly improving soil fertility. At present, few studies have been conducted on the most effective carbon enhancing management measures for various crops. Therefore, we conducted a meta-analysis using data collected from 184 literature sources, comprising 3297 data sets to analyze the carbon increase effects of straw returning in three main crops (rice, maize, and wheat) in China and to explore the influence mechanism of natural factors, soil properties, straw return measures, and cropping systems on the carbon enhancement effect. The study showed that straw return significantly increased soil organic carbon and the rate of increase was higher for wheat at 15.88% (14.74%-17.03%) than for rice at 12.7% (11.5%-13.91%) and maize at 12.42% (11.42%-13.42%), with varying degrees of improvement in other soil physicochemical properties. Natural factors have the greatest impact on the carbon increasing effect of rice fields, reaching 28.8%, especially at temperature between 10 °C and 15 °C, less than 800 mm precipitation, low latitude, and short frost-free period. Maize and wheat are most affected by soil properties, reaching 41% and 34.5% respectively. Furthermore, field management practices also play a pivotal role, organic carbon increasing obviously was observed when the C/N ratio of exogenous nutrients is bigger than 20 with the low initial organic matter. Shallow tillage and less than 7.5 t hm-2 straw returning with 3-10 years to the field are ideal for rice and maize. Crop rotation, especially in drylands, increased soil organic carbon more significantly than continuous. The results of our analysis can provide valuable insights into the effect of straw return on carbon increase. In the future, the soil carbon can be improved by adopting rational cropping patterns and straw return measures with taking into account climate and soil characteristics for different crops.

A MYB-related transcription factor ZmMYBR29 is involved in grain filling.

BACKGROUND: The endosperm serves as the primary source of nutrients for maize (Zea mays L.) kernel embryo development and germination. Positioned at the base of the endosperm, the transfer cells (TCs) of the basal endosperm transfer layer (BETL) generate cell wall ingrowths, which enhance the connectivity between the maternal plant and the developing kernels. These TCs play a crucial role in nutrient transport and defense against pathogens. The molecular mechanism underlying BETL development in maize remains unraveled. RESULTS: This study demonstrated that the MYB-related transcription factor ZmMYBR29, exhibited specific expression in the basal cellularized endosperm, as evidenced by in situ hybridization analysis. Utilizing the CRISPR/Cas9 system, we successfully generated a loss-of-function homozygous zmmybr29 mutant, which presented with smaller kernel size. Observation of histological sections revealed abnormal development and disrupted morphology of the cell wall ingrowths in the BETL. The average grain filling rate decreased significantly by 26.7% in zmmybr29 mutant in comparison to the wild type, which impacted the dry matter accumulation within the kernels and ultimately led to a decrease in grain weight. Analysis of RNA-seq data revealed downregulated expression of genes associated with starch synthesis and carbohydrate metabolism in the mutant. Furthermore, transcriptomic profiling identified 23 genes that expressed specifically in BETL, and the majority of these genes exhibited altered expression patterns in zmmybr29 mutant. CONCLUSIONS: In summary, ZmMYBR29 encodes a MYB-related transcription factor that is expressed specifically in BETL, resulting in the downregulation of genes associated with kernel development. Furthermore, ZmMYBR29 influences kernels weight by affecting the grain filling rate, providing a new perspective for the complementation of the molecular regulatory network in maize endosperm development.