Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Unraveling root and rhizosphere traits in temperate maize landraces and modern cultivars: Implications for soil resource acquisition and drought adaptation

A holistic understanding of plant strategies to acquire soil resources is pivotal in achieving sustainable food security. However, we lack knowledge about variety-specific root and rhizosphere traits for resource acquisition, their plasticity and adaptation to drought. We conducted a greenhouse experiment to phenotype root and rhizosphere traits (mean root diameter [Root D], specific root length [SRL], root tissue density, root nitrogen content, specific rhizosheath mass [SRM], arbuscular mycorrhizal fungi [AMF] colonization) of 16 landraces and 22 modern cultivars of temperate maize (Zea mays L.). Our results demonstrate that landraces and modern cultivars diverge in their root and rhizosphere traits. Although landraces follow a 'do-it-yourself' strategy with high SRLs, modern cultivars exhibit an 'outsourcing' strategy with increased mean Root Ds and a tendency towards increased root colonization by AMF. We further identified that SRM indicates an 'outsourcing' strategy. Additionally, landraces were more drought-responsive compared to modern cultivars based on multitrait response indices. We suggest that breeding leads to distinct resource acquisition strategies between temperate maize varieties. Future breeding efforts should increasingly target root and rhizosphere economics, with SRM serving as a valuable proxy for identifying varieties employing an outsourcing resource acquisition strategy.

Climate adaptation through crop migration requires a nexus perspective for environmental sustainability in the North China Plain

Crop migration can moderate the impacts of global warming on crop production, but its feedback on the climate and environment remains unknown. Here we develop an integrated framework to capture the climate impacts and the feedback of adaptation behaviours with the land-water-energy-carbon nexus perspective and identify opportunities to achieve the synergies between climate adaptation and environmental sustainability. We apply the framework to assess wheat and maize migration in the North China Plain and show that adaptation through wheat migration could increase crop production by ~18.5% in the 2050s, but at the cost of disproportional increment in land use (~19.2%), water use (~20.2%), energy use (~19.5%) and carbon emissions (~19.9%). Irrigation and fertilization management are critical mitigation opportunities in the framework, through which wheat migration can be optimized to reduce the climatic and environmental impacts and avoid potential carbon leakage. Our work highlights the sustainable climate adaptation to mitigate negative environmental externalities.

Calcium Hexacyanoferrate Nanozyme Enhances Plant Stress Resistance by Oxidative Stress Alleviation and Heavy Metal Removal

Oxidative damage, exacerbated by the excessive accumulation of reactive oxygen species (ROS), profoundly inhibits both crop growth and yield. Herein, a biocompatible nanozyme, calcium hexacyanoferrate nanoparticles (CaHCF NPs), targeting ROS is developed, to mitigate oxidative damage and sequestrate heavy metal ions during plant growth. Uniquely, CaHCF NPs feature multifaced enzyme-like activities, involving superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), glutathione peroxidase, thiol peroxidase, and ascorbate peroxidase, which enable them to neutralize excessive ROS. Furthermore, CaHCF NPs promote calcium-cadmium exchange process, diminishing the uptake of heavy metals. Importantly, 120 µg mL-1 of CaHCF NPs alleviate the inhibitory effects of hydrogen peroxide and cadmium chloride on Arabidopsis and tomato. The activities of SOD, POD, and CAT increase by 46.2%, 74.4%, and 48.3%, respectively, meanwhile the glutathione level rises by 72.4% in Arabidopsis under cadmium stress. Moreover, CaHCF NPs boost the expression of genes associated with antioxidation, heavy metal detoxification, nutrient transport, and stress resistance. These findings unveil the significant potential of nanoplatforms equipped with nanozymes in alleviating oxidative stress in plants, which not only regulate crop growth but also substantially ameliorate yield and quality, heralding a new era in agricultural nanotechnology.

Daily bias-corrected weather data and daily simulated growth data of maize, millet, sorghum, and wheat in the changing climate of sub-Saharan Africa

Crop models are the primary means by which agricultural scientists assess climate change impacts on crop production. Site-based and high-quality weather and climate data is essential for agronomically and physiologically sound crop simulations under historical and future climate scenarios. Here, we describe a bias-corrected dataset of daily agro-meteorological data for 109 reference weather stations distributed across key production areas of maize, millet, sorghum, and wheat in ten sub-Saharan African countries. The dataset leverages extensive ground observations from the Global Yield Gap Atlas (GYGA), an existing climate change projections dataset from the Inter-Sectoral Model Intercomparison Project (ISIMIP), and a calibrated crop simulation model (the WOrld FOod Studies -WOFOST). The weather data were bias-corrected using the delta method, which is widely used in climate change impact studies. The bias-corrected dataset encompasses daily values of maximum and minimum temperature, precipitation rate, and global radiation obtained from five models participating in the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), as well as simulated daily growth variables for the four crops. The data covers three periods: historical (1995-2014), 2030 (2020-2039), and 2050 (2040-2059). The simulation of daily growth dynamics for maize, millet, sorghum, and wheat growth was performed using the daily weather data and the WOFOST crop model, under potential and water-limited potential conditions. The crop simulation outputs were evaluated using national agronomic expertise. The presented datasets, including the weather dataset and daily simulated crop growth outputs, hold substantial potential for further use in the investigation of future climate change impacts in sub-Saharan Africa. The daily weather data can be used as an input into other modelling frameworks for crops or other sectors (e.g., hydrology). The weather and crop growth data can provide key insights about agro-meteorological conditions and water-limited crop output to inform adaptation priorities and benchmark (gridded) crop simulations. Finally, the weather and simulated growth data can also be used for training machine learning techniques for extrapolation purposes.

Seedling root system adaptation to water availability during maize domestication and global expansion

The maize root system has been reshaped by indirect selection during global adaptation to new agricultural environments. In this study, we characterized the root systems of more than 9,000 global maize accessions and its wild relatives, defining the geographical signature and genomic basis of variation in seminal root number. We demonstrate that seminal root number has increased during maize domestication followed by a decrease in response to limited water availability in locally adapted varieties. By combining environmental and phenotypic association analyses with linkage mapping, we identified genes linking environmental variation and seminal root number. Functional characterization of the transcription factor ZmHb77 and in silico root modeling provides evidence that reshaping root system architecture by reducing the number of seminal roots and promoting lateral root density is beneficial for the resilience of maize seedlings to drought.

Strategies for Enhancing Plant Immunity and Resilience Using Nanomaterials for Sustainable Agriculture

Research on plant-nanomaterial interactions has greatly advanced over the past decade. One particularly fascinating discovery encompasses the immunomodulatory effects in plants. Due to the low doses needed and the comparatively low toxicity of many nanomaterials, nanoenabled immunomodulation is environmentally and economically promising for agriculture. It may reduce environmental costs associated with excessive use of chemical pesticides and fertilizers, which can lead to soil and water pollution. Furthermore, nanoenabled strategies can enhance plant resilience against various biotic and abiotic stresses, contributing to the sustainability of agricultural ecosystems and the reduction of crop losses due to environmental factors. While nanoparticle immunomodulatory effects are relatively well-known in animals, they are still to be understood in plants. Here, we provide our perspective on the general components of the plant's immune system, including the signaling pathways, networks, and molecules of relevance for plant nanomodulation. We discuss the recent scientific progress in nanoenabled immunomodulation and nanopriming and lay out key avenues to use plant immunomodulation for agriculture. Reactive oxygen species (ROS), the mitogen-activated protein kinase (MAPK) cascade, and the calcium-dependent protein kinase (CDPK or CPK) pathway are of particular interest due to their interconnected function and significance in the response to biotic and abiotic stress. Additionally, we underscore that understanding the plant hormone salicylic acid is vital for nanoenabled applications to induce systemic acquired resistance. It is suggested that a multidisciplinary approach, incorporating environmental impact assessments and focusing on scalability, can expedite the realization of enhanced crop yields through nanotechnology while fostering a healthier environment.

Real-time emulation of future global warming reveals realistic impacts on the phenological response and quality deterioration in rice

Decreased production of crops due to climate change has been predicted scientifically. While climate-resilient crops are necessary to ensure food security and support sustainable agriculture, predicting crop growth under future global warming is challenging. Therefore, we aimed to assess the impact of realistic global warming conditions on rice cultivation. We developed a crop evaluation platform, the agro-environment (AE) emulator, which generates diverse environments by implementing the complexity of natural environmental fluctuations in customized, fully artificial lighting growth chambers. We confirmed that the environmental responsiveness of rice obtained in the fluctuation of artificial environments is similar to those exhibited in natural environments by validating our AE emulator using publicly available meteorological data from multiple years at the same location and multiple locations in the same year. Based on the representative concentration pathway, real-time emulation of severe global warming unveiled dramatic advances in the rice life cycle, accompanied by a 35% decrease in grain yield and an 85% increase in quality deterioration, which is higher than the recently reported projections. The transcriptome dynamism showed that increasing temperature and CO2 concentrations synergistically changed the expression of various genes and strengthened the induction of flowering, heat stress adaptation, and CO2 response genes. The predicted severe global warming greatly alters rice environmental adaptability and negatively impacts rice production. Our findings offer innovative applications of artificial environments and insights for enhancing varietal potential and cultivation methods in the future.

Finger millet: a hero in the making to combat food insecurity

Climate change and population growth pose challenges to food security. Major crops such as maize, wheat, and rice are expected to face yield reductions due to warming in the coming years, highlighting the need for incorporating climate-resilient crops in agricultural production systems. Finger millet (Eleusine coracana (L.) Gaertn) is a nutritious cereal crop adapted to arid regions that could serve as an alternative crop for sustaining the food supply in low rainfall environments where other crops routinely fail. Despite finger millet's nutritional qualities and climate resilience, it is deemed an "orphan crop," neglected by researchers compared to major crops, which has hampered breeding efforts. However, in recent years, finger millet has entered the genomics era. Next-generation sequencing resources, including a chromosome-scale genome assembly, have been developed to support trait characterization. This review discusses the current genetic and genomic resources available for finger millet while addressing the gaps in knowledge and tools that are still needed to aid breeders in bringing finger millet to its full production potential.

Maize miRNAs and their putative target genes involved in chilling stress response in 5-day old seedlings

BACKGROUND

In the context of early sowing of maize as a promising adaptation strategy that could significantly reduce the negative effects of climate change, an in-depth understanding of mechanisms underlying plant response to low-temperature stress is demanded. Although microRNAs (miRNAs) have been recognized as key regulators of plant stress response, research on their role in chilling tolerance of maize during early seedling stages is scarce. Therefore, it is of great significance to explore chilling-responsive miRNAs, reveal their expression patterns and associated target genes, as well as to examine the possible functions of the conserved and novel miRNAs. In this study, the role of miRNAs was examined in 5d-old maize seedlings of one tolerant and one sensitive inbred line exposed to chilling (10/8 °C) stress for 6 h and 24 h, by applying high throughput sequencing.

RESULTS

A total of 145 annotated known miRNAs belonging to 30 families and 876 potentially novel miRNAs were identified. Differential expression (DE) analysis between control and stress conditions identified 98 common miRNAs for both genotypes at one time point and eight miRNAs at both time points. Target prediction and enrichment analysis showed that the DE zma-miR396, zma-miR156, zma-miR319, and zma-miR159 miRNAs modulate growth and development. Furthermore, it was found that several other DE miRNAs were involved in abiotic stress response: antioxidative mechanisms (zma-miR398), signal transduction (zma-miR156, zma-miR167, zma-miR169) and regulation of water content (zma-miR164, zma-miR394, zma-miR396). The results underline the zma-miRNAs involvement in the modulation of their target genes expression as an important aspect of the plant's survival strategy and acclimation to chilling stress conditions.

CONCLUSIONS

To our understanding, this is the first study on miRNAs in 5-d old seedlings' response to chilling stress, providing data on the role of known and novel miRNAs post-transcriptional regulation of expressed genes and contributing a possible platform for further network and functional analysis.

Climate change market-driven poleward shifts in cropland production create opportunities for tropical biodiversity conservation and habitat restoration

Although the impacts of climate change on the yields of crops have been studied, how these changes will result in the eventual realized crop production through market feedbacks has received little attention. Using a combination of attainable yield predictions for wheat, rice, maize, soybean and sugarcane, computable general equilibrium and land rent models, we project market impacts and crop-specific land-use change up to 2100 and the resulting implications for carbon and biodiversity. The results show a general increase in crop prices in tropical regions and a decrease in sub-tropical and temperate regions. Land-use change driven by market feedbacks generally amplify the effects of climate change on yields. Wheat, maize and sugarcane are projected to experience the most expansion especially in Canada and Russia, which also present the highest potential for habitat conversion-driven carbon emissions. Conversely, Latin America presents the highest extinction potential for birds, mammals and amphibians due to cropland expansion. Climate change is likely to redistribute agricultural production, generating market-driven land-use feedback effects which could, counterintuitively, protect global biodiversity by shifting global food production towards less-biodiverse temperate regions while creating substantial restoration opportunities in the tropics.

Redistribution of nitrogen to feed the people on a safer planet

Lack of nitrogen limits food production in poor countries while excessive nitrogen use in industrial countries has led to transgression of the planetary boundary. However, the potential of spatial redistribution of nitrogen input for food security when returning to the safe boundary has not been quantified in a robust manner. Using an emulator of a global gridded crop model ensemble, we found that redistribution of current nitrogen input to major cereals among countries can double production in the most food-insecure countries, while increasing global production of these crops by 12% with no notable regional loss or reducing the nitrogen input to the current production by one-third. Redistribution of the input within the boundary increased production by 6-8% compared to the current relative distribution, increasing production in the food-insecure countries by two-thirds. Our findings provide georeferenced guidelines for redistributing nitrogen use to enhance food security while safeguarding the planet.

Mapping the race between crop phenology and climate risks for wheat in France under climate change

Climate change threatens food security by affecting the productivity of major cereal crops. To date, agroclimatic risk projections through indicators have focused on expected hazards exposure during the crop's current vulnerable seasons, without considering the non-stationarity of their phenology under evolving climatic conditions. We propose a new method for spatially classifying agroclimatic risks for wheat, combining high-resolution climatic data with a wheat's phenological model. The method is implemented for French wheat involving three GCM-RCM model pairs and two emission scenarios. We found that the precocity of phenological stages allows wheat to avoid periods of water deficit in the near future. Nevertheless, in the coming decades the emergence of heat stress and increasing water deficit will deteriorate wheat cultivation over the French territory. Projections show the appearance of combined risks of heat and water deficit up to 4 years per decade under the RCP 8.5 scenario. The proposed method provides a deep level of information that enables regional adaptation strategies: the nature of the risk, its temporal and spatial occurrence, and its potential combination with other risks. It's a first step towards identifying potential sites for breeding crop varieties to increase the resilience of agricultural systems.

Decoding early stress signaling waves in living plants using nanosensor multiplexing

Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.

Site-directed genotype screening for elimination of antinutritional saponins in quinoa seeds identifies TSARL1 as a master controller of saponin biosynthesis selectively in seeds

Climate change may result in a drier climate and increased salinization, threatening agricultural productivity worldwide. Quinoa (Chenopodium quinoa) produces highly nutritious seeds and tolerates abiotic stresses such as drought and high salinity, making it a promising future food source. However, the presence of antinutritional saponins in their seeds is an undesirable trait. We mapped genes controlling seed saponin content to a genomic region that includes TSARL1. We isolated desired genetic variation in this gene by producing a large mutant library of a commercial quinoa cultivar and screening the library for specific nucleotide substitutions using droplet digital PCR. We were able to rapidly isolate two independent tsarl1 mutants, which retained saponins in the leaves and roots for defence, but saponins were undetectable in the seed coat. We further could show that TSARL1 specifically controls seed saponin biosynthesis in the committed step after 2,3-oxidosqualene. Our work provides new important knowledge on the function of TSARL1 and represents a breakthrough for quinoa breeding.

Phosphorus applications adjusted to optimal crop yields can help sustain global phosphorus reserves

With the longevity of phosphorus reserves uncertain, distributing phosphorus to meet food production needs is a global challenge. Here we match plant-available soil Olsen phosphorus concentrations to thresholds for optimal productivity of improved grassland and 28 of the world's most widely grown and valuable crops. We find more land (73%) below optimal production thresholds than above. We calculate that an initial capital application of 56,954 kt could boost soil Olsen phosphorus to their threshold concentrations and that 28,067 kt yr-1 (17,500 kt yr-1 to cropland) could maintain these thresholds. Without additional reserves becoming available, it would take 454 years at the current rate of application (20,500 kt yr-1) to exhaust estimated reserves (2020 value), compared with 531 years at our estimated maintenance rate and 469 years if phosphorus deficits were alleviated. More judicious use of phosphorus fertilizers to account for soil Olsen phosphorus can help achieve optimal production without accelerating the depletion of phosphorus reserves.

Climate change enhances stability of wheat-flowering-date

The stability of winter wheat-flowering-date is crucial for ensuring consistent and robust crop performance across diverse climatic conditions. However, the impact of climate change on wheat-flowering-dates remains uncertain. This study aims to elucidate the influence of climate change on wheat-flowering-dates, predict how projected future climate conditions will affect flowering date stability, and identify the most stable wheat genotypes in the study region. We applied a multi-locus genotype-based (MLG-based) model for simulating wheat-flowering-dates, which we calibrated and evaluated using observed data from the Northern China winter wheat region (NCWWR). This MLG-based model was employed to project flowering dates under different climate scenarios. The simulated flowering dates were then used to assess the stability of flowering dates under varying allelic combinations in projected climatic conditions. Our MLG-based model effectively simulated flowering dates, with a root mean square error (RMSE) of 2.3 days, explaining approximately 88.5 % of the genotypic variation in flowering dates among 100 wheat genotypes. We found that, in comparison to the baseline climate, wheat-flowering-dates are expected to shift earlier within the target sowing window by approximately 11 and 14 days by 2050 under the Representative Concentration Pathways 4.5 (RCP4.5) and RCP8.5 climate scenarios, respectively. Furthermore, our analysis revealed that wheat-flowering-date stability is likely to be further strengthened under projected climate scenarios due to early flowering trends. Ultimately, we demonstrate that the combination of Vrn and Ppd genes, rather than individual Vrn or Ppd genes, plays a critical role in wheat-flowering-date stability. Our results suggest that the combination of Ppd-D1a with winter genotypes carrying the vrn-D1 allele significantly contributes to flowering date stability under current and projected climate scenarios. These findings provide valuable insights for wheat breeders and producers under future climatic conditions.

The water-energy-food-ecosystem nexus in the Danube River Basin: Exploring scenarios and implications of maize irrigation

The Water-Energy-Food-Ecosystem (WEFE) nexus concept postulates that water, energy production, agriculture and ecosystems are closely interlinked. In transboundary river basins, different sectors and countries compete for shared water resources. In the Danube River Basin (DRB), possible expansion of agricultural irrigation is expected to intensify water competition in the WEFE nexus, however, trade-offs have not yet been quantified. Here, we quantified trade-offs between agriculture, hydropower and (aquatic) ecosystems in the DRB resulting from maize irrigation when irrigation water was withdrawn from rivers. Using the process-based hydro-agroecological model PROMET, we simulated three maize scenarios for the period 2011-2020: (i) rainfed; (ii) irrigated near rivers without considering environmental flow requirements (EFRs); (iii) irrigated near rivers with water abstractions complying with EFRs. Maize yield and water use efficiency (WUE) increased by 101-125 % and 29-34 % under irrigation compared to rainfed cultivation. Irrigation water withdrawals from rivers resulted in moderate to severe discharge reductions and, without consideration of EFRs, to substantial EFR infringements. Annual hydropower production decreased by 1.0-1.9 % due to discharge reductions. However, the financial turnover increase in agriculture (5.8-7.2 billion €/a) was two orders of magnitude larger than the financial turnover decrease in hydropower (23.9-47.8 million €/a), making water more profitable in agriculture. Irrigation WUE was highest for EFR-compliant irrigation, indicating that maintaining EFRs is economically beneficial and that improving WUE is key to attenuating nexus water competition. Current maize production could be met on the most productive 35-41 % of current maize cropland under irrigation, allowing 59-65 % to be returned to nature without loss of production. Maize priority areas were on fertile lowlands near major rivers, while biodiversity priority areas were on marginal cropland of highest biodiversity intactness. Our quantitative trade-off analysis can help identifying science-based pathways for sustainable WEFE nexus management in the DRB, also in light of climate change.

Effect of heat stress on the hypothalamic expression profile of water homeostasis-associated genes in low- and high-water efficient chicken lines

With climate change, selection for water efficiency and heat resilience are vitally important. We undertook this study to determine the effect of chronic cyclic heat stress (HS) on the hypothalamic expression profile of water homeostasis-associated markers in high (HWE)- and low (LWE)-water efficient chicken lines. HS significantly elevated core body temperatures of both lines. However, the amplitude was higher by 0.5-1°C in HWE compared to their LWE counterparts. HWE line drank significantly less water than LWE during both thermoneutral (TN) and HS conditions, and HS increased water intake in both lines with pronounced magnitude in LWE birds. HWE had better feed conversion ratio (FCR), water conversion ratio (WCR), and water to feed intake ratio. At the molecular level, the overall hypothalamic expression of aquaporins (AQP8 and AQP12), arginine vasopressin (AVP) and its related receptor AVP2R, angiotensinogen (AGT), angiotensin II receptor type 1 (AT1), and calbindin 2 (CALB2) were significantly lower; however, CALB1 mRNA and AQP2 protein levels were higher in HWE compared to LWE line. Compared to TN conditions, HS exposure significantly increased mRNA abundances of AQPs (8, 12), AVPR1a, natriuretic peptide A (NPPA), angiotensin I-converting enzyme (ACE), CALB1 and 2, and transient receptor potential cation channel subfamily V member 1 and 4 (TRPV1 and TRPV4) as well as the protein levels of AQP2, however it decreased that of AQP4 gene expression. A significant line by environment interaction was observed in several hypothalamic genes. Heat stress significantly upregulated AQP2 and SCT at mRNA levels and AQP1 and AQP3 at both mRNA and protein levels, but it downregulated that of AQP4 protein only in LWE birds. In HWE broilers, however, HS upregulated the hypothalamic expression of renin (REN) and AVPR1b genes and AQP5 proteins, but it downregulated that of AQP3 protein. The hypothalamic expression of AQP (5, 7, 10, and 11) genes was increased by HS in both chicken lines. In summary, this is the first report showing improvement of growth performances in HWE birds. The hypothalamic expression of several genes was affected in a line- and/or environment-dependent manner, revealing potential molecular signatures for water efficiency and/or heat tolerance in chickens.

Water footprints and crop water use of 175 individual crops for 1990-2019 simulated with a global crop model

The water footprint of a crop (WF) is a common metric for assessing agricultural water consumption and productivity. To provide an update and methodological enhancement of existing WF datasets, we apply a global process-based crop model to quantify consumptive WFs of 175 individual crops at a 5 arcminute resolution over the 1990-2019 period. This model simulates the daily crop growth and vertical water balance considering local environmental conditions, crop characteristics, and farm management. We partition WFs into green (water from precipitation) and blue (from irrigation or capillary rise), and differentiate between rainfed and irrigated production systems. The outputs include gridded datasets and national averages for unit water footprints (expressed in m3 t-1 yr-1), water footprints of production (m3 yr-1), and crop water use (mm yr-1). We compare our estimates to other global studies covering different historical periods and methodological approaches. Provided outputs can offer insights into spatial and temporal patterns of agricultural water consumption and serve as inputs for further virtual water trade studies, life cycle and water footprint assessments.

Air quality improvements can strengthen China's food security

Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 μg m-3 for peak-season ozone and 35 μg m-3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security.

Spatiotemporal co-optimization of agricultural management practices towards climate-smart crop production

Co-optimization of multiple management practices may facilitate climate-smart agriculture, but is challenged by complex climate-crop-soil management interconnections across space and over time. Here we develop a hybrid approach combining agricultural system modelling, machine learning and life cycle assessment to spatiotemporally co-optimize fertilizer application, irrigation and residue management to achieve yield potential of wheat and maize and minimize greenhouse gas emissions in the North China Plain. We found that the optimal fertilizer application rate and irrigation for the historical period (1995-2014) are lower than local farmers' practices as well as trial-derived recommendations. With the optimized practices, the projected annual requirement of fertilizer, irrigation water and residue inputs across the North China Plain in the period 2051-2070 is reduced by 16% (14-21%) (mean with 95% confidence interval), 19% (7-32%) and 20% (16-26%), respectively, compared with the current supposed optimal management in the historical reference period, with substantial greenhouse gas emission reductions. We demonstrate the potential of spatiotemporal co-optimization of multiple management practices and present digital mapping of management practices as a benchmark for site-specific management across the region.

Genome-wide characterization and evolutionary analysis of the AP2/ERF gene family in lettuce (Lactuca sativa)

The APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF) gene family plays vital roles in plants, serving as a key regulator in responses to abiotic stresses. Despite its significance, a comprehensive understanding of this family in lettuce remains incomplete. In this study, we performed a genome-wide search for the AP2/ERF family in lettuce and identified a total of 224 members. The duplication patterns provided evidence that both tandem and segmental duplications contributed to the expansion of this family. Ka/Ks ratio analysis demonstrated that, following duplication events, the genes have been subjected to purifying selection pressure, leading to selective constraints on their protein sequence. This selective pressure provides a dosage benefit against stresses in plants. Additionally, a transcriptome analysis indicated that some duplicated genes gained novel functions, emphasizing the contribution of both dosage effect and functional divergence to the family functionalities. Furthermore, an orthologous relationship study showed that 60% of genes descended from a common ancestor of Rosid and Asterid lineages, 28% from the Asterid ancestor, and 12% evolved in the lettuce lineage, suggesting lineage-specific roles in adaptive evolution. These results provide valuable insights into the evolutionary mechanisms of the AP2/ERF gene family in lettuce, with implications for enhancing abiotic stress tolerance, ultimately contributing to the genetic improvement of lettuce crop production.

Building soil to reduce climate change impacts on global crop yield

Improving soil health and resilience is fundamental for sustainable food production, however the role of soil in maintaining or improving global crop productivity under climate warming is not well identified and quantified. Here, we examined the impact of soil on yield response to climate warming for four major crops (i.e., maize, wheat, rice and soybean), using global-scale datasets and random forest method. We found that each °C of warming reduced global yields of maize by 3.4%, wheat by 2.4%, rice by 0.3% and soybean by 5.0%, which were spatially heterogeneous with possible positive impacts. The random forest modeling analyses further showed that soil organic carbon (SOC), as an indicator of soil quality, dominantly explained the spatial heterogeneity of yield responses to warming and would regulate the negative warming responses. Improving SOC under the medium SOC sequestration scenario would reduce the warming-induced yield loss of maize, wheat, rice and soybean to 0.1% °C-1, 2.7% °C-1, 3.4% °C-1 and - 0.6% °C-1, respectively, avoiding an average of 3%-5% °C-1 of global yield loss. These yield benefits would occur on 53.2%, 67.8%, 51.8% and 71.6% of maize, wheat, rice and soybean planting areas, respectively, with particularly pronounced benefits in the regions with negative warming responses. With improved soil carbon, food systems are predicted to provide additional 20 to over 130 million tonnes of food that would otherwise lose due to future warming. Our findings highlight the critical role of soil in alleviating negative warming impacts on food security, especially for developing regions, given that sustainable actions on soil improvement could be taken broadly.

Greening of human-dominated ecosystems in India

Satellite data show the Earth has been greening and identify croplands in India as one of the most prominent greening hotspots. Though India's agriculture has been dependent on irrigation enhancement to reduce crop water stress and increase production, the spatiotemporal dynamics of how irrigation influenced the satellite observed greenness remains unclear. Here, we use satellite-derived leaf area data and survey-based agricultural statistics together with results from state-of-the-art Land Surface Models (LSM) to investigate the role of irrigation in the greening of India's croplands. We find that satellite observations provide multiple lines of evidence showing strong contributions of irrigation to significant greening during dry season and in drier environments. The national statistics support irrigation-driven yield enhancement and increased dry season cropping intensity. These suggest a continuous shift in India's agriculture toward an irrigation-driven dry season cropping system and confirm the importance of land management in the greening phenomenon. However, the LSMs identify CO2 fertilization as a primary driver of greening whereas land use and management have marginal impacts on the simulated leaf area changes. This finding urges a closer collaboration of the modeling, Earth observation, and land system science communities to improve representation of land management in the Earth system modeling.

Mitigation of the U.S. agrifood sector's contribution to human and planetary health: a case study

The relationship of the United States (U.S.) agrifood sector to climate change is bidirectional; cattle production for beef consumption generates methane and nitrous oxide, both of which are potent greenhouse gases (GHGs). These gases contribute to global warming which in turn increase the frequency and strength of adverse catastrophic events, which compromise the food supply. Increased GHGs also affect crop yields and the micronutrient content of crops, which adversely affect the prevalence of food and nutrition insecurity, particularly in low- and middle-income countries. Because the U.S. is a major contributor to global warming, we have a special responsibility to reduce our contribution to the generation of GHGs. The dilemma is that beef is a highly nutritious and desirable food, with excess consumption in the U.S. and under consumption in other parts of the world, but a desirable source of nutrients in low- and middle-income countries (LMICs). Reductions in fossil fuels have been a major focus of concern, and the agrifood system has been largely ignored. Policy changes to reduce beef consumption have been resisted at the highest levels of government. Furthermore, shifts to more plant-based diets have been contentious. Successful reductions in beef consumption will require individual, institutional, municipal, and state initiatives. Building the political will for change will require a compelling communication campaign that emphasizes the unsustainable contribution of beef consumption to climate change and land and water use.

Effects of Heat Stress on Plant-Nutrient Relations: An Update on Nutrient Uptake, Transport, and Assimilation

As a consequence of global climate change, the frequency, severity, and duration of heat stress are increasing, impacting plant growth, development, and reproduction. While several studies have focused on the physiological and molecular aspects of heat stress, there is growing concern that crop quality, particularly nutritional content and phytochemicals important for human health, is also negatively impacted. This comprehensive review aims to provide profound insights into the multifaceted effects of heat stress on plant-nutrient relationships, with a particular emphasis on tissue nutrient concentration, the pivotal nutrient-uptake proteins unique to both macro- and micronutrients, and the effects on dietary phytochemicals. Finally, we propose a new approach to investigate the response of plants to heat stress by exploring the possible role of plant peroxisomes in the context of heat stress and nutrient mobilization. Understanding these complex mechanisms is crucial for developing strategies to improve plant nutrition and resilience during heat stress.

Predicting spatiotemporal soil organic carbon responses to management using EPIC-IIASA meta-models

The management of Soil Organic Carbon (SOC) is a critical component of both nature-based solutions for climate change mitigation and global food security. Agriculture has contributed substantially to a reduction in global SOC through cultivation, thus there has been renewed focus on management practices which minimize SOC losses and increase SOC gain as pathways towards maintaining healthy soils and reducing net greenhouse gas emissions. Mechanistic models are frequently used to aid in identifying these pathways due to their scalability and cost-effectiveness. Yet, they are often computationally costly and rely on input data that are often only available at coarse spatial resolutions. Herein, we build statistical meta-models of a multifactorial crop model in order to both (a) obtain a simplified model response and (b) explore the biophysical determinants of SOC responses to management and the geospatial heterogeneity of SOC dynamics across Europe. Using 5600 unique simulations of crop growth from the gridded Environmental Policy Integrated Climate-based Gridded Agricultural Model (EPIC-IIASA GAM) covering 86,000 simulation units across Europe, we build multiple polynomial regression ensemble meta-models for unique combinations of climate and soil across Europe in order to predict SOC responses to varying management intensities. We find that our biophysically-explicit meta models are highly accurate (R2 = 0.97) representations of the full mechanistic model and can be used in lieu of the full EPIC-IIASA GAM model for the estimation of SOC responses to cropland management. Model stratification by means of climate and soil clustering improved the performance of the meta-models compared to the full EU-scale model. In regional and local validations of the meta-model predictions, we find that the meta-models largely capture broad SOC dynamics such as the linear nature of SOC responses to residue application, yet they often underestimate the magnitude of SOC responses to management. Furthermore, we find notable differences between the results from the biophysically-specific models throughout Europe, which point to spatially-distinct SOC responses to management choices such as nitrogen fertilizer application rates and residue retention that illustrate the potential for these models to be used for future management applications. While more accurate input data, calibration, and validation will be needed to accurately predict SOC change, we demonstrate the use of our meta-models for biophysical cluster and field study scale analyses of broad SOC dynamics with basically zero fine-tuning of the models needed. This work provides a framework for simplifying large-scale agricultural models and identifies the opportunities for using these meta-models for assessing SOC responses to management at a variety of scales.

A global dataset for the production and usage of cereal residues in the period 1997-2021

Crop residue management plays an important role in determining agricultural greenhouse gas emissions and related changes in soil carbon stocks. However, no publicly-available global dataset currently exists for how crop residues are managed. Here we present such a dataset, covering the period 1997-2021, on a 0.5° resolution grid. For each grid cell we estimate the total production of residues from cereal crops, and determine the fraction of residues (i) used for livestock feed/bedding, (ii) burnt on the field, (iii) used for other off-field purposes (e.g. domestic fuel, construction or industry), and (iv) left on the field. This dataset is the first of its kind, and can be used for multiple purposes, such as global crop modelling, including the calculation of greenhouse gas inventories, estimating crop-residue availability for biofuel production or modelling livestock feed availability.

Wheat adaptation to environmental stresses under climate change: Molecular basis and genetic improvement

Wheat (Triticum aestivum) is a staple food for about 40% of the world's population. As the global population has grown and living standards improved, high yield and improved nutritional quality have become the main targets for wheat breeding. However, wheat production has been compromised by global warming through the more frequent occurrence of extreme temperature events, which have increased water scarcity, aggravated soil salinization, caused plants to be more vulnerable to diseases, and directly reduced plant fertility and suppressed yield. One promising option to address these challenges is the genetic improvement of wheat for enhanced resistance to environmental stress. Several decades of progress in genomics and genetic engineering has tremendously advanced our understanding of the molecular and genetic mechanisms underlying abiotic and biotic stress responses in wheat. These advances have heralded what might be considered a "golden age" of functional genomics for the genetic improvement of wheat. Here, we summarize the current knowledge on the molecular and genetic basis of wheat resistance to abiotic and biotic stresses, including the QTLs/genes involved, their functional and regulatory mechanisms, and strategies for genetic modification of wheat for improved stress resistance. In addition, we also provide perspectives on some key challenges that need to be addressed.

Predicting plasticity of rosette growth and metabolic fluxes in Arabidopsis thaliana

Plants can rapidly mitigate the effects of suboptimal growth environments by phenotypic plasticity of fitness-traits. While genetic variation for phenotypic plasticity offers the means for breeding climate-resilient crop lines, accurate genomic prediction models for plasticity of fitness-related traits are still lacking. Here, we employed condition- and accession-specific metabolic models for 67 Arabidopsis thaliana accessions to dissect and predict plasticity of rosette growth to changes in nitrogen availability. We showed that specific reactions in photorespiration, linking carbon and nitrogen metabolism, as well as key pathways of central carbon metabolism exhibited substantial genetic variation for flux plasticity. We also demonstrated that, in comparison with a genomic prediction model for fresh weight (FW), genomic prediction of growth plasticity improves the predictability of FW under low nitrogen by 58.9% and by additional 15.4% when further integrating data on plasticity of metabolic fluxes. Therefore, the combination of metabolic and statistical modeling provides a stepping stone in understanding the molecular mechanisms and improving the predictability of plasticity for fitness-related traits.

Optimal climate intervention scenarios for crop production vary by nation

Stratospheric aerosol intervention (SAI) is a proposed strategy to reduce the effects of anthropogenic climate change. There are many temperature targets that could be chosen for a SAI implementation, which would regionally modify climatically relevant variables such as surface temperature, precipitation, humidity, total solar radiation and diffuse radiation. In this work, we analyse impacts on national maize, rice, soybean and wheat production by looking at output from 11 different SAI scenarios carried out with a fully coupled Earth system model coupled to a crop model. Higher-latitude nations tend to produce the most calories under unabated climate change, while midlatitude nations maximize calories under moderate SAI implementation and equatorial nations produce the most calories from crops under high levels of SAI. Our results highlight the challenges in defining 'globally optimal' SAI strategies, even if such definitions are based on just one metric.

Feeding climate and biodiversity goals with novel plant-based meat and milk alternatives

Plant-based animal product alternatives are increasingly promoted to achieve more sustainable diets. Here, we use a global economic land use model to assess the food system-wide impacts of a global dietary shift towards these alternatives. We find a substantial reduction in the global environmental impacts by 2050 if globally 50% of the main animal products (pork, chicken, beef and milk) are substituted-net reduction of forest and natural land is almost fully halted and agriculture and land use GHG emissions decline by 31% in 2050 compared to 2020. If spared agricultural land within forest ecosystems is restored to forest, climate benefits could double, reaching 92% of the previously estimated land sector mitigation potential. Furthermore, the restored area could contribute to 13-25% of the estimated global land restoration needs under target 2 from the Kunming Montreal Global Biodiversity Framework by 2030, and future declines in ecosystem integrity by 2050 would be more than halved. The distribution of these impacts varies across regions-the main impacts on agricultural input use are in China and on environmental outcomes in Sub-Saharan Africa and South America. While beef replacement provides the largest impacts, substituting multiple products is synergistic.

Anti-fungal bioactive terpenoids in the bioenergy crop switchgrass (Panicum virgatum) may contribute to ecotype-specific microbiome composition

Plant derived bioactive small molecules have attracted attention of scientists across fundamental and applied scientific disciplines. We seek to understand the influence of these phytochemicals on rhizosphere and root-associated fungi. We hypothesize that - consistent with accumulating evidence that switchgrass genotype impacts microbiome assembly - differential terpenoid accumulation contributes to switchgrass ecotype-specific microbiome composition. An initial in vitro Petri plate-based disc diffusion screen of 18 switchgrass root derived fungal isolates revealed differential responses to upland- and lowland-isolated metabolites. To identify specific fungal growth-modulating metabolites, we tested fractions from root extracts on three ecologically important fungal isolates - Linnemania elongata, Trichoderma sp. and Fusarium sp. Saponins and diterpenoids were identified as the most prominent antifungal metabolites. Finally, analysis of liquid chromatography-purified terpenoids revealed fungal inhibition structure - activity relationships (SAR). Saponin antifungal activity was primarily determined by the number of sugar moieties - saponins glycosylated at a single core position were inhibitory whereas saponins glycosylated at two core positions were inactive. Saponin core hydroxylation and acetylation were also associated with reduced activity. Diterpenoid activity required the presence of an intact furan ring for strong fungal growth inhibition. These results inform future breeding and biotechnology strategies for crop protection with reduced pesticide application.

Upcycling rice yield trial data using a weather-driven crop growth model

Efficient plant breeding plays a significant role in increasing crop yields and attaining food security under climate change. Screening new cultivars through yield trials in multi-environments has improved crop yields, but the accumulated data from these trials has not been effectively upcycled. We propose a simple method that quantifies cultivar-specific productivity characteristics using two regression coefficients: yield-ability (β) and yield-plasticity (α). The recorded yields of each cultivar are expressed as a unique linear regression in response to the theoretical potential yield (Y_p) calculated by a weather-driven crop growth model, called as the "YpCGM method". We apply this to 72510 independent datasets from yield trials of rice that used 237 cultivars measured at 110 locations in Japan over 38 years. The YpCGM method can upcycle accumulated yield data for use in genetic-gain analysis and genome-wide-association studies to guide future breeding programs for developing new cultivars suitable for the world's changing climate.

Risks of synchronized low yields are underestimated in climate and crop model projections

Simultaneous harvest failures across major crop-producing regions are a threat to global food security. Concurrent weather extremes driven by a strongly meandering jet stream could trigger such events, but so far this has not been quantified. Specifically, the ability of state-of-the art crop and climate models to adequately reproduce such high impact events is a crucial component for estimating risks to global food security. Here we find an increased likelihood of concurrent low yields during summers featuring meandering jets in observations and models. While climate models accurately simulate atmospheric patterns, associated surface weather anomalies and negative effects on crop responses are mostly underestimated in bias-adjusted simulations. Given the identified model biases, future assessments of regional and concurrent crop losses from meandering jet states remain highly uncertain. Our results suggest that model-blind spots for such high-impact but deeply-uncertain hazards have to be anticipated and accounted for in meaningful climate risk assessments.

Anatomical drivers of stomatal conductance in sorghum lines with different leaf widths grown under different temperatures

Sustaining crop productivity and resilience in water-limited environments and under rising temperatures are matters of concern worldwide. We investigated the leaf anatomical traits that underpin our recently identified link between leaf width (LW) and intrinsic water use efficiency (iWUE), as traits of interest in plant breeding. Ten sorghum lines with varying LW were grown under three temperatures to expand the range of variation of both LW and gas exchange rates. Leaf gas exchange, surface morphology and cross-sectional anatomy were measured and analysed using structural equations modelling. Narrower leaves had lower stomatal conductance (g_s ) and higher iWUE across growth temperatures. They also had smaller intercellular airspaces, stomatal size, percentage of open stomatal aperture relative to maximum, hydraulic pathway, mesophyll thickness, and leaf mass per area. Structural modelling revealed a developmental association among leaf anatomical traits that underpinned g_s variation in sorghum. Growing temperature and LW both impacted leaf gas exchange rates, but only LW directly impacted leaf anatomy. Wider leaves may be more productive under well-watered conditions, but consume more water for growth and development, which is detrimental under water stress.

Review: Harnessing extant energy and protein requirement modeling for sustainable beef production

Numerous mathematical nutrition models have been developed in the last sixty years to predict the dietary supply and requirement of farm animals' energy and protein. Although these models, usually developed by different groups, share similar concepts and data, their calculation routines (i.e., submodels) have rarely been combined into generalized models. This lack of mixing submodels is partly because different models have different attributes, including paradigms, structural decisions, inputs/outputs, and parameterization processes that could render them incompatible for merging. Another reason is that predictability might increase due to offsetting errors that cannot be thoroughly studied. Alternatively, combining concepts might be more accessible and safer than combining models' calculation routines because concepts can be incorporated into existing models without changing the modeling structure and calculation logic, though additional inputs might be needed. Instead of developing new models, improving the merging of extant models' concepts might curtail the time and effort needed to develop models capable of evaluating aspects of sustainability. Two areas of beef production research that are needed to ensure adequate diet formulation include accurate energy requirements of grazing animals (decrease methane emissions) and efficiency of energy use (reduce carcass waste and resource use) by growing cattle. A revised model for energy expenditure of grazing animals was proposed to incorporate the energy needed for physical activity, as the British feeding system recommended, and eating and rumination (HjEer) into the total energy requirement. Unfortunately, the proposed equation can only be solved iteratively through optimization because HjEer requires metabolizable energy (ME) intake. The other revised model expanded an existing model to estimate the partial efficiency of using ME for growth (kg) from protein proportion in the retained energy by including an animal degree of maturity and average daily gain (ADG) as used in the Australian feeding system. The revised kg model uses carcass composition, and it is less dependent on dietary ME content, but still requires an accurate assessment of the degree of maturity and ADG, which in turn depends on the kg. Therefore, it needs to be solved iteratively or using one-step delayed continuous calculation (i.e., use the previous day's ADG to compute the current day's kg). We believe that generalized models developed by merging different models' concepts might improve our understanding of the relationships of existing variables that were known for their importance but not included in extant models because of the lack of proper information or confidence at that time.

Rice availability and stability in Africa under future socio-economic development and climatic change

As Africa is facing multiple challenges related to food security, frameworks integrating production and availability are urgent for policymaking. Attention should be given not only to gradual socio-economic and climatic changes but also to their temporal variability. Here we present an integrated framework that allows one to assess the impacts of socio-economic development, gradual climate change and climate anomalies. We apply this framework to rice production and consumption in Africa whereby we explicitly account for the continent's dependency on imported rice. We show that socio-economic development dictates rice availability, whereas climate change has only minor effects in the long term and is predicted not to amplify supply shocks. Still, rainfed-dominated or self-producing regions are sensitive to local climatic anomalies, while trade dominates stability in import-dependent regions. Our study suggests that facilitating agricultural development and limiting trade barriers are key in relieving future challenges to rice availability and stability.

Paralog editing tunes rice stomatal density to maintain photosynthesis and improve drought tolerance

Rice (Oryza sativa) is of paramount importance for global nutrition, supplying at least 20% of global calories. However, water scarcity and increased drought severity are anticipated to reduce rice yields globally. We explored stomatal developmental genetics as a mechanism for improving drought resilience in rice while maintaining yield under climate stress. CRISPR/Cas9-mediated knockouts of the positive regulator of stomatal development STOMAGEN and its paralog EPIDERMAL PATTERNING FACTOR-LIKE10 (EPFL10) yielded lines with ∼25% and 80% of wild-type stomatal density, respectively. epfl10 lines with moderate reductions in stomatal density were able to conserve water to similar extents as stomagen lines but did not suffer from the concomitant reductions in stomatal conductance, carbon assimilation, or thermoregulation observed in stomagen knockouts. Moderate reductions in stomatal density achieved by editing EPFL10 present a climate-adaptive approach for safeguarding yield in rice. Editing the paralog of STOMAGEN in other species may provide a means for tuning stomatal density in agriculturally important crops beyond rice.

A synthesis of hydroclimatic, ecological, and socioeconomic data for transdisciplinary research in the Mekong

The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data- including groundwater records digitized from the literature-provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB.

Extreme rainfall reduces one-twelfth of China's rice yield over the last two decades

Extreme climate events constitute a major risk to global food production. Among these, extreme rainfall is often dismissed from historical analyses and future projections, the impacts and mechanisms of which remain poorly understood. Here we used long-term nationwide observations and multi-level rainfall manipulative experiments to explore the magnitude and mechanisms of extreme rainfall impacts on rice yield in China. We find that rice yield reductions due to extreme rainfall were comparable to those induced by extreme heat over the last two decades, reaching 7.6 ± 0.9% (one standard error) according to nationwide observations and 8.1 ± 1.1% according to the crop model incorporating the mechanisms revealed from manipulative experiments. Extreme rainfall reduces rice yield mainly by limiting nitrogen availability for tillering that lowers per-area effective panicles and by exerting physical disturbance on pollination that declines per-panicle filled grains. Considering these mechanisms, we projected ~8% additional yield reduction due to extreme rainfall under warmer climate by the end of the century. These findings demonstrate that it is critical to account for extreme rainfall in food security assessments.

Solutions to agricultural green water scarcity under climate change

Rain-fed agricultural systems, which solely depend on green water (i.e. soil moisture from rainfall), sustain ∼60% of global food production and are particularly vulnerable to vagaries in temperature and precipitation patterns, which are intensifying due to climate change. Here, using projections of crop water demand and green water availability under warming scenarios, we assess global agricultural green water scarcity-defined when the rainfall regime is unable to meet crop water requirements. With present-day climate conditions, food production for 890 million people is lost because of green water scarcity. Under 1.5°C and 3°C warming-the global warming projected from the current climate targets and business as usual policies-green water scarcity will affect global crop production for 1.23 and 1.45 billion people, respectively. If adaptation strategies were to be adopted to retain more green water in the soil and reduce evaporation, we find that food production loss from green water scarcity would decrease to 780 million people. Our results show that appropriate green water management strategies have the potential to adapt agriculture to green water scarcity and promote global food security.

Light and carbon: Synthetic biology toward new cyanobacteria-based living biomaterials

Cyanobacteria are ideal candidates to use in developing carbon neutral and carbon negative technologies; they are efficient photosynthesizers and amenable to genetic manipulation. Over the past two decades, researchers have demonstrated that cyanobacteria can make sustainable, useful biomaterials, many of which are engineered living materials. However, we are only beginning to see such technologies applied at an industrial scale. In this review, we explore the ways in which synthetic biology tools enable the development of cyanobacteria-based biomaterials. First we give an overview of the ecological and biogeochemical importance of cyanobacteria and the work that has been done using cyanobacteria to create biomaterials so far. This is followed by a discussion of commonly used cyanobacteria strains and synthetic biology tools that exist to engineer cyanobacteria. Then, three case studies-bioconcrete, biocomposites, and biophotovoltaics-are explored as potential applications of synthetic biology in cyanobacteria-based materials. Finally, challenges and future directions of cyanobacterial biomaterials are discussed.

Improving crop genetic transformation to feed the world

Food security is threatened by rising global population and effects of climate change. Most of our calories come from a few crops that are difficult to improve. Lowe et al. developed a plant transformation approach enabling crop genetic engineering that could provide a route to a future with greater food security.

Microbial consortia enhance the yield of maize under sub-humid rainfed production system of India

Plant beneficial microorganisms are being used to improve soil health and crop yield in different cropping systems. Maize is an important crop grown around the world for food, feed and raw material for various industries. The aim of the present study was to evaluate two microbial consortia viz., microbial consortia 1 (Pseudomonas putida P7 + Paenibacillus favisporus B30) and microbial consortia 2 (Pseudomonas putida P45 + Bacillus amyloliquefaciens B17) under field conditions for their suitability in improving maize yield under rainfed situations at Ballowal Saunkhri (Punjab) having sub-humid (Hot Dry) climatic conditions. Pooled analysis of three years field experiments data showed that, seed + soil application of microbial consortia 1 and 2 led to enhancement in grain yield of kharif maize by 27.78 and 23.21% respectively over uninoculated control. Likewise, significant increase in Benefit:Cost ratio as well as straw yield was also observed. The present investigation suggests that, microbial consortia would help in significantly improving the yield and economics of maize grown on inceptisols under rainfed conditions.