Climate change has likely already affected global food production

Microplastics and climate change: the global impacts of a tiny driver

Microplastic pollution and climate change, the two seemingly distinct phenomena of global concern, are interconnected through various pathways. The connecting links between the two include the biological carbon pumps in the oceans, the sea ice, the plastisphere involved in biogeochemical cycling and the direct emissions of greenhouse gases from microplastics. On one hand, the presence of microplastics in the water column disrupts the balance of the natural carbon sequestration by affecting the key players in the pumping of carbon, such as the phytoplankton and zooplankton. On the other hand, the effect of microplastics on the sea ice in Polar Regions is two-way, as the ice caps are transformed into sinks and sources of microplastics and at the same time, the microplastics can enhance the melting of ice by reducing the albedo. Microplastics may have more potential than larger plastic fragments to release greenhouse gases (GHGs). Microbe-mediated emission of GHGs from soils is also now altered by the microplastics present in the soil. Plastisphere, the emerging microbiome in aquatic environments, can also contribute to climate change as it hosts complex networks of microbes, many of which are involved in greenhouse gas production. To combat a global stressor like climate change, it needs to be addressed with a holistic approach and this begins with tracing the various stressors like microplastic pollution that can aggravate the impacts of climate change.

The Role of Multistakeholder Platforms in Environmental Governance: Analyzing Stakeholder Perceptions in Kalomo District, Zambia, Using Q-Method

Multistakeholder platforms (MSPs) are increasingly applied in environmental governance as institutions to collectively negotiate challenges, opportunities, and policy options in contested landscapes. However, their contributions and effectiveness depend on how stakeholders perceive and frame the role of MSPs in addressing social and environmental challenges. Despite this dependence, stakeholder perceptions of MSPs are currently under-researched. Hence this empirical study carried out in Zambia's Kalomo District asks: how do stakeholder groups perceive the role of MSPs in addressing landscape challenges, given the context of the dual land tenure system, and what does this imply for the implementation of integrated landscape approaches? This study uses Q-methodology to analyze the perceptions of purposefully selected stakeholders from state institutions, civil society organizations, land users, and others familiar with existing MSPs at the district and village levels. The findings reveal three narratives. The first one presents MSPs as institutions that foster dialogue. The second narrative foregrounds the role of the government and private sector, despite acknowledging the diversity of stakeholders in MSPs. In this narrative, MSPs should focus on supporting market-driven solutions to resolve landscape challenges. The third narrative recognizes power imbalances and considers MSPs as institutions to identify policy gaps and needs. The first two narratives are positioned in Dryzek's discourse classification as environmental problem-solving, while the third inclines toward green radicalism. Despite this divergence, there was consensus that MSPs have the potential to harmonize policies in a dual governance system and encourage dialogue between stakeholders to reconcile landscape challenges.

Precision phenotyping of a barley diversity set reveals distinct drought response strategies

Plants exhibit an array of drought responses and adaptations, where the trade-off between water loss and CO2 uptake for growth is mediated by regulation of stomatal aperture in response to soil water content (SWC), among other factors. For crop yield stability, the question is how drought timing and response patterns relate to post-drought growth resilience and vigor. We earlier identified, in a few reference varieties of barley that differed by the SWC at which transpiration was curtailed, two divergent water use strategies: water-saving ("isohydric") and water-spending ("anisohydric"). We proposed that an isohydric strategy may reduce risk from spring droughts in climates where the probability of precipitation increases during the growing season, whereas the anisohydric is consistent with environments having terminal droughts, or with those where dry periods are short and not seasonally progressive. Here, we have examined drought response physiology in an 81-line barley (Hordeum vulgare L.) diversity set that spans 20th century European breeding and identified several lines with a third, dynamic strategy. We found a strong positive correlation between vigor and transpiration, the dynamic group being highest for both. However, these lines curtailed daily transpiration at a higher SWC than the isohydric group. While the dynamic lines, particularly cv Hydrogen and Baronesse, were not the most resilient in terms of restoring initial growth rates, their strong initial vigor and high return to initial transpiration rates meant that their growth nevertheless surpassed more resilient lines during recovery from drought. The results will be of use for defining barley physiological ideotypes suited to future climate scenarios.

Smart Robotics for Automation

In recent years, the demand for efficient automation across various sectors has accelerated significantly [...].

Adoption of CRISPR-Cas for crop production: present status and future prospects

Background

Global food systems in recent years have been impacted by some harsh environmental challenges and excessive anthropogenic activities. The increasing levels of both biotic and abiotic stressors have led to a decline in food production, safety, and quality. This has also contributed to a low crop production rate and difficulty in meeting the requirements of the ever-growing population. Several biotic stresses have developed above natural resistance in crops coupled with alarming contamination rates. In particular, the multiple antibiotic resistance in bacteria and some other plant pathogens has been a hot topic over recent years since the food system is often exposed to contamination at each of the farm-to-fork stages. Therefore, a system that prioritizes the safety, quality, and availability of foods is needed to meet the health and dietary preferences of everyone at every time.

Methods

This review collected scattered information on food systems and proposes methods for plant disease management. Multiple databases were searched for relevant specialized literature in the field. Particular attention was placed on the genetic methods with special interest in the potentials of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and Cas (CRISPR associated) proteins technology in food systems and security.

Results

The review reveals the approaches that have been developed to salvage the problem of food insecurity in an attempt to achieve sustainable agriculture. On crop plants, some systems tend towards either enhancing the systemic resistance or engineering resistant varieties against known pathogens. The CRISPR-Cas technology has become a popular tool for engineering desired genes in living organisms. This review discusses its impact and why it should be considered in the sustainable management, availability, and quality of food systems. Some important roles of CRISPR-Cas have been established concerning conventional and earlier genome editing methods for simultaneous modification of different agronomic traits in crops.

Conclusion

Despite the controversies over the safety of the CRISPR-Cas system, its importance has been evident in the engineering of disease- and drought-resistant crop varieties, the improvement of crop yield, and enhancement of food quality.

Unsupervised literature mining approaches for extracting relationships pertaining to habitats and reproductive conditions of plant species

Introduction

Fine-grained, descriptive information on habitats and reproductive conditions of plant species are crucial in forest restoration and rehabilitation efforts. Precise timing of fruit collection and knowledge of species' habitat preferences and reproductive status are necessary especially for tropical plant species that have short-lived recalcitrant seeds, and those that exhibit complex reproductive patterns, e.g., species with supra-annual mass flowering events that may occur in irregular intervals. Understanding plant regeneration in the way of planning for effective reforestation can be aided by providing access to structured information, e.g., in knowledge bases, that spans years if not decades as well as covering a wide range of geographic locations. The content of such a resource can be enriched with literature-derived information on species' time-sensitive reproductive conditions and location-specific habitats.

Methods

We sought to develop unsupervised approaches to extract relationships pertaining to habitats and their locations, and reproductive conditions of plant species and corresponding temporal information. Firstly, we handcrafted rules for a traditional rule-based pattern matching approach. We then developed a relation extraction approach building upon transformer models, i.e., the Text-to-Text Transfer Transformer (T5), casting the relation extraction problem as a question answering and natural language inference task. We then propose a novel unsupervised hybrid approach that combines our rule-based and transformer-based approaches.

Results

Evaluation of our hybrid approach on an annotated corpus of biodiversity-focused documents demonstrated an improvement of up to 15 percentage points in recall and best performance over solely rule-based and transformer-based methods with F1-scores ranging from 89.61 to 96.75% for reproductive condition - temporal expression relations, and ranging from 85.39% to 89.90% for habitat - geographic location relations. Our work shows that even without training models on any domain-specific labeled dataset, we are able to extract relationships between biodiversity concepts from literature with satisfactory performance.

Determinants of Consumers' Acceptance and Adoption of Novel Food in View of More Resilient and Sustainable Food Systems in the EU: A Systematic Literature Review

This review article aims to provide an up-to-date overview of the main determinants of consumers' acceptance of novel foods (new foods and ingredients) in the EU with emphasis on product's intrinsic properties (sensory characteristics) and individual factors (socio-demographics, perceptive, psychological) by adopting a systematic approach following the PRISMA methodology. Case studies on terrestrial (i.e., insects, cultured meat and other animal origin products, plant-based food including mushrooms, plant-based analogues, pulses, and cereals) and aquatic systems (i.e., algae and jellyfish) are included focusing on age-related and cross-national differences in consumer acceptance of novel foods and ingredients. General trends have emerged that are common to all the novel foods analysed, regardless of their aquatic or terrestrial origin. Aspects such as food neophobia, unfamiliarity, and poor knowledge of the product are important barriers to the consumption of novel foods, while healthiness and environmental sustainability perception are drivers of acceptance. Sensory properties are challenging for more familiar ingredients such as plant-based food (e.g., novel food made by pulses, mushrooms, cereals and pseudocereals). Results are discussed in terms of feasibility of introducing these products in the EU food systems highlighting strategies that can encourage the use of new ingredients or novel foods.

Extension of Japan's Prefectural Emission Accounting and Enrichment of Socioeconomic Data from 1990 to 2020

With the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan's 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.

Transgenerational Seed Exposure to Elevated CO2 Involves Stress Memory Regulation at Metabolic Levels to Confer Drought Resistance in Wheat

Drought is the worst environmental stress constraint that inflicts heavy losses to global food production, such as wheat. The metabolic responses of seeds produced overtransgenerational exposure to e[CO2] to recover drought's effects on wheat are still unexplored. Seeds were produced constantly for four generations (F1 to F4) under ambient CO2 (a[CO2], 400 μmol L-1) and elevated CO2 (e[CO2], 800 μmol L-1) concentrations, and then further regrown under natural CO2 conditions to investigate their effects on the stress memory metabolic processes liable for increasing drought resistance in the next generation (F5). At the anthesis stage, plants were subjected to normal (100% FC, field capacity) and drought stress (60% FC) conditions. Under drought stress, plants of transgenerational e[CO2] exposed seeds showed markedly increased superoxide dismutase (16%), catalase (24%), peroxidase (9%), total antioxidants (14%), and proline (35%) levels that helped the plants to sustain normal growth through scavenging of hydrogen peroxide (11%) and malondialdehyde (26%). The carbohydrate metabolic enzymes such as aldolase (36%), phosphoglucomutase (12%), UDP-glucose pyrophosphorylase (25%), vacuolar invertase (33%), glucose-6-phosphate-dehydrogenase (68%), and cell wall invertase (17%) were decreased significantly; however, transgenerational seeds produced under e[CO2] showed a considerable increase in their activities in drought-stressed wheat plants. Moreover, transgenerational e[CO2] exposed seeds under drought stress caused a marked increase in leaf Ψw (15%), chlorophyll a (19%), chlorophyll b (8%), carotenoids (12%), grain spike (16%), hundred grain weight (19%), and grain yield (10%). Hence, transgenerational seeds exposed to e[CO2] upregulate the drought recovery metabolic processes to improve the grain yield of wheat under drought stress conditions.

Regional food self-sufficiency potential in the European Alpine space

The sustainability of the food system needs to be improved, including shortening supply chains and promoting the consumption of regional food. Here, we explore the current potential for regional food self-sufficiency in the European Alpine space by calculating the current regional food/feed energy balance, deriving the regional per capita land footprint based on current food/feed consumption rates, and modelling the current potential for regional food/feed self-sufficiency. We show that 59% of the 560 Pcal of energy currently available in the study area comes from domestic production, and almost 60% of the energy is used for livestock consumption, with high regional variability. The resulting land footprints range from 2301 to 2975 m2 cap-1 y-1. Taking into account changes in cropping patterns, partial intensification, but no expansion of agricultural land, the European Alpine space could produce 89% of its current food demand domestically, with high regional variability due to population density, availability of agricultural land, crop yields, climatic conditions and dietary habits. These findings highlight the potential and limitations of regional mountain food systems and call for new strategies to improve sustainability. Reducing the current high consumption of animal products would reduce the land footprint and increase the potential for food self-sufficiency.

Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning

Background

Autofluorescence-based imaging has the potential to non-destructively characterize the biochemical and physiological properties of plants regulated by genotypes using optical properties of the tissue. A comparative study of stress tolerant and stress susceptible genotypes of Brassica rapa with respect to newly introduced stress-based phenotypes using machine learning techniques will contribute to the significant advancement of autofluorescence-based plant phenotyping research.

Methods

Autofluorescence spectral images have been used to design a stress detection classifier with two classes, stressed and non-stressed, using machine learning algorithms. The benchmark dataset consisted of time-series image sequences from three Brassica rapa genotypes (CC, R500, and VT), extreme in their morphological and physiological traits captured at the high-throughput plant phenotyping facility at the University of Nebraska-Lincoln, USA. We developed a set of machine learning-based classification models to detect the percentage of stressed tissue derived from plant images and identified the best classifier. From the analysis of the autofluorescence images, two novel stress-based image phenotypes were computed to determine the temporal variation in stressed tissue under progressive drought across different genotypes, i.e., the average percentage stress and the moving average percentage stress.

Results

The study demonstrated that both the computed phenotypes consistently discriminated against stressed versus non-stressed tissue, with oilseed type (R500) being less prone to drought stress relative to the other two Brassica rapa genotypes (CC and VT).

Conclusion

Autofluorescence signals from the 365/400 nm excitation/emission combination were able to segregate genotypic variation during a progressive drought treatment under a controlled greenhouse environment, allowing for the exploration of other meaningful phenotypes using autofluorescence image sequences with significance in the context of plant science.

Perennial Baki™ Bean Safety for Human Consumption: Evidence from an Analysis of Heavy Metals, Folate, Canavanine, Mycotoxins, Microorganisms and Pesticides

Global food production relies on annual grain crops. The reliability and productivity of these crops are threatened by adaptations to climate change and unsustainable rates of soil loss associated with their cultivation. Perennial grain crops, which do not require planting every year, have been proposed as a transformative solution to these challenges. Perennial grain crops typically rely on wild species as direct domesticates or as sources of perenniality in hybridization with annual grains. Onobrychis spp. (sainfoins) are a genus of perennial legumes domesticated as ancient forages. Baki™ bean is the tradename for pulses derived from sainfoins, with ongoing domestication underway to extend demonstrated benefits to sustainable agriculture. This study contributes to a growing body of evidence characterizing the nutritional quality of Baki™ bean. Through two studies, we investigated the safety of Baki™ bean for human consumption. We quantified heavy metals, folate, and canavanine for samples from commercial seed producers, and we quantified levels of mycotoxins, microorganisms, and pesticides in samples from a single year and seed producer, representing different varieties and production locations. The investigated analytes were not detectable or occurred at levels that do not pose a significant safety risk. Overall, this study supports the safety of Baki™ bean for human consumption as a novel pulse crop.

Aging Increases Global Annual Food Greenhouse Gas Emissions up to 300 Million Tonnes by 2100

The dietary preferences of the elderly population exhibit distinct variations from the overall averages in most countries, gaining increasing significance due to aging demographics worldwide. These dietary preferences play a crucial role in shaping global food systems, which will result in changed environmental impacts in the future such as greenhouse gas (GHG) emissions. We present a quantitative evaluation of the influence of population aging on the changes in GHG emissions from global food systems. To achieve this, we developed regional dietary coefficients (DCs) of the elderly based on the Global Dietary Database (GDD). We then reconciled the GDD with the dataset from the Food and Agriculture Organization of the United Nations (FAO) to calculate the food GHG emissions of the average population in each of the countries. By applying the DCs, we estimated the national food GHG emissions and obtained the variations between the emissions from aged and average populations. We employed a modified version of the regional integrated model of climate and the economy model (RICE) to forecast the emission trends in different countries based on FAO and GDD data. This integrated approach allowed us to evaluate the dynamic relationships among aging demographics, food consumption patterns, and economic developments within regions. Our results indicate that the annual aging-embodied global food GHG emissions will reach 288 million tonnes of CO2 equivalent (Mt CO2e) by 2100. This estimation is crucial for policymakers, entrepreneurs, and researchers as it provides insights into a potential future environmental challenge and emphasizes the importance of sustainable food production and consumption strategies to GHG emission mitigations associated with aging dietary patterns.

Relationship among weather variation, agricultural production, and migration: A systematic methodological review

Background and Aims

Two main problems the globe currently facing are migration and weather variation. Weather change has a significant impact on the agricultural industry, which affects the majority of poor people. There is a dearth of adequate methodological documentation when examining the relationship between weather variation, agricultural output, and migration. We aimed to identify methodological reporting difficulties by reviewing the quantitative literature on weather-related migration through agricultural channels.

Methods

A systematic evaluation was conducted using papers published between January 2010 and June 2022, indexed in the SCOPUS, PUBMED, and Google Scholar databases. Using inclusion/exclusion criteria, we selected 22 original research articles out of 18,929 distinct articles for review, in accordance with the PRISMA guidelines. We extracted data from each study to understand how various concepts, research designs, and investigative techniques influence our understanding of migration patterns related to weather in the agricultural sector.

Results

The majority (64%) of the study's data consisted of time series data. In 50% of the studies, secondary data were used. Additionally, 55% of these studies did not state the sample size. In 40% of the studies, model assumptions were fully adhered to, whereas in 36% of the studies, they were not followed at all. The majority of the articles used the Ordinary Least Squares technique, while about 41% applied the Two-Stage Least Squares technique. Various tests were conducted across these studies, such as robustness checks (59.1%), endogeneity tests (31.8%), omitted variable bias tests (22.7%), sensitivity analyses (22.7%), and weak instrument tests (13.6%), to name a few. In the research we selected, the methodology section had various shortcomings and lacked organization. Furthermore, the justifications for deviations from model assumptions were unclear, potentially affecting the study outcomes.

Conclusion

This study has important indications for researchers in studying climatic (weather) migration through agricultural channels besides for policymakers by giving a thorough review of the methods and techniques.

Over 80% of the European Union's Common Agricultural Policy supports emissions-intensive animal products

The European Union's Common Agricultural Policy strongly influences the European Union's food system via agricultural subsidies. Linking global physical input-output datasets with public subsidy data reveals that current allocation favours animal-based foods, which uses 82% of the European Union's agricultural subsidies (38% directly and 44% for animal feed). Subsidy intensity (€ kg-1) for animal-based foods approximately doubles after feed inclusion. The same animal-based foods are associated with 84% of embodied greenhouse gas emissions of EU food production while supplying 35% of EU calories and 65% of proteins.

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.

Ensifer adhaerens strain OV14 seed application enhances Triticum aestivum L. and Brassica napus L. development

Given the challenges imposed by climate change and societal challenges, the European Union established ambitious goals as part of its Farm to Fork (F2F) strategy. Focussed on accelerating the transition to systems of sustainable food production, processing and consumption, a key element of F2F is to reduce the use of fertilisers by at least 20% and plant protection products by up to 50% by 2030. In recent years, a substantial body of research has highlighted the potential impact of microbial-based applications to support crop production practices through both biotic/abiotic stresses via maintaining or even improving yields and reducing reliance on intensive chemical inputs. Here, we have characterised the ability of a new soil-borne free-living bacterium strain Ensifer adhaerens OV14 (EaOV14) to significantly enhance crop vigour index by up to 50% for monocot (wheat, Triticum aestivum L., p < 0.0001) and by up to 40% for dicot (oilseed rape, Brassica napus L., p < 0.0001) species under in-vitro conditions (n = 360 seedlings/treatment). The beneficial effect was further studied under controlled glasshouse growing conditions (n = 60 plants/treatment) where EaOV14 induced significantly increased seed yield of spring oilseed rape compared to the controls (p < 0.0001). Moreover, using bespoke rhizoboxes, enhanced root architecture (density, roots orientation, roots thickness etc.) was observed for spring oilseed rape and winter wheat, with the median number of roots 55% and 33% higher for oilseed rape and wheat respectively, following EaOV14 seed treatment compared to the control. In addition, EaOV14 treatment increased root tip formation and root volume, suggesting the formation of a more robust root system architecture post-seed treatment. However, like other microbial formulations, the trade-offs associated with field translation, such as loss or limited functionality due to inoculum formulation or environmental distress, need further investigation. Moreover, the delivery method requires further optimisation to identify the optimal inoculum formulation that will maximise the expected beneficial impact on yield under field growing conditions.

Interactive Effects of Temperature, Water Regime, and [CO2] on Wheats with Different Heat Susceptibilities

Plants' response to single environmental changes can be highly distinct from the response to multiple changes. The effects of a single environmental factor on wheat growth have been well documented. However, the interactive influences of multiple factors on different wheat genotypes need further investigation. Here, treatments of three important growth factors, namely water regime, temperature, and CO2 concentration ([CO2]), were applied to compare the response of two wheat genotypes with different heat sensitivities. The temperature response curves showed that both genotypes showed more variations at elevated [CO2] (e[CO2]) than ambient [CO2] (a[CO2]) when the plants were treated under different water regimes and temperatures. This corresponded to the results of water use efficiency at the leaf level. At e[CO2], heat-tolerant 'Gladius' showed a higher net photosynthetic rate (Pn), while heat-susceptible 'Paragon' had a lower Pn at reduced water, as compared with full water availability. The temperature optimum for photosynthesis in wheat was increased when the growth temperature was high, while the leaf carbon/nitrogen was increased via a reduced water regime. Generally, water regime, temperature and [CO2] have significant interactive effects on both wheat genotypes. Two wheat genotypes showed different physiological responses to different combinations of environmental factors. Our investigation concerning the interactions of multi-environmental factors on wheat will benefit the future wheat climate-response study.

Predators control pests and increase yield across crop types and climates: a meta-analysis

Pesticides have well-documented negative consequences to control crop pests, and natural predators are alternatives and can provide an ecosystem service as biological control agents. However, there remains considerable uncertainty regarding whether such biological control can be a widely applicable solution, especially given ongoing climatic variation and climate change. Here, we performed a meta-analysis focused on field studies with natural predators to explore broadly whether and how predators might control pests and in turn increase yield. We also contrasted across studies pest suppression by a single and multiple predators and how climate influence biological control. Predators reduced pest populations by 73% on average, and increased crop yield by 25% on average. Surprisingly, the impact of predators did not depend on whether there were many or a single predator species. Precipitation seasonality was a key climatic influence on biological control: as seasonality increased, the impact of predators on pest populations increased. Taken together, the positive contribution of predators in controlling pests and increasing yield, and the consistency of such responses in the face of precipitation variability, suggest that biocontrol has the potential to be an important part of pest management and increasing food supplies as the planet precipitation patterns become increasingly variable.

Nanofibrous Biomaterial-Based Passive Cooling Paint Structurally Linked by Alkane-Oleate Interactions

Passive radiative cooling materials, which provide cooling without consuming electricity, are widely recognized as an important technology for reducing greenhouse gas emissions and delivering thermal comfort to less industrialized communities. Optimizing thermal and optical properties is of primary importance for these materials, but for real-world utilization, ease of application and scalability also require significant emphasis. In this work, we embed the biomaterial hydroxyapatite, in the form of nanoscale fibers, within an oil-based medium to achieve passive cooling from an easy-to-apply paint-like solution. The chemical structure and bonding behaviors of this mixture are studied in detail using FTIR, providing transferable conclusions for pigment-like passive cooling solutions. By reflecting 95% of solar energy and emitting 92% of its radiative output through the atmospheric transparency window, this composite material realizes an average subambient cooling performance of 3.7 °C in outdoor conditions under a mean solar irradiance of 800 W m-2. The inflammability of the material provides enhanced durability as well as unique opportunities for recycling which promote circular economic practices. Finally, the surface structure can be easily altered to tune bonding behaviors and hydrophobicity, making it an ideal passive cooling coating candidate for outdoor applications.

Maize green leaf area index dynamics: genetic basis of a new secondary trait for grain yield in optimal and drought conditions

KEY MESSAGE

Green Leaf Area Index dynamics is a promising secondary trait for grain yield and drought tolerance. Multivariate GWAS is particularly well suited to identify the genetic determinants of the green leaf area index dynamics. Improvement of maize grain yield is impeded by important genotype-environment interactions, especially under drought conditions. The use of secondary traits, that are correlated with yield, more heritable and less prone to genotype-environment interactions, can increase breeding efficiency. Here, we studied the genetic basis of a new secondary trait: the green leaf area index (GLAI) dynamics over the maize life cycle. For this, we used an unmanned aerial vehicle to characterize the GLAI dynamics of a diverse panel in well-watered and water-deficient trials in two years. From the dynamics, we derived 24 traits (slopes, durations, areas under the curve), and showed that six of them were heritable traits representative of the panel diversity. To identify the genetic determinants of GLAI, we compared two genome-wide association approaches: a univariate (single-trait) method and a multivariate (multi-trait) method combining GLAI traits, grain yield, and precocity. The explicit modeling of correlation structure between secondary traits and grain yield in the multivariate mixed model led to 2.5 times more associations detected. A total of 475 quantitative trait loci (QTLs) were detected. The genetic architecture of GLAI traits appears less complex than that of yield with stronger-effect QTLs that are more stable between environments. We also showed that a subset of GLAI QTLs explains nearly one fifth of yield variability across a larger environmental network of 11 water-deficient trials. GLAI dynamics is a promising grain yield secondary trait in optimal and drought conditions, and the detected QTLs could help to increase breeding efficiency through a marker-assisted approach.

Co-benefits for net carbon emissions and rice yields through improved management of organic nitrogen and water

Returning organic nutrient sources (for example, straw and manure) to rice fields is inevitable for coupling crop-livestock production. However, an accurate estimate of net carbon (C) emissions and strategies to mitigate the abundant methane (CH4) emission from rice fields supplied with organic sources remain unclear. Here, using machine learning and a global dataset, we scaled the field findings up to worldwide rice fields to reconcile rice yields and net C emissions. An optimal organic nitrogen (N) management was developed considering total N input, type of organic N source and organic N proportion. A combination of optimal organic N management with intermittent flooding achieved a 21% reduction in net global warming potential and a 9% rise in global rice production compared with the business-as-usual scenario. Our study provides a solution for recycling organic N sources towards a more productive, carbon-neutral and sustainable rice-livestock production system on a global scale.

Gene pyramiding for boosted plant growth and broad abiotic stress tolerance

Abiotic stresses such as salinity, heat and drought seriously impair plant growth and development, causing a significant loss in crop yield and ornamental value. Biotechnology approaches manipulating specific genes prove to be effective strategies in crop trait modification. The Arabidopsis vacuolar pyrophosphatase gene AVP1, the rice SUMO E3 ligase gene OsSIZ1 and the cyanobacterium flavodoxin gene Fld have previously been implicated in regulating plant stress responses and conferring enhanced tolerance to different abiotic stresses when individually overexpressed in various plant species. We have explored the feasibility of combining multiple favourable traits brought by individual genes to acquire superior plant performance. To this end, we have simultaneously introduced AVP1, OsSIZ1 and Fld in creeping bentgrass. Transgenic (TG) plants overexpressing these three genes performed significantly better than wild type controls and the TGs expressing individual genes under both normal and various abiotic stress conditions, exhibited significantly enhanced plant growth and tolerance to drought, salinity and heat stresses as well as nitrogen and phosphate starvation, which were associated with altered physiological and biochemical characteristics and delicately fine-tuned expression of genes involved in plant stress responses. Our results suggest that AVP1, OsSIZ1 and Fld function synergistically to regulate plant development and plant stress response, leading to superior overall performance under both normal and adverse environments. The information obtained provides new insights into gene stacking as an effective approach for plant genetic engineering. A similar strategy can be extended for the use of other beneficial genes in various crop species for trait modifications, enhancing agricultural production.

Global spatially explicit yield gap time trends reveal regions at risk of future crop yield stagnation

Yield gaps, here defined as the difference between actual and attainable yields, provide a framework for assessing opportunities to increase agricultural productivity. Previous global assessments, centred on a single year, were unable to identify temporal variation. Here we provide a spatially and temporally comprehensive analysis of yield gaps for ten major crops from 1975 to 2010. Yield gaps have widened steadily over most areas for the eight annual crops and remained static for sugar cane and oil palm. We developed a three-category typology to differentiate regions of 'steady growth' in actual and attainable yields, 'stalled floor' where yield is stagnated and 'ceiling pressure' where yield gaps are closing. Over 60% of maize area is experiencing 'steady growth', in contrast to ∼12% for rice. Rice and wheat have 84% and 56% of area, respectively, experiencing 'ceiling pressure'. We show that 'ceiling pressure' correlates with subsequent yield stagnation, signalling risks for multiple countries currently realizing gains from yield growth.

CRISPR/Cas system: A revolutionary tool for crop improvement

World's population is elevating at an alarming rate thus, the rising demands of producing crops with better adaptability to biotic and abiotic stresses, superior nutritional as well as morphological qualities, and generation of high-yielding varieties have led to encourage the development of new plant breeding technologies. The availability and easy accessibility of genome sequences for a number of crop plants as well as the development of various genome editing technologies such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) has opened up possibilities to develop new varieties of crop plants with superior desirable traits. However, these approaches has limitation of being more expensive as well as having complex steps and time-consuming. The CRISPR/Cas genome editing system has been intensively studied for allowing versatile target-specific modifications of crop genome that fruitfully aid in the generation of novel varieties. It is an advanced and promising technology with the potential to meet hunger needs and contribute to food production for the ever-growing human population. This review summarizes the usage of novel CRISPR/Cas genome editing tool for targeted crop improvement in stress resistance, yield, quality and nutritional traits in the desired crop plants.

Plants and global warming: challenges and strategies for a warming world

KEY MESSAGE

In this review, we made an attempt to create a holistic picture of plant response to a rising temperature environment and its impact by covering all aspects from temperature perception to thermotolerance. This comprehensive account describing the molecular mechanisms orchestrating these responses and potential mitigation strategies will be helpful for understanding the impact of global warming on plant life. Organisms need to constantly recalibrate development and physiology in response to changes in their environment. Climate change-associated global warming is amplifying the intensity and periodicity of these changes. Being sessile, plants are particularly vulnerable to variations happening around them. These changes can cause structural, metabolomic, and physiological perturbations, leading to alterations in the growth program and in extreme cases, plant death. In general, plants have a remarkable ability to respond to these challenges, supported by an elaborate mechanism to sense and respond to external changes. Once perceived, plants integrate these signals into the growth program so that their development and physiology can be modulated befittingly. This multifaceted signaling network, which helps plants to establish acclimation and survival responses enabled their extensive geographical distribution. Temperature is one of the key environmental variables that affect all aspects of plant life. Over the years, our knowledge of how plants perceive temperature and how they respond to heat stress has improved significantly. However, a comprehensive mechanistic understanding of the process still largely elusive. This review explores how an increase in the global surface temperature detrimentally affects plant survival and productivity and discusses current understanding of plant responses to high temperature (HT) and underlying mechanisms. We also highlighted potential resilience attributes that can be utilized to mitigate the impact of global warming.

Statistical-dynamical modeling of the maize yield response to future climate change in West, East and Central Africa using the regional climate model REMO

Africa is vulnerable to the impacts of climate change, particularly in terms of its agriculture and crop production. The majority of climate models project a negative impact of future climate change on crop production, with maize being particularly vulnerable. However, the magnitude of this change remains uncertain. Therefore, it is important to reduce the uncertainties related to the anticipated changes to guide adaptation options. This study uses a combination of local and large-scale empirical orthogonal function (EOF) predictors as a novel approach to model the impacts of future climate change on crop yields in West, East and Central Africa. Here a cross-validated Bayesian model was developed using predictors derived from the regional climate model REMO for the period 1982-2100. On average, the combined local and large-scale EOF predictors explained around 28 % of maize yield variability from 1982 to 2016 of the entire study regions. Notably, climate predictors played a significant role in West Africa, explaining up to 51 % of the maize yield variability. Large-scale climate EOF predictors contributed most to the explained variance, reflecting the role of regional climate in future maize yield variability. Under a high-emissions scenario (RCP8.5), maize yield is projected to decrease over the entire study region by 20 % by the end of the century. However, a minor increase is projected in eastern Africa. This study highlights the importance of incorporating climate predictors at various scales into crop yield modeling. Furthermore, the findings will offer valuable guidance to decision-makers in shaping adaptation options.

Effect of a Fortified Biostimulant Extract on Tomato Plant Productivity, Physiology, and Growing Media Properties

The pursuit of sustainable and productive agriculture demands the exploration of innovative approaches to improve plant productivity and soil health. The utilization of natural agricultural biostimulants, such as extracts from seaweed, fish, and humus, has gained prominence as an ecological strategy to achieve this goal. In this study we investigated the effectiveness of a fortified biostimulant extract (FBE), composed of extracts from seaweed, fish, and humus, on tomato plant physiology, productivity, and growing media properties, and estimated carbon emissions associated with tomato production. The FBE was applied to the growing media of tomato plants produced in a greenhouse, in experiments over two growing seasons. The productivity assessments demonstrated that the application of FBE significantly increased tomato fruit yield by 20% and relative marketable fruit yield by 27%, and reduced estimated greenhouse gas (GHG) emissions associated with production by 29%. FBE treatment improved plant shoot and root biomass, accelerated flower and fruit set initiation, and increased chlorophyll content in leaves, resulting in enhanced plant physiology and advanced development. FBE treatment positively influenced the availability of crucial nutrients such as nitrogen, phosphorus, and iron in the growing media. FBE promoted the growth of total active microbes in the growing media, particularly the fungal population, which plays an important role in nutrient cycling and health. These findings highlight the beneficial effects of the FBE due to enhanced plant productivity and growth, improved fertility, the promotion of beneficial plant and growing media interactions, and the reduction in estimated GHG emissions.

The 'microbiome counterattack': Insights on the soil and root-associated microbiome in diverse chickpea and lentil genotypes after an erratic rainfall event

Legumes maintain soil fertility thanks to their associated microbiota but are threatened by climate change that causes soil microbial community structural and functional modifications. The core microbiome associated with different chickpea and lentil genotypes was described after an unexpected climatic event. Results showed that chickpea and lentil bulk soil microbiomes varied significantly between two sampling time points, the first immediately after the rainfall and the second 2 weeks later. Rhizobia were associated with the soil of the more productive chickpea genotypes in terms of flower and fruit number. The root-associated bacteria and fungi were surveyed in lentil genotypes, considering that several parcels showed disease symptoms. The metabarcoding analysis revealed that reads related to fungal pathogens were significantly associated with one lentil genotype. A lentil core prokaryotic community common to all genotypes was identified as well as a genotype-specific one. A higher number of specific bacterial taxa and an enhanced tolerance to fungal diseases characterized a lentil landrace compared to the commercial varieties. This outcome supported the hypothesis that locally adapted landraces might have a high recruiting efficiency of beneficial soil microbes.

Approaches to Address the Anemia Challenge

Anemia is a multifactorial condition; approaches to address it must recognize that the causal factors represent an ecology consisting of internal (biology, genetics, and health) and external (social/behavioral/demographic and physical) environments. In this paper, we present an approach for selecting interventions, followed by a description of key issues related to the multiple available interventions for prevention and reduction of anemia. We address interventions for anemia using the following 2 main categories: 1) those that address nutrients alone, and, 2) those that address nonnutritional causes of anemia. The emphasis will be on interventions of public health relevance, but we also consider the clinical context. We also focus on interventions at different stages of the life course, with a particular focus on women of reproductive age and preschool-age children, and present evidence on various factors to consider when selecting an intervention-inflammation, genetic mutations, nutrient delivery, bioavailability, and safety. Each section on an intervention domain concludes with a brief discussion of key research areas.

Proteomics and Metabolomics Reveal that an Abundant α-Glucosidase Drives Sorghum Fermentability for Beer Brewing

Sorghum (Sorghum bicolor), a grass native to Africa, is a popular alternative to barley for brewing beer. The importance of sorghum to beer brewing is increasing because it is a naturally gluten-free cereal, and climate change is expected to cause a reduction in the production of barley over the coming decades. However, there are challenges associated with the use of sorghum instead of barley in beer brewing. Here, we used proteomics and metabolomics to gain insights into the sorghum brewing process to advise processes for efficient beer production from sorghum. We found that during malting, sorghum synthesizes the amylases and proteases necessary for brewing. Proteomics revealed that mashing with sorghum malt required higher temperatures than barley malt for efficient protein solubilization. Both α- and β-amylase were considerably less abundant in sorghum wort than in barley wort, correlating with lower maltose concentrations in sorghum wort. However, metabolomics revealed higher glucose concentrations in sorghum wort than in barley wort, consistent with the presence of an abundant α-glucosidase detected by proteomics in sorghum malt. Our results indicate that sorghum can be a viable grain for industrial fermented beverage production, but that its use requires careful process optimization for efficient production of fermentable wort and high-quality beer.

Geospatial technology in agroforestry: status, prospects, and constraints

Agroforestry has an indispensable role in food and livelihood security in addition to its capacity to combat the detrimental effects of climate change. However, agroforestry has not been properly promoted and exploited due to lack of precise extent, geographical distribution, and carbon sequestration (CS) assessment. The recent advent of geospatial technologies, as well as free availability of spatial data and software, can provide new insights into agroforestry resources assessment, decision-making, and policy development despite agroforestry's small spatial extent, isolated nature, and higher structural and functional complexity of agroforestry. In this review, the existing application of geospatial technologies together with its constraints and limitations as well as the potential future application for agroforestry has been discussed. The review reveals that the application of optical remote sensing in agroforestry includes spatial extent mapping, production of tree species spectral signature, CS assessment, and suitability mapping. Simultaneously, the recent surge in the use of synthetic aperture radar in conjunction with algorithms based on vegetation photosynthesis and optical data enables a more accurate estimation of gross primary productivity at different scales. However, unmanned aerial vehicles equipped with sensors, such as multispectral, LiDAR, hyperspectral, and thermal, offer a considerably higher potential and accuracy than satellite-based datasets. In the future, the health monitoring of agroforestry systems can be a key concern that may be addressed by utilizing hyperspectral and thermal datasets to analyze plant biochemistry, chlorophyll fluorescence, and water stress. Additionally, current (GEDI, ECOSTRESS) and future space agency missions (BIOMASS, FLEX, NISAR, TRISHNA) have enormous potential to shed fresh light on agroforestry systems.

Modelling the climate change impact of mitigation (RCP 2.6) and high emission (RCP 8.5) scenarios on maize yield and possible adaptation measures in different agroclimatic zones of Punjab, India

BACKGROUND

A simulation study was performed for assessing climate change impact on maize under Representative Concentration Pathways (RCPs 2.6 and 8.5) for Punjab, India. The study area comprised five agroclimatic zones (AZs) including seven locations. The bias corrected temperature and rainfall data from four models (CSIRO-Mk-3-6-0, FIO-ESM, IPSL-CM5A-MR and Ensemble) were used as input in CERES-Maize model which was run with constant management practices for two Punjab maize hybrids (PMH 1 and PMH 2). The maize yield for upcoming 70 years (2025-2095) was simulated and its deviations from the baseline (2010-2021) yield were computed under optimized sowing (early-May to early-July) and current sowing (end-May to end-June) period.

RESULTS

With current sowing dates, the maize yield declined under both RCP 2.6 and RCP 8.5 scenarios, respectively in all the AZs, that is, by 4-23% and 60-80% in AZ II, by 5-60% and 60-90% in AZ III, by 9-30% and 50-90% in AZ IV and by 13-40% and 30-90% in AZ V. Though yield decline was lesser under RCP 2.6 as compared to RCP 8.5, but still it indicates that adaptive strategy such as shifting of sowing dates may be helpful in stabilizing the maize yield.

CONCLUSION

The results for iterative combinations of sowing period revealed that early June sowing in AZ II for both the hybrids, mid- to end-June (Ludhiana and Amritsar) and end-May to mid-June (Patiala) sowings for PMH 1 were able to nullify the negative impact of climate change. Maize cultivation in AZ IV and AZ V would not be a suitable venture for farmers of the region. © 2023 Society of Chemical Industry.

Transcriptome and Physiological Analysis of Rapeseed Tolerance to Post-Flowering Temperature Increase

Climate-change-induced temperature fluctuations pose a significant threat to crop production, particularly in the Southern Hemisphere. This study investigates the transcriptome and physiological responses of rapeseed to post-flowering temperature increases, providing valuable insights into the molecular mechanisms underlying rapeseed tolerance to heat stress. Two rapeseed genotypes, Lumen and Solar, were assessed under control and heat stress conditions in field experiments conducted in Valdivia, Chile. Results showed that seed yield and seed number were negatively affected by heat stress, with genotype-specific responses. Lumen exhibited an average of 9.3% seed yield reduction, whereas Solar showed a 28.7% reduction. RNA-seq analysis of siliques and seeds revealed tissue-specific responses to heat stress, with siliques being more sensitive to temperature stress. Hierarchical clustering analysis identified distinct gene clusters reflecting different aspects of heat stress adaptation in siliques, with a role for protein folding in maintaining silique development and seed quality under high-temperature conditions. In seeds, three distinct patterns of heat-responsive gene expression were observed, with genes involved in protein folding and response to heat showing genotype-specific expression. Gene coexpression network analysis revealed major modules for rapeseed yield and quality, as well as the trade-off between seed number and seed weight. Overall, this study contributes to understanding the molecular mechanisms underlying rapeseed tolerance to heat stress and can inform crop improvement strategies targeting yield optimization under changing environmental conditions.

Edible fire buffers: Mitigation of wildfire with multifunctional landscapes

Wildfires ravage lands in seasonally dry regions, imposing high costs on infrastructure maintenance and human habitation at the wildland-urban interface. Current fire mitigation approaches present upfront costs with uncertain long-term payoffs. We show that a new landscape intervention on human-managed wildlands-buffers of a low-flammability crop species such as banana irrigated using recycled water-can mitigate wildfires and produce food profitably. This new intervention can complement existing fire mitigation approaches. Recreating a recent, major fire in simulation, we find that a medium-sized (633 m) banana buffer decreases fireline intensity by 96%, similar to the combination of prescribed burns and mechanical thinning, and delays the fire by 316 min, enabling safer and more effective firefighting. We find that under climate change, despite worsened fires, banana buffers will still have a protective effect. We also find that banana buffers with average yield could produce a profit of $56k USD/hectare through fruit sales, in addition to fire mitigation.

The neglected role of abandoned cropland in supporting both food security and climate change mitigation

Despite the looming land scarcity for agriculture, cropland abandonment is widespread globally. Abandoned cropland can be reused to support food security and climate change mitigation. Here, we investigate the potentials and trade-offs of using global abandoned cropland for recultivation and restoring forests by natural regrowth, with spatially-explicit modelling and scenario analysis. We identify 101 Mha of abandoned cropland between 1992 and 2020, with a capability of concurrently delivering 29 to 363 Peta-calories yr-1 of food production potential and 290 to 1,066 MtCO2 yr-1 of net climate change mitigation potential, depending on land-use suitability and land allocation strategies. We also show that applying spatial prioritization is key to maximizing the achievable potentials of abandoned cropland and demonstrate other possible approaches to further increase these potentials. Our findings offer timely insights into the potentials of abandoned cropland and can inform sustainable land management to buttress food security and climate goals.

Agronomic Evaluation and Molecular Cytogenetic Characterization of Triticum aestivum × Thinopyrum spp. Derivative Breeding Lines Presenting Perennial Growth Habits

The transition from annual to perennial growth habits can contribute to increased sustainability and diversification of staple cropping systems like those based on annual wheat. Amphiploids between Triticum aestivum and Thinopyrum spp. can present a wheat-like morphology and post sexual cycle regrowth. The complex and unpredictable nature of the chromosomal rearrangements typical of inter-generic hybrids can hamper progress in the development of this new crop. By using fluorescence in situ hybridization, we described the genomic constitution of three perennial wheat breeding lines that regrew and completed a second year of production in field conditions in Washington state (USA). Two breeding lines presented stable, 56-chromosome partial amphiploids; however, their chromosome composition differed significantly. The third breeding line presented an unstable karyotype with a chromosome number ranging from 53 to 58 across eight individuals. The agronomic performance of the perennial breeding lines was evaluated for two growing seasons from 2020 to 2022. The grain yields of the perennial lines were lower than the grain production of the annual wheat control line in the first season. The perennial lines displayed vigorous regrowth after the initial harvest; however, worsening environmental conditions in the second season of growth hampered subsequent growth and grain yield. This information facilitates the breeding work necessary to improve key traits by grouping agronomically valuable individuals according to their genomic constitution.

Temporal variation of the relationships between rice yield and climate variables since 1925

Background

Long-term time-series datasets of crop yield and climate variables are necessary to study the temporal variation of climate effects on crops. The aim of this study was to broadly assess assessment of the effects of climate on rice, and the associated temporal variations of the effects during the long-term period.

Methods

We conducted field experiments in Taiwan from 1925 to 2019 to collect and analyze rice yield data and evaluate the impacts of changes in average temperature, diurnal temperature range (DTR), rainfall, and sunshine duration on rice yield during cool and warm cropping seasons. We then estimated the relationships between annual grain yield and the climate variables using the time series of their first difference values. We also computed the total relative and annual actual yield changes using regression coefficients for each climate variable for the intervals 1925-1944, 1945-1983, and 1996-2019 to reveal the impacts of climate change on yields and the associated temporal variations during the overall experimental period.

Results

The annual daily average temperature calculated from the trend of the regression lines increased by 0.94-1.03 °C during the 95-year period. The maximum temperature remained steady while the minimum temperature increased, leading to decreased DTR. The total annual rainfall decreased by 237-352 mm and the annual total sunshine duration decreased by 93.9-238.9 h during the experimental period. We observed that during the cool cropping season, yield response to temperature change decreased, while that to DTR and rainfall changes increased. During the warm cropping season, all the yield responses to temperature, DTR, and rainfall changes were negative throughout the experimental period. In recent years (1996-2019) the estimated annual actual rice yield changes during the cool cropping season were negatively affected by climate variables (except for sunshine duration), and slightly positively affected (except for temperature) during the warm cropping season. Compared to the effects of temperature and DTR, those of rainfall and sunshine duration on rice yield changes were weak. This study contributes to provide impacts of climate change on rice yield and associated long-term temporal variations over nearly a century.

Linking genetic and environmental factors through marker effect networks to understand trait plasticity

Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.

High temperature inhibits vascular development via the PIF4-miR166-HB15 module in Arabidopsis

The plant vascular system is an elaborate network of conducting and supporting tissues that extends throughout the plant body, and its structure and function must be orchestrated with different environmental conditions. Under high temperature, plants display thin and lodging stems that may lead to decreased yield and quality of crops. However, the molecular mechanism underlying high-temperature-mediated regulation of vascular development is not known. Here, we show that Arabidopsis plants overexpressing the basic-helix-loop-helix (bHLH) transcription factor PHYTOCHROME INTERACTING FACTOR 4 (PIF4), a central regulator of high-temperature signaling, display fewer vascular bundles (VBs) and decreased secondary cell wall (SCW) thickening, mimicking the lodging inflorescence stems of high-temperature-grown wild-type plants. Rising temperature and elevated PIF4 expression reduced the expression of MIR166 and, concomitantly, elevated the expression of the downstream class III homeodomain leucine-zipper (HD-ZIP III) family gene HB15. Consistently, knockdown of miR166 and overexpression of HB15 led to inhibition of vascular development and SCW formation, whereas the hb15 mutant displayed the opposite phenotype in response to high temperature. Moreover, in vitro and in vivo assays verified that PIF4 binds to the promoters of several MIR166 genes and represses their expression. Our study establishes a direct functional link between PIF4 and the miR166-HB15 module in modulating vascular development and SCW thickening and consequently stem-lodging susceptibility at elevated temperatures.

Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Measuring climate change's impact on different sugarcane varieties production in the South of Goiás

A crucial aspect analysed during the last years, aiming to improve sugarcane production, is the impact of climate change on sugarcane productivity. One of the strategies to mitigate climate change's impact on sugarcane yield is the development of new varieties known to positively affect crop production. This paper analysed how climate change impacts sugarcane production regarding the different planted varieties. Data regarding sugarcane harvest were collected from a cooperative in the south of Goiás state-Brazil, the second biggest national sugarcane producer. Results indicate that climate impact on sugarcane yield is irrelevant when controlling for different varieties. Considering the results presented in this work, the Brazilian government should keep the incentives for the development of new sugarcane varieties and, at the same time, spur sugarcane producers to use the new sugarcane varieties. The results imply that if the variety is correctly chosen, sugarcane can be produced without harming the environment, contributing to reaching SDG 15. Moreover, it is less probable that an adverse climatic event will destroy the planted area, preventing sugarcane producers from severe loss and contributing to achieving SDGs number 1 and 2.

The Regulatory Network of Sweet Corn (Zea mays L.) Seedlings under Heat Stress Revealed by Transcriptome and Metabolome Analysis

Heat stress is an increasingly significant abiotic stress factor affecting crop yield and quality. This study aims to uncover the regulatory mechanism of sweet corn response to heat stress by integrating transcriptome and metabolome analyses of seedlings exposed to normal (25 °C) or high temperature (42 °C). The transcriptome results revealed numerous pathways affected by heat stress, especially those related to phenylpropanoid processes and photosynthesis, with 102 and 107 differentially expressed genes (DEGs) identified, respectively, and mostly down-regulated in expression. The metabolome results showed that 12 or 24 h of heat stress significantly affected the abundance of metabolites, with 61 metabolites detected after 12 h and 111 after 24 h, of which 42 metabolites were detected at both time points, including various alkaloids and flavonoids. Scopoletin-7-o-glucoside (scopolin), 3-indolepropionic acid, acetryptine, 5,7-dihydroxy-3',4',5'-trimethoxyflavone, and 5,6,7,4'-tetramethoxyflavanone expression levels were mostly up-regulated. A regulatory network was built by analyzing the correlations between gene modules and metabolites, and four hub genes in sweet corn seedlings under heat stress were identified: RNA-dependent RNA polymerase 2 (RDR2), UDP-glucosyltransferase 73C5 (UGT73C5), LOC103633555, and CTC-interacting domain 7 (CID7). These results provide a foundation for improving sweet corn development through biological intervention or genome-level modulation.

Flowering and fruit-set in cassava under extended red-light photoperiod supplemented with plant-growth regulators and pruning

BACKGROUND

Cassava (Manihot esculenta Crantz) is staple food and major source of calories for over 500 million people in sub-Saharan Africa. The crop is also a source of income for smallholder farmers, and has increasing potential for industrial utilization. However, breeding efforts to match the increasing demand of cassava are impeded by its inability to flower, delayed or unsynchronized flowering, low proportion of female flowers and high fruit abortions. To overcome these sexual reproductive bottlenecks, this study investigated the effectiveness of using red lights to extend the photoperiod (RLE), as a gateway to enhancing flowering and fruit set under field conditions.

MATERIALS AND METHODS

Panels of cassava genotypes, with non- or late and early flowering response, 10 in each case, were subjected to RLE from dusk to dawn. RLE was further evaluated at low (LL), medium (ML) and high (HL) red light intensities, at ~  ≤ 0.5; 1.0 and 1.5PFD (Photon Flux Density) in µmol m^-2 s^-1 respectively. Additionally, the effect of a cytokinin and anti-ethylene as plant growth regulators (PGR) and pruning under RLE treatment were examined.

RESULTS

RLE stimulated earlier flower initiation in all genotypes, by up to 2 months in the late-flowering genotypes. Height and number of nodes at first branching, particularly in the late-flowering genotypes were also reduced, by over 50%. Number and proportion of pistillate flowers more than doubled, while number of fruits and seeds also increased. Number of branching levels during the crop season also increased by about three. Earlier flowering in many genotypes was most elicited at LL to ML intensities. Additive effects on flower numbers were detected between RLE, PGR and pruning applications. PGR and pruning treatments further increased number and proportion of pistillate flowers and fruits. Plants subjected to PGR and pruning, developed bisexual flowers and exhibited feminization of staminate flowers. Pruning at first branching resulted in higher pistillate flower induction than at second branching.

CONCLUSIONS

These results indicate that RLE improves flowering in cassava, and its effectiveness is enhanced when PGR and pruning are applied. Thus, deployment of these technologies in breeding programs could significantly enhance cassava hybridizations and thus cassava breeding efficiency and impact.

The role of harmonized Landsat Sentinel-2 (HLS) products to reveal multiple trajectories and determinants of cropland abandonment in subtropical mountainous areas

Cropland abandonment is a widespread land-change process globally, which can stem from the accelerated outmigration of the population from rural to urban areas, socio-economic and political changes, catastrophes, and other trigger events. Clouds limit the utility of optical satellite data to monitor cropland abandonment in highly fragmented mountain agricultural landscapes of tropical and subtropical regions, including the south of China. Taking Nanjing County of China as an example, we developed a novel approach by utilizing multisource satellite (Landsat and Sentinel-2) imagery to map multiple trajectories of cropland abandonment (transitioning from cropland to grassland, shrubs and forest) in subtropical mountainous landscapes. Then, we employed a redundancy analysis (RDA) to identify the spatial association of cropland abandonment considering agricultural productivity, physiography, locational characteristics and economic factors. Results indicate the great suitability of harmonized Landsat 8 and Sentinel-2 images to distinguish multiple trajectories of cropland abandonment in subtropical mountainous areas. Our framework of mapping cropland abandonment resulted in good producer's (78.2%) and user's (81.3%) accuracies. The statistical analysis showed 31.85% of croplands cultivated in 2000 were abandoned by 2018, and more than a quarter of townships experienced cropland abandonment with high abandoned rates (>38%). Cropland abandonment mainly occurred in relatively unfavorable areas for agricultural production, for instance with a slope above 6°. Slope and the proximity to the nearest settlement explained 65.4% and 8.1% of the variation of cropland abandonment at the township level, respectively. The developed approaches on both mapping cropland abandonment and modeling determinants can be highly relevant to monitor multiple trajectories of cropland abandonment and ascribe their determinants not only in mountainous China but also elsewhere and thus promote the formulation of land-use policies that aim to steer cropland abandonment.

"Measuring the Environmental Context of Child Growth in Burkina Faso"

Child growth failure, as indicated by low height-for-age z-scores (HAZ), is an important metric of health, social inequality, and food insecurity. Understanding the environmental pathways to this outcome can provide insight into how to prevent it. While other studies have examined the environmental determinants of HAZ, there is no agreed upon best-practices approach to measure the environmental context of this outcome. From this literature, we derive a large set of potential environmental predictors and specifications including temperature and precipitation levels, anomalies, and counts as well as vegetation anomalies and trends, which we include using linear, nonlinear, and interactive specifications. We compare these measures and specifications using four rounds of DHS survey data from Burkina Faso and a large set of fixed effects regression models, focusing on exposures from the time of conception through the second year of life and relying on joint hypothesis tests and goodness-of-fit measures to determine which approach best explains HAZ. Our analysis reveals that nonlinear and interactive transformations of climate anomalies, as opposed to climate levels or vegetation indices, provide the best explanation of child growth failure. These results underline the complex and nonlinear pathways through which climate change affects child health and should motivate climate-health researchers to more broadly adopt measures and specifications that capture these pathways.

The impacts of climatic conditions on cereal production: implications for food security in Africa

Climate change is a confounding factor that affects food security in several ways. Although the analyses of earlier studies in this area were largely non-technical, new analytical techniques have been developed to comprehensively evaluate climate change patterns and their implications for food security. In this study, we use recent developments in panel econometrics, which consider cross-sectional dependence and parameter heterogeneity, to examine the effects of climatic conditions on cereal farming in Africa from 1970Q1 to 2017Q4. The results show that rainfall positively affects cereal crops, although average temperatures are typically unfavourable. In the country-specific scenarios, we observed significant variations in the influence of climatic conditions on cereal production. The causality test results show a two-way causal relationship between climatic conditions-rainfall and temperature-and cereal production. It is suggested that African governments and non-governmental organisations support farmers' adaptation to climate change by implementing policies that prioritise farmers' capacity building and ensure that extension service officers engage with farmers intensively.

Cassava begomovirus species diversity changes during plant vegetative cycles

Cassava is a root crop important for global food security and the third biggest source of calories on the African continent. Cassava production is threatened by Cassava mosaic disease (CMD), which is caused by a complex of single-stranded DNA viruses (family: Geminiviridae, genus: Begomovirus) that are transmitted by the sweet potato whitefly (Bemisia tabaci). Understanding the dynamics of different cassava mosaic begomovirus (CMB) species through time is important for contextualizing disease trends. Cassava plants with CMD symptoms were sampled in Lake Victoria and coastal regions of Kenya before transfer to a greenhouse setting and regular propagation. The field-collected and greenhouse samples were sequenced using Illumina short-read sequencing and analyzed on the Galaxy platform. In the field-collected samples, African cassava mosaic virus (ACMV), East African cassava mosaic virus (EACMV), East African cassava mosaic Kenya virus (EACMKV), and East African cassava mosaic virus-Uganda variant (EACMV-Ug) were detected in samples from the Lake Victoria region, while EACMV and East African mosaic Zanzibar virus (EACMZV) were found in the coastal region. Many of the field-collected samples had mixed infections of EACMV and another begomovirus. After 3 years of regrowth in the greenhouse, only EACMV-like viruses were detected in all samples. The results suggest that in these samples, EACMV becomes the dominant virus through vegetative propagation in a greenhouse. This differed from whitefly transmission results. Cassava plants were inoculated with ACMV and another EACMV-like virus, East African cassava mosaic Cameroon virus (EACMCV). Only ACMV was transmitted by whiteflies from these plants to recipient plants, as indicated by sequencing reads and copy number data. These results suggest that whitefly transmission and vegetative transmission lead to different outcomes for ACMV and EACMV-like viruses.

Green aid, aid fragmentation and carbon emissions

The existing studies that examined the green aid effectiveness in reducing carbon dioxide (CO2) emissions found mixed results; however, neither of these studies considered the role of aid fragmentation in the effectiveness of green aid flows. By using the dynamic panel generalized method of moments (GMM) methodology to panel data of 92 countries covering the period between 2002 and 2018, this study examines the impact of green aid fragmentation on the effectiveness of green aid flows in reducing CO2 emissions. Using different fragmentation measures, this paper finds that green aid fragmentation is detrimental to the effectiveness of green aid flows in reducing CO2 emissions per capita. The findings also highlight that the damaging impact of green aid fragmentation is lower in countries with stronger institutions. This paper highlights the need for better coordination of the green aid flows by having less fragmented green aid flows.

Variations in phenological, physiological, plant architectural and yield-related traits, their associations with grain yield and genetic basis

BACKGROUND AND AIMS

Physiological and morphological traits play essential roles in wheat (Triticum aestivum) growth and development. In particular, photosynthesis is a limitation to yield. Increasing photosynthesis in wheat has been identified as an important strategy to increase yield. However, the genotypic variations and the genomic regions governing morphological, architectural and photosynthesis traits remain unexplored.

METHODS

Here, we conducted a large-scale investigation of the phenological, physiological, plant architectural and yield-related traits, involving 32 traits for 166 wheat lines during 2018-2020 in four environments, and performed a genome-wide association study with wheat 90K and 660K single nucleotide polymorphism (SNP) arrays.

KEY RESULTS

These traits exhibited considerable genotypic variations in the wheat diversity panel. Higher yield was associated with higher net photosynthetic rate (r = 0.41, P < 0.01), thousand-grain weight (r = 0.36, P < 0.01) and truncated and lanceolate shape, but shorter plant height (r = -0.63, P < 0.01), flag leaf angle (r = -0.49, P < 0.01) and spike number per square metre (r = -0.22, P < 0.01). Genome-wide association mapping discovered 1236 significant stable loci detected in the four environments among the 32 traits using SNP markers. Trait values have a cumulative effect as the number of the favourable alleles increases, and significant progress has been made in determining phenotypic values and favourable alleles over the years. Eleven elite cultivars and 14 traits associated with grain yield per plot (GY) were identified as potential parental lines and as target traits to develop high-yielding cultivars.

CONCLUSIONS

This study provides new insights into the phenotypic and genetic elucidation of physiological and morphological traits in wheat and their associations with GY, paving the way for discovering their underlying gene control and for developing enhanced ideotypes in wheat breeding.