Explore the vast range of titles available.

The current trajectory for crop yields is insufficient to nourish the world’s population by 2050 1 . Greater and more consistent crop production must be achieved against a backdrop of climatic stress that limits yields, owing to shifts in pests and pathogens, precipitation, heat-waves and other weather extremes. Here we consider the potential of plant sciences to address post-Green Revolution challenges in agriculture and explore emerging strategies for enhancing sustainable crop production and resilience in a changing climate. Accelerated crop improvement must leverage naturally evolved traits and transformative engineering driven by mechanistic understanding, to yield the resilient production systems that are needed to ensure future harvests. Genetic strategies for improving the yield and sustainability of agricultural crops, and the resilience of crops in the face of biotic and abiotic stresses contingent on projected climate change, are evaluated.

Food security is the main challenge in the developing world, particularly in the least developed countries. Orphan crops play a vital role in the food security and livelihood of resource-poor farmers and consumers in these countries. Like major crops, there are members of all food types—cereals, legumes, vegetables and root and tuber crops, that are considered to be orphan crops. Despite their huge importance for present and future agriculture, orphan crops have generally received little attention by the global scientific community. Due to this, they produce inferior yields in terms of both quantity and quality. The major bottlenecks affecting the productivity of these crops are little or no selection of improved genetic traits, extreme environmental conditions and unfavorable policy. However, some orphan crops have recently received the attention of the global and national scientific community where advanced research and development initiatives have been launched. These initiatives which implement a variety of genetic and genomic tools targeted major constraints affecting productivity and/or nutritional quality of orphan crops. In this paper, some of these initiatives are briefly described. Here, I provide key suggestions to relevant stakeholders regarding improvement of orphan crops. Concerted efforts are urgently needed to advance the research and development of both the major and orphan crops so that food security will be achieved and ultimately the livelihood of the population will be improved.

Global food production faces challenges in balancing the need for increased yields with environmental sustainability. This study presents a six-year field experiment in the North China Plain, demonstrating the benefits of diversifying traditional cereal monoculture (wheat–maize) with cash crops (sweet potato) and legumes (peanut and soybean). The diversified rotations increase equivalent yield by up to 38%, reduce N 2 O emissions by 39%, and improve the system’s greenhouse gas balance by 88%. Furthermore, including legumes in crop rotations stimulates soil microbial activities, increases soil organic carbon stocks by 8%, and enhances soil health (indexed with the selected soil physiochemical and biological properties) by 45%. The large-scale adoption of diversified cropping systems in the North China Plain could increase cereal production by 32% when wheat–maize follows alternative crops in rotation and farmer income by 20% while benefiting the environment. This study provides an example of sustainable food production practices, emphasizing the significance of crop diversification for long-term agricultural resilience and soil health. Food production systems need to balance yield and sustainability. Here, the authors conduct 6 years long crop diversification field experiments in the North China Plain, showing that diversifying cereal monocultures with cash crops and legumes cand improve yield and reduce GHG emissions.

The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

Out of several thousand known edible plant species, only four crops-rice, wheat, maize and potato provide the largest proportion of daily nutrition to billions of people. While these crops are the primary supplier of carbohydrates, they lack essential amino acids and minerals for a balanced nutrition. The overdependence on only few crops makes the future cropping systems vulnerable to the predicted climate change. Diversifying food resources through incorporation of orphan or minor crops in modern cropping systems is one potential strategy to improve the nutritional security and mitigate the hostile weather patterns. One such crop is buckwheat, which can contribute to the agricultural sustainability as it grows in a wide range of environments, requires relatively low inputs and possess balanced amino acid and micronutrient profiles. Additionally, gluten-free nature of protein and nutraceutical properties of secondary metabolites make the crop a healthy alternative of wheat-based diet in developed countries. Despite enormous potential, efforts for the genetic improvement of buckwheat are considerably lagged behind the conventional cereal crops. With the draft genome sequences in hand, there is a great scope to speed up the progress of genetic improvement of buckwheat. This article outlines the state of the art in buckwheat research and provides concrete perspectives how modern breeding approaches can be implemented to accelerate the genetic gain. Our suggestions are transferable to many minor and underutilized crops to address the issue of limited genetic gain and low productivity.

Especially in low-income nations, new and orphan crops provide important opportunities to improve diet quality and the sustainability of food production, being rich in nutrients, capable of fitting into multiple niches in production systems, and relatively adapted to low-input conditions. The evolving space for these crops in production systems presents particular genetic improvement requirements that extensive gene pools are able to accommodate. Particular needs for genetic development identified in part with plant breeders relate to three areas of fundamental importance for addressing food production and human demographic trends and associated challenges, namely: facilitating integration into production systems; improving the processability of crop products; and reducing farm labour requirements. Here, we relate diverse involved target genes and crop development techniques. These techniques include transgressive methods that involve defining exemplar crop models for effective new and orphan crop improvement pathways. Research on new and orphan crops not only supports the genetic improvement of these crops, but they serve as important models for understanding crop evolutionary processes more broadly, guiding further major crop evolution. The bridging position of orphan crops between new and major crops provides unique opportunities for investigating genetic approaches for de novo domestications and major crop ‘rewildings’.

The contributions of crop wild relatives (CWR) to food security depend on their conservation and accessibility for use. The United States contains a diverse native flora of CWR, including those of important cereal, fruit, nut, oil, pulse, root and tuber, and vegetable crops, which may be threatened in their natural habitats and underrepresented in plant conservation repositories. To determine conservation priorities for these plants, we developed a national inventory, compiled occurrence information, modeled potential distributions, and conducted threat assessments and conservation gap analyses for 600 native taxa. We found that 7.1% of the taxa may be critically endangered in their natural habitats, 50% may be endangered, and 28% may be vulnerable. We categorized 58.8% of the taxa as of urgent priority for further action, 37% as high priority, and 4.2% as medium priority. Major ex situ conservation gaps were identified for 93.3% of the wild relatives (categorized as urgent or high priority), with 83 taxa absent from conservation repositories, while 93.1% of the plants were equivalently prioritized for further habitat protection. Various taxonomic richness hotspots across the US represent focal regions for further conservation action. Related needs include facilitating greater access to and characterization of these cultural-genetic-natural resources and raising public awareness of their existence, value, and plight.

Agriculture is now facing the ‘perfect storm’ of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic‐assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change.

Background The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors influencing crop growth, can greatly benefit from artificial intelligence (AI) methods like deep learning. The Agro Deep Learning Framework (ADLF) was developed to tackle critical issues in crop cultivation by processing vast datasets. These datasets include variables such as soil moisture, temperature, and humidity, all of which are essential to understanding and predicting crop behavior. By leveraging deep learning models, the framework seeks to improve decision-making processes, detect potential crop problems early, and boost agricultural productivity. Results The study found that the Agro Deep Learning Framework (ADLF) achieved an accuracy of 85.41%, precision of 84.87%, recall of 84.24%, and an F1-Score of 88.91%, indicating strong predictive capabilities for improving crop management. The false negative rate was 91.17% and the false positive rate was 89.82%, highlighting the framework's ability to correctly detect issues while minimizing errors. These results suggest that ADLF can significantly enhance decision-making in precision agriculture, leading to improved crop yield and reduced agricultural losses. Conclusions The ADLF can significantly improve precision agriculture by leveraging deep learning to process complex datasets and provide valuable insights into crop management. The framework allows farmers to detect issues early, optimize resource use, and improve yields. The study demonstrates that AI-driven agriculture has the potential to revolutionize farming, making it more efficient and sustainable. Future research could focus on further refining the model and exploring its applicability across different types of crops and farming environments.

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments.