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71,177 result(s) for "Crop yields"
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Genetic strategies for improving crop yields
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.
Yield Trends Are Insufficient to Double Global Crop Production by 2050
Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.
Remote-Sensing Data and Deep-Learning Techniques in Crop Mapping and Yield Prediction: A Systematic Review
Reliable and timely crop-yield prediction and crop mapping are crucial for food security and decision making in the food industry and in agro-environmental management. The global coverage, rich spectral and spatial information and repetitive nature of remote sensing (RS) data have made them effective tools for mapping crop extent and predicting yield before harvesting. Advanced machine-learning methods, particularly deep learning (DL), can accurately represent the complex features essential for crop mapping and yield predictions by accounting for the nonlinear relationships between variables. The DL algorithm has attained remarkable success in different fields of RS and its use in crop monitoring is also increasing. Although a few reviews cover the use of DL techniques in broader RS and agricultural applications, only a small number of references are made to RS-based crop-mapping and yield-prediction studies. A few recently conducted reviews attempted to provide overviews of the applications of DL in crop-yield prediction. However, they did not cover crop mapping and did not consider some of the critical attributes that reveal the essential issues in the field. This study is one of the first in the literature to provide a thorough systematic review of the important scientific works related to state-of-the-art DL techniques and RS in crop mapping and yield estimation. This review systematically identified 90 papers from databases of peer-reviewed scientific publications and comprehensively reviewed the aspects related to the employed platforms, sensors, input features, architectures, frameworks, training data, spatial distributions of study sites, output scales, evaluation metrics and performances. The review suggests that multiple DL-based solutions using different RS data and DL architectures have been developed in recent years, thereby providing reliable solutions for crop mapping and yield prediction. However, challenges related to scarce training data, the development of effective, efficient and generalisable models and the transparency of predictions should be addressed to implement these solutions at scale for diverse locations and crops.
The role of photosynthesis related pigments in light harvesting, photoprotection and enhancement of photosynthetic yield in planta
Photosynthetic pigments are an integral and vital part of all photosynthetic machinery and are present in different types and abundances throughout the photosynthetic apparatus. Chlorophyll, carotenoids and phycobilins are the prime photosynthetic pigments which facilitate efficient light absorption in plants, algae, and cyanobacteria. The chlorophyll family plays a vital role in light harvesting by absorbing light at different wavelengths and allowing photosynthetic organisms to adapt to different environments, either in the long-term or during transient changes in light. Carotenoids play diverse roles in photosynthesis, including light capture and as crucial antioxidants to reduce photodamage and photoinhibition. In the marine habitat, phycobilins capture a wide spectrum of light and have allowed cyanobacteria and red algae to colonise deep waters where other frequencies of light are attenuated by the water column. In this review, we discuss the potential strategies that photosynthetic pigments provide, coupled with development of molecular biological techniques, to improve crop yields through enhanced light harvesting, increased photoprotection and improved photosynthetic efficiency.
Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability
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.
Genome assembly of a tropical maize inbred line provides insights into structural variation and crop improvement
Maize is one of the most important crops globally, and it shows remarkable genetic diversity. Knowledge of this diversity could help in crop improvement; however, gold-standard genomes have been elucidated only for modern temperate varieties. Here, we present a high-quality reference genome (contig N50 of 15.78 megabases) of the maize small-kernel inbred line, which is derived from a tropical landrace. Using haplotype maps derived from B73, Mo17 and SK, we identified 80,614 polymorphic structural variants across 521 diverse lines. Approximately 22% of these variants could not be detected by traditional single-nucleotide-polymorphism-based approaches, and some of them could affect gene expression and trait performance. To illustrate the utility of the diverse SK line, we used it to perform map-based cloning of a major effect quantitative trait locus controlling kernel weight—a key trait selected during maize improvement. The underlying candidate gene ZmBARELY ANY MERISTEM1d provides a target for increasing crop yields. A high-quality reference genome of the maize SK inbred line and analyses between the tropical SK line and two other maize genomes, B73 and Mo17, provide insights into structural variation and crop improvement.
Benefits and Risks of Intercropping for Crop Resilience and Pest Management
To combat climate change, farmers must innovate through ecological intensification to boost food production, increase resilience to weather extremes, and shrink the carbon footprint of agriculture. Intercropping (where alternative crops or noncrop plants are integrated with cash crops) can strengthen and stabilize agroecosystems under climate change by improving resource use efficiency, enhancing soil water holding capacity, and increasing the diversity and quality of habitat for beneficial insects that provide pollination services and natural pest control. Despite these benefits, intercropping has yet to be widely adopted due to perceived risks and challenges including decreased crop yield, increased management complexity, a steep learning curve for successful management, and increased susceptibility to pests. Here, we explore the major benefits of intercropping in agricultural systems for pest control and climate resilience reported in 24 meta-analyses, while addressing risks and barriers to implementation. Most studies demonstrate clear benefits of intercropping for weed, pathogen, insect pest control, relative yield, and gross profitability. However, relatively few studies document ecosystem services conferred by intercrops alongside labor costs, which are key to economic sustainability for farmers. In addition to clearer demonstrations of the economic viability of intercropping, farmers also need strong technical and financial support during the adoption process to help them troubleshoot the site-specific complexities and challenges of managing polycultures. Ecological intensification of agriculture requires a more strategic approach than simplified production systems and is not without risks and challenges. Calibrating incentive programs to reduce financial burdens of risk for farmers could promote more widespread adoption of intercropping.
The effects of climate extremes on global agricultural yields
Climate extremes, such as droughts or heat waves, can lead to harvest failures and threaten the livelihoods of agricultural producers and the food security of communities worldwide. Improving our understanding of their impacts on crop yields is crucial to enhance the resilience of the global food system. This study analyses, to our knowledge for the first time, the impacts of climate extremes on yield anomalies of maize, soybeans, rice and spring wheat at the global scale using sub-national yield data and applying a machine-learning algorithm. We find that growing season climate factors-including mean climate as well as climate extremes-explain 20%-49% of the variance of yield anomalies (the range describes the differences between crop types), with 18%-43% of the explained variance attributable to climate extremes, depending on crop type. Temperature-related extremes show a stronger association with yield anomalies than precipitation-related factors, while irrigation partly mitigates negative effects of high temperature extremes. We developed a composite indicator to identify hotspot regions that are critical for global production and particularly susceptible to the effects of climate extremes. These regions include North America for maize, spring wheat and soy production, Asia in the case of maize and rice production as well as Europe for spring wheat production. Our study highlights the importance of considering climate extremes for agricultural predictions and adaptation planning and provides an overview of critical regions that are most susceptible to variations in growing season climate and climate extremes.