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Crop breeding in sub‐Saharan Africa has made considerable gains; however, postharvest and food‐related preferences have been overlooked, in addition to how these preferences vary by gender, social difference and context. This context is changing as participatory approaches using intersectional gender and place‐based methods are beginning to inform how breeding programmes make decisions. This article presents an innovative methodology to inclusively and democratically prioritise food quality traits of root, tuber and banana crops based on engagement with food systems actors and transdisciplinary collaboration. The outcome of the methodology is the Gendered Food Product Profile (GFPP) – a list of prioritised food quality characteristics – to support breeders to make more socially inclusive decisions on the methods for trait characterisation to select genotypes closer to the needs of food system actors. This article reviews application of the methodology in 14 GFPPs, presents illustrative case studies and lessons learned. Key lessons are that the transdisciplinary structure and the key role of social scientists helped avoid reductionism, supported co‐learning, and the creation of GFPPs that represented the diverse interests of food system actors, particularly women, in situ. The method partially addressed power dynamics in multidisciplinary decision making; however, effectiveness was dependent on equitable team relations and supportive institutions committed to valuing plural forms of knowledge. Actions to address power asymmetries that privilege particular types of knowledge and voices in decision making are crucial in techno‐science projects, along with opportunities for co‐learning and long‐term collaboration and a transdisciplinary structure at higher level. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This article discusses the importance of roots, tubers, and cooking bananas (RTBs) in the diets of tropical populations, particularly in sub-Saharan Africa. It highlights the challenges faced by growers due to limited genetic diversity, pests, diseases, and climate change. The article emphasizes the need for breeders to prioritize consumer preferences and post-harvest quality traits when developing new varieties. The RTBfoods project aims to address these challenges by identifying key traits desired by farmers, processors, and consumers through consultations and testing, while also incorporating a gender-intentional approach to ensure diverse perspectives are included. The article also discusses a special issue focused on RTBs and their breeding methods, providing information on quality traits and methods for analysis, processing, evaluation, and genetic studies. The goal is to identify promising genotypes with preferred traits for future release to farmers and stakeholders, with an emphasis on understanding user preferences to improve varietal adoption within RTB value chains. [Extracted from the article]

Background: In an environment where the adoption of improved varieties resulting from plant breeding programs is limited, it is essential to identify end‐user preferences beforehand. A participatory survey was conducted in eight localities in Korhogo and Bouaké regions (central and northern Cote d'Ivoire respectively) to identify producers' preferences and increase the adoption of improved varieties. The study involved 160 producers and consumers through focus group discussions and individual interviews. Results: Sweetpotato is mostly grown on small plots (<1 ha) of land (89.2%), with women (66%) as the main producers. In the Bouaké region, sweetpotatoes are grown on mounds (100%), whereas in Korhogo they are grown on ridges (86.2%). The main food products or forms of preparation from roots are fries (34.7%), boiled (34.3%), mashed (12.4%), and sweetpotato stew (9.1%). Major constraints, including low price of roots (26.3%), low productivity (16.2%), and post‐harvest storage issues (14.5%), were identified as affecting sweetpotato production. Conclusions: The selection of new varieties should be oriented towards high‐yielding varieties with high dry matter content, deployed stems, and roots of round, oblong, or elliptical shape with good culinary characteristics (dry matter, sweet taste, dry texture, absence of fiber). Plants must be drought resistant, be tolerant to poor soil, diseases, and pests, and have a good yield. The color of skin and flesh of the sweetpotato, although constituting criteria of choice, are not essential for the acceptance or the rejection of a variety by users. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Summary: The rhizosphere microbiome plays critical roles in plant growth and provides promising solutions for sustainable agriculture. While the rhizosphere microbiome frequently fluctuates with the soil environment, recent studies have demonstrated that a small proportion of the microbiome is consistently assembled in the rhizosphere of a specific plant genotype regardless of the soil condition, which is determined by host genetics. Based on these breakthroughs, which involved exploiting the plant‐beneficial function of the rhizosphere microbiome, we propose to divide the rhizosphere microbiome into environment‐dominated and plant genetic‐dominated components based on their different assembly mechanisms. Subsequently, two strategies to explore the different rhizosphere microbiome components for agricultural production are suggested, that is, the precise management of the environment‐dominated rhizosphere microbiome by agronomic practices, and the elucidation of the plant genetic basis of the plant genetic‐dominated rhizosphere microbiome for breeding microbiome‐assisted crop varieties. We finally present the major challenges that need to be overcome to implement strategies for modulating these two components of the rhizosphere microbiome. [ABSTRACT FROM AUTHOR]

To meet the demands of the new Green Revolution and sustainable agriculture, it is important to develop crop varieties with improved yield, nitrogen use efficiency, and stress resistance. Nitrate is the major form of inorganic nitrogen available for plant growth in many well-aerated agricultural soils, and acts as a signaling molecule regulating plant development, growth, and stress responses. Abscisic acid (ABA), an important phytohormone, plays vital roles in integrating extrinsic and intrinsic responses and mediating plant growth and development in response to biotic and abiotic stresses. Therefore, elucidating the interplay between nitrate and ABA can contribute to crop breeding and sustainable agriculture. Here, we review studies that have investigated the interplay between nitrate and ABA in root growth modulation, nitrate and ABA transport processes, seed germination regulation, and drought responses. We also focus on nitrate and ABA interplay in several reported omics analyses with some important nodes in the crosstalk between nitrate and ABA. Through these insights, we proposed some research perspectives that could help to develop crop varieties adapted to a changing environment and to improve crop yield with high nitrogen use efficiency and strong stress resistance. [ABSTRACT FROM AUTHOR]

The selection of highly productive genotypes with stable performance across environments is a major challenge of plant breeding programs due to genotype-by-environment (GE) interactions. Over the years, different metrics have been proposed that aim at characterizing the superiority and/or stability of genotype performance across environments. However, these metrics are traditionally estimated using phenotypic values only and are not well suited to an unbalanced design in which genotypes are not observed in all environments. The objective of this research was to propose and evaluate new estimators of the following GE metrics: Ecovalence, Environmental Variance, Finlay–Wilkinson regression coefficient, and Lin–Binns superiority measure. Drawing from a multi-environment genomic prediction model, we derived the best linear unbiased prediction for each GE metric. These derivations included both a squared expectation and a variance term. To assess the effectiveness of our new estimators, we conducted simulations that varied in traits and environment parameters. In our results, new estimators consistently outperformed traditional phenotype-based estimators in terms of accuracy. By incorporating a variance term into our new estimators, in addition to the squared expectation term, we were able to improve the precision of our estimates, particularly for Ecovalence in situations where heritability was low and/or sparseness was high. All methods are implemented in a new R-package: GEmetrics. These genomic-based estimators enable estimating GE metrics in unbalanced designs and predicting GE metrics for new genotypes, which should help improve the selection efficiency of high-performance and stable genotypes across environments. [ABSTRACT FROM AUTHOR]

Recently, significant advances have been achieved in gene editing of plant protein kinases and phosphatases using clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) technology. Progress in computer science and programming could significantly improve CRISPR/Cas9 gene-editing predictions and subsequent wet-laboratory experiments on protein kinases and phosphatases. Gene-edited protein kinases and phosphatases could considerably improve desirable crop traits and stress tolerance. Protein phosphorylation, the most common and essential post-translational modification, belongs to crucial regulatory mechanisms in plants, affecting their metabolism, intracellular transport, cytoarchitecture, cell division, growth, development, and interactions with the environment. Protein kinases and phosphatases, two important families of enzymes optimally regulating phosphorylation, have now become important targets for gene editing in crops. We review progress on gene-edited protein kinases and phosphatases in crops using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9). We also provide guidance for computational prediction of alterations and/or changes in function, activity, and binding of protein kinases and phosphatases as consequences of CRISPR/Cas9-based gene editing with its possible application in modern crop molecular breeding towards sustainable agriculture. [ABSTRACT FROM AUTHOR]

It should be the ultimate goal of any theory of evolution to delineate the contours of an integrative system to answer the question: How does life (in all its complexity) evolve (which can be called mega‐evolution)? But how to plausibly define 'life'? My answer (1994–2023) is: 'life' sounds like a noun, but denotes an activity, and thus is a verb. Life (L) denotes nothing else than the total sum (∑) of all acts of communication (transfer of information) (C) executed by any type of senders–receivers at all their levels (up to at least 15) of compartmental organization: L = ∑C. The 'communicating compartment' is better suited to serve as the universal unit of structure, function and evolution than the cell, the smallest such unit. By paying as much importance to communication activity as to the Central Dogma of molecular biology, a wealth of new insights unfold. The major ones are as follows. (1) Living compartments have not only a genetic memory (DNA), but also a still enigmatic cognitive and an electrical memory system (and thus a triple memory system). (2) Complex compartments can have up to three types of progeny: genetic descendants/children, pupils/learners and electricians. (3) Of particular importance to adaptation, any act of communication is a problem‐solving act because all messages need to be decoded. Hence through problem‐solving that precedes selection, life itself is the driving force of its own evolution (a very clever but counterintuitive and unexpected logical deduction). Perhaps, this is the 'vital force' philosopher and Nobel laureate (in 1927) Henri Bergson searched for but did not find. [ABSTRACT FROM AUTHOR]

The post‐emergent herbicide options to control grasses in sorghum have historically been limited. Therefore, a mass selection program was implemented to increase the tolerance of sorghum to the broad‐spectrum herbicide tembotrione. The objectives of this study are to determine (i) which observation timing and vegetative indices are most effective in assessing sorghum injury to tembotrione using unoccupied aerial system imagery and (ii) if mass selection can be used to increase the tolerance of sorghum to tembotrione. Using an unoccupied aerial system, several vegetative indices, collected at either 14 or 21 days after tembotrione application, accurately measured sorghum injury. Over four cycles of selection, tembotrione tolerance increased in a linear and consistent manner. This demonstrates that mass selection can be used as a strategy for developing herbicide tolerance in crops. The modest, but steady genetic gain indicates both the quantitative nature of the trait and sufficient heritability to improve it. Given further development, tembotrione‐resistant sorghum hybrids could provide an effective means of post‐emergent weed control for a range of common weeds. [ABSTRACT FROM AUTHOR]

• Organic farming grapples with drought, demanding efficient crop selection. • Molecular techniques revolutionize selection, expediting drought-resistant crop identification. • This review delves into molecular tech's role in streamlining drought-resistant crop selection in organic agriculture. • This exploration guides towards drought-resistant crop varieties, promoting sustainability amidst climate unpredictability. Drought, an ever-looming threat to agriculture, is of paramount concern in organic crop production. The traditional methodologies employed for screening and selecting drought-resistant crops are characterized by their laborious and time-intensive nature. However, the integration of molecular techniques has wrought a revolutionary transformation, expediting the identification and precise selection of crop varieties resilient to drought stress. This review explores the intricate relationship between molecular technologies and the imperative to streamline the screening and selection process for drought-resistant crops in organic agriculture. The advantages of these molecular methodologies are delved into, revealing the potential to accelerate the breeding of crops capable of withstanding the challenges posed by water scarcity. However, this exploration is full of challenges. From scalability issues to cost-effectiveness, ethical implications, and environmental impact, a comprehensive examination is crucial for a nuanced understanding of integrating these technologies into the organic crop production landscape. Moreover, this review extends beyond the present, casting a discerning eye toward the prospects of molecular techniques in pursuing sustainable agriculture. The potential for refinement, overcoming challenges, and synergies with other emerging technologies is crucially considered as a resilient and environmentally conscious agricultural future is envisioned. In essence, this exploration serves as a comprehensive guide, shedding light on the transformative power of molecular techniques in navigating the intricate path towards drought-resistant crop varieties, thereby fostering sustainable practices in the face of an increasingly unpredictable climate. [ABSTRACT FROM AUTHOR]

• Increase of nitrogen use efficiency (NUE) through management and genetic manipulation is an urgent need. • The review highlights the current trend of using genetic insights from plant systems biology to promote cereal crop breeding strategies that reduce reliance on fertilizer without sacrificing yield. • This review explores the role of nitrogen in plants, its assimilation and transport, and new approaches to genetically improving cereal crops. Nowadays, researchers are focused on sustainable crop growth as the world population is rising at an alarming rate. Therefore, global food safety and security are major concerns. Cereals play a significant role in mitigating hunger at a global level. The main factor responsible for the rise in cereal production has been the increased use of inorganic nitrogen. Due to rising nitrogen application, inefficient use, and the negative effects of excess nitrogen on the environment, soil and human health, therefore there is an immediate need to increase nitrogen use efficiency (NUE) through management and genetic manipulation. The limitation of nitrogen management due to nitrogen runoff, denitrification, and other nitrogen losses that cause ecological hazards has shifted attention to increasing NUE. This review explores the role of nitrogen in plants, its assimilation and transport, and new approaches to genetically improving of cereal crops with high nitrogen use efficiency. The article focused on the need for genetic manipulation and management strategies to fully realise NUE's potential in cereal crops i.e., rice, wheat etc. It also highlights the current trend of using genetic insights from plant systems biology to promote cereal crop breeding strategies that reduce reliance on fertiliser without sacrificing yield. The urgent challenge of optimising NUE while ensuring food security and environmental well-being can be met through the synergistic application of management practices, genetic breakthroughs, and breeding innovations that have the potential to reshape the future of agricultural sustainability. [ABSTRACT FROM AUTHOR]

Summary: Rice blast, caused by Magnaporthe oryzae, significantly impacts grain yield, necessitating the identification of broad‐spectrum resistance genes and their functional mechanisms for disease‐resistant crop breeding. Here, we report that rice with knockdown OsHDAC1 gene expression displays enhanced broad‐spectrum blast resistance without effects on plant height and tiller numbers compared to wild‐type rice, while rice overexpressing OsHDAC1 is more susceptible to M. oryzae. We identify a novel blast resistance transcription factor, OsGRAS30, which genetically acts upstream of OsHDAC1 and interacts with OsHDAC1 to suppress its enzymatic activity. This inhibition increases the histone H3K27ac level, thereby boosting broad‐spectrum blast resistance. Integrating genome‐wide mapping of OsHDAC1 and H3K27ac targets with RNA sequencing analysis unveils how OsHDAC1 mediates the expression of OsSSI2, OsF3H, OsRLR1 and OsRGA5 to regulate blast resistance. Our findings reveal that the OsGRAS30–OsHDAC1 module is critical to rice blast control. Therefore, targeting either OsHDAC1 or OsGRAS30 offers a promising approach for enhancing crop blast resistance. [ABSTRACT FROM AUTHOR]

Summary: Rhizomes are modified stems that grow underground and produce new individuals genetically identical to the mother plant. Recently, a breakthrough has been made in efforts to convert annual grains into perennial ones by utilizing wild rhizomatous species as donors, yet the developmental biology of this organ is rarely studied. Oryza longistaminata, a wild rice species featuring strong rhizomes, provides a valuable model for exploration of rhizome development. Here, we first assembled a double‐haplotype genome of O. longistaminata, which displays a 48‐fold improvement in contiguity compared to the previously published assembly. Furthermore, spatiotemporal transcriptomics was performed to obtain the expression profiles of different tissues in O. longistaminata rhizomes and tillers. Two spatially reciprocal cell clusters, the vascular bundle 2 cluster and the parenchyma 2 cluster, were determined to be the primary distinctions between the rhizomes and tillers. We also captured meristem initiation cells in the sunken area of parenchyma located at the base of internodes, which is the starting point for rhizome initiation. Trajectory analysis further indicated that the rhizome is regenerated through de novo generation. Collectively, these analyses revealed a spatiotemporal transcriptional transition underlying the rhizome initiation, providing a valuable resource for future perennial crop breeding. [ABSTRACT FROM AUTHOR]

Summary: Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground‐breaking work, especially his effort to list orphan tropical crops to genomic resource‐rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape. [ABSTRACT FROM AUTHOR]

This document is a summary of a collection of articles that explore the impacts of various agronomic practices on crop yields and ecosystem functioning in dryland agroecosystems. The articles cover topics such as the effects of plastic mulch, straw returning, biochar amendments, intercropping, biomass allocation patterns, conservation tillage, and soil drying-rewetting cycles. The findings suggest that these practices can enhance soil fertility, increase crop productivity, improve soil moisture and temperature conditions, reduce soil degradation, and mitigate environmental pollution. However, the effects of these practices can vary depending on factors such as geographical location, crop type, and environmental conditions. Further research is needed to expand our understanding of these practices in different contexts. [Extracted from the article]

Background: Extreme weather events induced by climate change, particularly droughts, have detrimental consequences for crop yields and food security. Concurrently, these conditions provoke substantial changes in the soil bacterial microbiota and affect plant health. Early recognition of soil affected by drought enables farmers to implement appropriate agricultural management practices. In this context, interpretable machine learning holds immense potential for drought stress classification of soil based on marker taxa. Results: This study demonstrates that the 16S rRNA-based metagenomic approach of Differential Abundance Analysis methods and machine learning-based Shapley Additive Explanation values provide similar information. They exhibit their potential as complementary approaches for identifying marker taxa and investigating their enrichment or depletion under drought stress in grass lineages. Additionally, the Random Forest Classifier trained on a diverse range of relative abundance data from the soil bacterial micobiome of various plant species achieves a high accuracy of 92.3 % at the genus rank for drought stress prediction. It demonstrates its generalization capacity for the lineages tested. Conclusions: In the detection of drought stress in soil bacterial microbiota, this study emphasizes the potential of an optimized and generalized location-based ML classifier. By identifying marker taxa, this approach holds promising implications for microbe-assisted plant breeding programs and contributes to the development of sustainable agriculture practices. These findings are crucial for preserving global food security in the face of climate change. [ABSTRACT FROM AUTHOR]

Background: There is a lack of knowledge on the combined effects of different stresses on plants, in particular different stresses that occur during winter in temperate climates. Perennial herbaceous plants in temperate regions are exposed to many different stresses during winter, but except for the fact that cold temperatures induce resistance to a number of them, very little is known about their interaction effects. Knowledge about stress interactions is needed in order to predict effects of climate change on both agricultural production and natural ecosystems, and to develop adaptation strategies, e.g., through plant breeding. Here, we conducted a series of experiments under controlled conditions to study the interactions between cold (low positive temperature), clover rot infection (caused by Sclerotinia trifoliorum) and freezing, in red clover (Trifolium pratense) accessions. We also compared our results with winter survival in field experiments and studied associations between stress and shoot growth. Results: Exposure to low positive temperatures (cold acclimation) induced resistance to clover rot. There was a clear negative interaction effect between freezing stress and clover rot infection, resulting in up to 37% lower survival rate compared to what would have been expected from the additive effect of freezing and infection alone. Freezing tolerance could continue to improve during incubation under artificial snow cover at 3 °C in spite of darkness, and we observed compensatory shoot growth following freezing after prolonged incubation. At the accession level, resistance to clover rot was negatively correlated with growth in the field during the previous year at a Norwegian location. It was also negatively correlated with the shoot regrowth of control plants after incubation. Clover rot resistance tests under controlled conditions showed limited correlation with clover rot resistance observed in the field, suggesting that they may reveal variation in more specific resistance mechanisms. Conclusions: We here demonstrate, for the first time, a strong negative interaction between freezing and infection with a winter pathogen. We also characterize the effects of cold acclimation and incubation in darkness at different temperatures on winter stress tolerance, and present data that support the notion that annual cycles of growth and stress resistance are associated at the genetic level. [ABSTRACT FROM AUTHOR]

Biofortification increases micronutrient content in staple crops through conventional breeding, agronomic methods, or genetic engineering. Bioaccessibility is a prerequisite for a nutrient to fulfill a biological function, e.g., to be bioavailable. The objective of this systematic review is to examine the bioavailability (and bioaccessibility as a proxy via in vitro and animal models) of the target micronutrients enriched in conventionally biofortified crops that have undergone post-harvest storage and/or processing, which has not been systematically reviewed previously, to our knowledge. We searched for articles indexed in MEDLINE, Agricola, AgEcon, and Center for Agriculture and Biosciences International databases, organizational websites, and hand-searched studies' reference lists to identify 18 studies reporting on bioaccessibility and 58 studies on bioavailability. Conventionally bred biofortified crops overall had higher bioaccessibility and bioavailability than their conventional counterparts, which generally provide more absorbed micronutrient on a fixed ration basis. However, these estimates depended on exact cultivar, processing method, context (crop measured alone or as part of a composite meal), and experimental method used. Measuring bioaccessibility and bioavailability of target micronutrients in biofortified and conventional foods is critical to optimize nutrient availability and absorption, ultimately to improve programs targeting micronutrient deficiency. [ABSTRACT FROM AUTHOR]

Background: Isolated microspore culture is a useful biotechnological technique applied in modern plant breeding programs as it can produce doubled haploid (DH) plants and accelerate the development of new varieties. Furthermore, as a single-cell culture technique, the isolated microspore culture provides an excellent platform for studying microspore embryogenesis. However, the reports on isolated microspore culture are rather limited in rice due to the low callus induction rate, poor regeneration capability, and high genotypic dependency. The present study developed an effective isolated microspore culture protocol for high-frequency androgenesis in four japonica rice genotypes. Several factors affecting the isolated microspore culture were studied to evaluate their effects on callus induction and plantlet regeneration. Results: Low-temperature pre-treatment at 4 ℃ for 10–15 days could effectively promote microspore embryogenesis in japonica rice. A simple and efficient method was proposed for identifying the microspore developmental stage. The anthers in yellow-green florets located on the second type of primary branch on the rice panicle were found to be the optimal stage for isolated microspore culture. The most effective induction media for callus induction were IM2 and IM3, depending on the genotype. The optimal concentration of 2, 4-D in the medium for callus induction was 1 mg/L. Callus induction was negatively affected by a high concentration of KT over 1.5 mg/L. The differentiation medium suitable for japonica rice microspore callus comprised 1/2 MS, 2 mg/L 6-BA, 0.5 mg/L NAA, 30 g/L sucrose, and 6 g/L agar. The regeneration frequency of the four genotypes ranged from 61–211 green plantlets per 100 mg calli, with Chongxiangjing showing the highest regeneration frequency. Conclusions: This study presented an efficient protocol for improved callus induction and green plantlet regeneration in japonica rice via isolated microspore culture, which could provide valuable support for rice breeding and genetic research. [ABSTRACT FROM AUTHOR]

Background: Yield and quality are the two most important traits in crop breeding. Exploring the regulatory mechanisms that affect both yield and quality traits is of great significance for understanding the molecular genetic networks controlling these key crop attributes. Expansins are cell wall loosening proteins that play important roles in regulating rice grain size. Results: We investigated the effect of OsEXPA7, encoding an expansin, on rice grain size and quality. OsEXPA7 overexpression resulted in increased plant height, panicle length, grain length, and thousand-grain weight in rice. OsEXPA7 overexpression also affected gel consistency and amylose content in rice grains, thus affecting rice quality. Subcellular localization and tissue expression analyses showed that OsEXPA7 is localized on the cell wall and is highly expressed in the panicle. Hormone treatment experiments revealed that OsEXPA7 expression mainly responds to methyl jasmonate, brassinolide, and gibberellin. Transcriptome analysis and RT-qPCR experiments showed that overexpression of OsEXPA7 affects the expression of OsJAZs in the jasmonic acid pathway and BZR1 and GE in the brassinosteroid pathway. In addition, OsEXPA7 regulates the expression of key quantitative trait loci related to yield traits, as well as regulates the expression levels of BIP1 and bZIP50 involved in the seed storage protein biosynthesis pathway. Conclusions: These results reveal that OsEXPA7 positively regulates rice yield traits and negatively regulates grain quality traits by involving plant hormone pathways and other trait-related pathway genes. These findings increase our understanding of the potential mechanism of expansins in regulating rice yield and quality traits and will be useful for breeding high-yielding and high-quality rice cultivars. [ABSTRACT FROM AUTHOR]

Background: X-ray computed tomography (CT) is a powerful tool for measuring plant root growth in soil. However, a rapid scan with larger pots, which is required for throughput-prioritized crop breeding, results in high noise levels, low resolution, and blurred root segments in the CT volumes. Moreover, while plant root segmentation is essential for root quantification, detailed conditional studies on segmenting noisy root segments are scarce. The present study aimed to investigate the effects of scanning time and deep learning-based restoration of image quality on semantic segmentation of blurry rice (Oryza sativa) root segments in CT volumes. Results: VoxResNet, a convolutional neural network-based voxel-wise residual network, was used as the segmentation model. The training efficiency of the model was compared using CT volumes obtained at scan times of 33, 66, 150, 300, and 600 s. The learning efficiencies of the samples were similar, except for scan times of 33 and 66 s. In addition, The noise levels of predicted volumes differd among scanning conditions, indicating that the noise level of a scan time ≥ 150 s does not affect the model training efficiency. Conventional filtering methods, such as median filtering and edge detection, increased the training efficiency by approximately 10% under any conditions. However, the training efficiency of 33 and 66 s-scanned samples remained relatively low. We concluded that scan time must be at least 150 s to not affect segmentation. Finally, we constructed a semantic segmentation model for 150 s-scanned CT volumes, for which the Dice loss reached 0.093. This model could not predict the lateral roots, which were not included in the training data. This limitation will be addressed by preparing appropriate training data. Conclusions: A semantic segmentation model can be constructed even with rapidly scanned CT volumes with high noise levels. Given that scanning times ≥ 150 s did not affect the segmentation results, this technique holds promise for rapid and low-dose scanning. This study offers insights into images other than CT volumes with high noise levels that are challenging to determine when annotating. [ABSTRACT FROM AUTHOR]

Participatory plant breeding (PPB) is a collaborative process between farmers, plant breeders and researchers to create germplasm specifically bred for target environments. We sought to examine the yield performance and adaptability of genotypes from an organic PPB wheat programme under organic management across the Canadian prairies. We evaluated 25 farmer genotypes and 6 commercial cultivars in locations in Alberta, Saskatchewan and Manitoba, totalling 12 organic environments. The top performers most responsive to higher yield environments were three farmer genotypes (BL34‐SW, BL43C‐TM and BJ13‐GW) and one check cultivar (Vesper). Genotype plus genotype by environment (GGE) biplot analysis indicated that one farmer genotype (BL23‐AS) and one check cultivar (Vesper) demonstrated high yield and greater organic adaptation than other genotypes tested. Two registered cultivars (AAC Brandon and Jake) had low yield and poor adaptation, as did one farmer genotype (PWA10B‐LD). Yield was positively and strongly correlated with height, anthesis and mature biomass and kernel number per unit area. The results provide evidence that early generation farmer selection is an effective breeding strategy for discovering wheat genotypes with high yield and excellent adaptability to organic production systems in Canada. [ABSTRACT FROM AUTHOR]

Trade‐offs between traits arise and reflect constraints imposed by the environment and physicochemical laws. Trade‐off situations are expected to be highly relevant for sessile plants, which have to respond to changes in the environment to ensure survival. Despite increasing interest in determining the genetic and molecular basis of plant trade‐offs, there are still gaps and differences with respect to how trade‐offs are defined, how they are measured, and how their genetic architecture is dissected. The first step to fill these gaps is to establish what is meant by trade‐offs. In this review we provide a classification of the existing definitions of trade‐offs according to: (1) the measures used for their quantification, (2) the dependence of trade‐offs on environment, and (3) experimental designed used (i.e. a single individual across different environments or a population of individuals in single or multiple environments). We then compare the approaches for quantification of trade‐offs based on phenotypic, between‐individual, and genetic correlations, and stress the need for developing further quantification indices particularly for trade‐offs between multiple traits. Lastly, we highlight the genetic mechanisms underpinning trade‐offs and experimental designs that facilitate their discovery in plants, with focus on usage of natural variability. This review also offers a perspective for future research aimed at identification of plant trade‐offs, dissection of their genetic architecture, and development of strategies to overcome trade‐offs, with applications in crop breeding. [ABSTRACT FROM AUTHOR]

As a physical mutagen, carbon ion beam (CIB) irradiation can induce high-frequency mutation, which is user-friendly and environment-friendly in plant breeding. In this study, we resequenced eight mutant lines which were screened out from the progeny of the CIB-irradiated dehulled rice seeds. Among these mutants, CIB induced 135,535 variations, which include single base substitutions (SBSs), and small insertion and deletion (InDels). SBSs are the most abundant mutation, and account for 88% of all variations. Single base conversion is the main type of SBS, and the average ratio of transition and transversion is 1.29, and more than half of the InDels are short-segmented mutation (1–2 bp). A total of 69.2% of the SBSs and InDels induced by CIBs occurred in intergenic regions on the genome. Surprisingly, the average mutation frequency in our study is 9.8 × 10−5/bp and much higher than that of the previous studies, which may result from the relatively high irradiation dosage and the dehulling of seeds for irradiation. By analyzing the mutation of every 1 Mb in the genome of each mutant strain, we found some unusual high-frequency (HF) mutation regions, where SBSs and InDels colocalized. This study revealed the mutation mechanism of dehulled rice seeds by CIB irradiation on the genome level, which will enrich our understanding of the mutation mechanism of CIB radiation and improve mutagenesis efficiency. [ABSTRACT FROM AUTHOR]

Coleus scutellarioides (L.) Benth. is a globally spread species, known for its characteristic spectacularly colorful leaves of decorative value. Thanks to its rich chemical composition, the plant is used in ethnopharmacology, and it is also regarded as having high medicinal potential. The application of in vitro cultures enables the acquisition of homogeneous certified material of high quality. Additionally, excluding the effect of biotic and abiotic factors on the plants is a way to fully recognize the influence of phytohormones on the plant morphology and the biosynthetic pathways of compound production. The best way to grow C. scutellarioides "Electric Lime" under in vitro conditions is to use the basic MS medium (Murashige and Skoog medium), enriched with naphthyl-1-acetic acid at a concentration of 0.5 mg dm−3. The analysis of volatile compounds demonstrated that the content of volatile compounds in the plants cultivated under in vivo conditions was expressed at a level of 2848.59 µg g−1, whereas in the plants bred in vitro without supplementation with phytohormones, the level was 8191.47 µg g−1. The highest content was noted for copaene, α-pinene, 1-octene-3-ol, α-selinene, sabinen, γ- and δ-cadinene, 3-octanol, and β-pinene. Aroma profiling revealed a lack of boranyl acetate, 2-hexenal, and 2-hexen-1-ol in the plants cultivated under in vivo conditions. Differences were found in the volatile composition between plants bred in vivo and in vitro, with the most significant recorded for the contents of 1-octen-3-ol and 3-octanol. The addition of plant growth regulators into the basic medium under in vitro conditions affected the percentage ratio and contents of specific compounds in plant tissues. The most intense biosynthesis of volatile compounds took place in the plants cultivated on the medium enriched with NAA at 10,579.11 µg g−1, whereas the least intense was noted for plants cultivated on the medium supplemented with BA, where it was recorded at the level of 5610.02 µg g−1. So far, there has been no research published which would pertain to the profiling of volatile compounds performed using the SPME (solid-phase microextraction) technique. Moreover, the very few studies conducted on the chemical composition of these compounds do not mention the specific variety of C. scutellarioides under analysis. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) has become an increasingly popular tool in plant breeding programs, propelled by declining genotyping costs, an increase in computational power, and rediscovery of the best linear unbiased prediction methodology over the past two decades. This development has led to an accumulation of extensive historical datasets with genotypic and phenotypic information, triggering the question of how to best utilize these datasets. Here, we investigate whether all available data or a subset should be used to calibrate GS models for across-year predictions in a 7-year dataset of a commercial hybrid sunflower breeding program. We employed a multi-objective optimization approach to determine the ideal years to include in the training set (TRS). Next, for a given combination of TRS years, we further optimized the TRS size and its genetic composition. We developed the Min_GRM size optimization method which consistently found the optimal TRS size, reducing dimensionality by 20% with an approximately 1% loss in predictive ability. Additionally, the Tails_GEGVs algorithm displayed potential, outperforming the use of all data by using just 60% of it for grain yield, a high-complexity, low-heritability trait. Moreover, maximizing the genetic diversity of the TRS resulted in a consistent predictive ability across the entire range of genotypic values in the test set. Interestingly, the Tails_GEGVs algorithm, due to its ability to leverage heterogeneity, enhanced predictive performance for key hybrids with extreme genotypic values. Our study provides new insights into the optimal utilization of historical data in plant breeding programs, resulting in improved GS model predictive ability. [ABSTRACT FROM AUTHOR]

Background: The formation of shoots plays a pivotal role in plant organogenesis and productivity. Despite its significance, the underlying molecular mechanism of de novo regeneration has not been extensively elucidated in Capsicum annuum 'Dempsey', a bell pepper cultivar. To address this, we performed a comparative transcriptome analysis focusing on the differential expression in C. annuum 'Dempsey' shoot, callus, and leaf tissue. We further investigated phytohormone-related biological processes and their interacting genes in the C. annuum 'Dempsey' transcriptome based on comparative transcriptomic analysis across five species. Results: We provided a comprehensive view of the gene networks regulating shoot formation on the callus, revealing a strong involvement of hypoxia responses and oxidative stress. Our comparative transcriptome analysis revealed a significant conservation in the increase of gene expression patterns related to auxin and defense mechanisms in both callus and shoot tissues. Consequently, hypoxia response and defense mechanism emerged as critical regulators in callus and shoot formation in C. annuum 'Dempsey'. Current transcriptome data also indicated a substantial decline in gene expression linked to photosynthesis within regenerative tissues, implying a deactivation of the regulatory system governing photosynthesis in C. annuum 'Dempsey'. Conclusion: Coupled with defense mechanisms, we thus considered spatial redistribution of auxin to play a critical role in the shoot morphogenesis via primordia outgrowth. Our findings shed light on shoot formation mechanisms in C. annuum 'Dempsey' explants, important information for regeneration programs, and have broader implications for precise molecular breeding in recalcitrant crops. [ABSTRACT FROM AUTHOR]

The limited engagement of farmers and their community agents in the process of variety development and evaluation is one of the main factors for lower rates of variety adoption, which resulted in lower crop productivity. Participatory bread wheat variety evaluation was jointly conducted by breeders, members of seed producer cooperative (SPC) and local experts with the objectives to identify farmers' selection criteria, to assess farmers' preferred varieties and to increase the SPC's variety portfolios. Twelve released bread wheat varieties were evaluated during 2019 cropping season at Sekela district of Amhara region, Ethiopia. Pair-wise ranking was used to identify farmers' selection criteria and direct matrix ranking to prioritize those selected criteria. Varieties were planted in two sets with and without lime application. Grain yield, followed by earliness, disease tolerance, and tillering capacity, was identified the first preferred criterion by farmers. The mean values showed that higher yield was recorded with the lime application compared to no lime application. Lemu (6.4 t/ha), Alidoro (6.3 t/ha), Dambal (6.3 t/ha), Obora (6.1 t/ha) and Liben (6.1 t/ha) had greater yield with lime application. The t-test results indicated that significant difference between with and without liming for the number of tillers per plant, spike length per plant, plant height, 1000 seed weight, and hectoliter weight, but non-significant difference for grain yield. The selected varieties should be included in the production plan of the cooperatives for large scale production to increase the variety portfolios and to address the demand of the farming community. [ABSTRACT FROM AUTHOR]

This study utilized the machine learning algorithm called "Bagging" to gain a better understanding of the relationships between climate variability, crop yields, and the agricultural contributions to the gross domestic product (agrigdp) in the Nile basin. The multiple stepwise regression model (MSRM) was also used as a comparison. The time series data collected from 1961 to 2016 for four main crops (groundnuts, sorghum, wheat, and sugarcane), rainfall, air temperature (minimum, mean, and maximum), and agrigdp were divided into 70% for training and 30% for testing using R packages. The results indicated that the Bagging algorithm improved crop yield predictions by 18%—63% compared to the MSRM. All crops demonstrated a greater sensitivity to climate variability, resulting in a low probability of achieving the highest attainable crop yield: 18% – 33% for groundnut, 18%—38% for sorghum, 21%—41% for wheat, and 22%—56% for sugarcane. The climate variability also led to a basin-wide loss of 35 million US$ in the agrigdp, with a basin-wide probability of 29%—61% for attaining the highest agrigdp. The algorithm clearly identified the ideal climatic conditions for reaching the highest attainable crop yields and agrigdp in the Nile Basin. The central factor was found to be air temperature, particularly the mean temperature, with anomalies of ± 0.5 °C responsible for 17%—69% of crop yield losses. Strategies for adapting to and managing risks associated with climate variability should focus on on-farm air temperature management practices, technologies such as greenhouses, and plant breeding. [ABSTRACT FROM AUTHOR]

Selecting wheat hybrids is vital for enhancing crop yield, adapting to changing climates, and ensuring food security. These hybrids align with market demands and sustainable farming practices, contributing to efficient crop management. Traditional methods for wheat hybrid selection, such as molecular techniques, are costly and time-consuming, and are prone to human error. However, advancements in artificial intelligence and machine learning offer non-destructive, objective, and more efficient solutions. This study is explored the classification of wheat varieties and hybrids using two deep learning models, MobileNetv2 and GoogleNet. These models are achieved impressive classification accuracy, with MobileNetv2 reaching 99.26% and GoogleNet achieving 97.41%. In the second scenario, the deep features obtained from these models are classified with Support Vector Machine (SVM). In the classification made with the MobileNetv2-SVM hybrid model, an accuracy of 99.91% is achieved. This study is provided rapid and accurate wheat variety and hybrid identification method, as well as contributing to breeding programs and crop management. [ABSTRACT FROM AUTHOR]

Host–plant resistance (HPR) is a subdiscipline in entomology that aims to understand, develop, and deploy crop varieties resistant to arthropod herbivores. The seminal figure in HPR was Reginald Painter, whose 1951 monograph Insect Resistance in Crop Plants established a conceptual framework and methodological approach for applied research on plant resistance. In the 75 years since the publication of this book, the empirical and multidisciplinary approach established by Painter has led to the development and use of hundreds of arthropod-resistant crop varieties. Much of the success of HPR research has been, and will continue to be, tied to advances in scientific disciplines related to HPR, such as plant breeding and genetics, analytical chemistry, and plant–insect interactions. However, given the challenges facing agriculture and pest management over the coming decades, increased attention will need to be given to the deployment of resistant varieties and the integration of resistant varieties into integrated pest management (IPM) programs. Recent advances in our understanding of fundamental aspects of the interactions between plants and herbivores provide insights that can facilitate the increased use of plant resistance in IPM programs, and the diverse membership of the Entomological Society of America can play a critical role by increasing communication between scientists interested in applied and fundamental aspects of plant resistance to insects. [ABSTRACT FROM AUTHOR]

Genome-editing tools such as the clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas9) system have become essential tools for increasing the efficiency and accuracy of plant breeding. Using such genome-editing tools on maize, one of the most important cereal crops of the world, will greatly benefit the agriculture and the mankind. Conventional genome-editing methods typically used for maize involve insertion of a Cas9-guide RNA expression cassette and a selectable marker in the genome DNA; however, using such methods, it is essential to eliminate the inserted DNA cassettes to avoid legislative concerns on gene-modified organisms. Another major hurdle for establishing an efficient and broadly applicable DNA-free genome-editing system for maize is presented by recalcitrant genotypes/cultivars, since cell/tissue culture and its subsequent regeneration into plantlets are crucial for producing transgenic and/or genome-edited maize. In this study, to establish a DNA-free genome-editing system for recalcitrant maize genotypes/cultivars, Cas9-gRNA ribonucleoproteins were directly delivered into zygotes isolated from the pollinated flowers of the maize-B73 cultivar. The zygotes successfully developed and were regenerated into genome-edited plantlets by co-culture with phytosulfokine, a peptide phytohormone. The method developed herein made it possible to obtain DNA- and selectable-marker-free genome-edited recalcitrant maize genotypes/cultivars with high efficiency. This method can advance the molecular breeding of maize and other important cereals, regardless of their recalcitrant characteristics. [ABSTRACT FROM AUTHOR]

Ash dieback is a disease caused by the fungal pathogen Hymenoscyphus fraxineus. Since its emergence in the 1990s, this pandemic disease has spread throughout much of the native range of its host species, the European ash (Fraxinus excelsior). Where present, it can kill up to 85% of ash trees. The loss of these trees has had an enormous impact, particularly in Britain and Ireland where they formed an integral component of wood and farmland, supporting complex communities of other species. Thanks in part to widespread public interest, the ash dieback pandemic has also had a large political impact, leading to changes in the management of plant diseases. Now, three decades after the emergence of the disease, ambitious projects to breed tolerant plants, and evidence of natural selection for resistance, give hope for the recovery of European ash. The aim of this review is to provide an overview of the history of the ash dieback pandemic, from its emergence to current efforts to mitigate its effects. We discuss the emergence of ash dieback and the wide body of research that has led to our current understanding of the disease. We question which aspects of the disease have led to it holding a particular interest to the public. With a focus on the islands of Britain and Ireland, we discuss how this has driven changes in the management of plant diseases, which may give hope for the control of emerging pathogens in the future. [ABSTRACT FROM AUTHOR]

Mutagenesis has been one of the effective methods for creating genetic diversity and plant mutants can be significant bio-resources for crop breeding and functional genomics studies. The genetic and phenotypic diversity of 95 selected mutants from 17 mutant populations, obtained from an EMS mutagenized rice Hashemi variety, were phenotypically and molecularly assessed in M3 generation. Phenotypic variation of these mutants showed that grain yield components varied among the selected mutants compared to the control plants. In parallel, genetic diversity assessed by 13 Inter-Simple Sequence Repeats (ISSR) primers showed that the number of amplified fragments per primer varied from 4 (pr1-7) to 11 (ISSR-7, ISSR-11). In general, 13 primers amplified 99 fragments, 50 of which were polymorphic (52.92%). The genetic variation created by ISSR markers within 17 populations varied from 11.11% in HM9 (Hashemi Mutant Line number 9) to 45.45% in HM2. The average molecular polymorphism value was 0.27. In the total genetic variance, 95% of differences were attributed to within-population diversity, and 5% were related to among-populations. The Unweighted Pair-Group Method with Arithmetic mean (UPGMA) trees illustrating ISSR diversity classified the rice mutant population into seven groups, which were further supported by model-based STRUCTURE analysis. In general, the studied mutant genotypes revealed desirable genetic characteristics in populations 13 and 17, with em3h204 and em3h280 genotypes being the most divergent. [ABSTRACT FROM AUTHOR]

Summary: Plants have evolved a multi‐layered immune system to fight off pathogens. However, immune activation is costly and is often associated with growth and development penalty. In crops, yield is the main breeding target and is usually affected by high disease resistance. Therefore, proper balance between growth and defence is critical for achieving efficient crop improvement. This review highlights recent advances in attempts designed to alleviate the trade‐offs between growth and disease resistance in crops mediated by resistance (R) genes, susceptibility (S) genes and pleiotropic genes. We also provide an update on strategies for optimizing the growth–defence trade‐offs to breed future crops with desirable disease resistance and high yield. [ABSTRACT FROM AUTHOR]

Summary: Base editors enable precise nucleotide changes at targeted genomic loci without requiring double‐stranded DNA breaks or repair templates. TALE‐adenine base editors (TALE‐ABEs) are genome editing tools, composed of a DNA‐binding domain from transcription activator‐like effectors (TALEs), an engineered adenosine deaminase (TadA8e), and a cytosine deaminase domain (DddA), that allow A•T‐to‐G•C editing in human mitochondrial DNA. However, the editing ability of TALE‐ABEs in plants apart from chloroplast DNA has not been described, so far, and the functional role how DddA enhances TadA8e is still unclear. We tested a series of TALE‐ABEs with different deaminase fusion architectures in Nicotiana benthamiana and rice. The results indicate that the double‐stranded DNA‐specific cytosine deaminase DddA can boost the activities of single‐stranded DNA‐specific deaminases (TadA8e or APOBEC3A) on double‐stranded DNA. We analysed A•T‐to‐G•C editing efficiencies in a β‐glucuronidase reporter system and showed precise adenine editing in genomic regions with high product purity in rice protoplasts. Furthermore, we have successfully regenerated rice plants with A•T‐to‐G•C mutations in the chloroplast genome using TALE‐ABE. Consequently, TALE‐adenine base editors provide alternatives for crop improvement and gene therapy by editing nuclear or organellar genomes. [ABSTRACT FROM AUTHOR]

SUMMARY: F1 hybrids derived from a cross between two inbred parental lines often display widespread changes in DNA methylation patterns relative to their parents. To which extent these changes drive non‐additive gene expression levels and phenotypic heterosis in F1 individuals is not fully resolved. Current mechanistic models propose that DNA methylation remodeling in hybrids is the result of epigenetic interactions between parental alleles via small interfering RNA (sRNA). These models have strong empirical support but are limited to genomic regions where the two parental lines differ in DNA methylation status. However, most remodeling events occur in parental regions with similar methylation patterns, and seem to be strongly conditioned by distally acting factors, even in isogenic hybrid systems. The molecular basis of these distal interactions is currently unknown, and will likely emerge as an active area of research in the future. Despite these gaps in our molecular understanding, parental DNA methylation states are statistically associated with heterosis, independent of genetic information, and may serve as biomarkers in crop breeding. Significance Statement: The genomes of F1 hybrids display substantial non‐additive DNA methylation changes relative to their parental lines. Here we review our current understanding of the molecular mechanisms underlying these events and discuss the extent to which they trigger transcriptional changes in phenotypic heterosis. [ABSTRACT FROM AUTHOR]

Ogura cytoplasmic male sterility (Ogura CMS) is extensively applied in hybrid seed production in cruciferous crops. However, the posttranscriptional molecular basis of Ogura CMS in cruciferous crops remains elusive. Here, a data-independent acquisition-based proteomic approach coupled with a parallel reaction monitoring-based targeted proteomic assay was used to analyze the proteome dynamics of Ogura CMS cabbage line RM and its maintainer line RF during floral bud development to obtain insights into the mechanism underlying Ogura CMS in cruciferous crops. A total of 9 162 proteins corresponding to 61 464 peptides were identified in RM and RF floral buds. The proteomic fluctuation of RM was weaker than that of RF. Differences in protein expression between RM and RF gradually enlarged with floral bud development. Fifteen continually up-regulated and eight continually down-regulated proteins were found in RM relative to RF throughout floral bud development. Differentially expressed proteins between RM and RF during floral bud development were implicated in the endoplasmic reticulum (ER)-associated protein processing pathway, in which most of them exhibited down-regulated expression in RM. These data suggest that ER-associated protein processing may be involved in pollen abortion in Ogura CMS cabbage by inhibiting the expression of critical factors. Our findings not only deepen the understanding of the molecular mechanisms of Ogura CMS in cruciferous crops but also provide better guidance for applying Ogura CMS in the hybrid breeding of cruciferous crops. [ABSTRACT FROM AUTHOR]

Genome editing provides exciting new opportunities to develop transgene-free mutants with desired modifications to meet global food demands. Current developments in genome editing and the diversity of CRISPR-associated proteins with various protospacer adjacent motif regions have redefined our ability to edit plant genomes. Improved Cas nucleases have been developed that could increase editing efficiencies and reduce off-targets as next-generation Cas-nuclease systems for genome-editing crops. Mutant sequencing and integration of data with artificial intelligence approaches could be used to seek any off-target edits and predict possible new protein–protein interactions. Regulatory authorities are increasingly viewing targeted mutagenesis as an extension of conventional plant breeding: the trend is to deregulate edited products if they could have been generated by conventional plant breeding processes. The CRISPR/Cas system comprises RNA-guided nucleases, the target specificity of which is directed by Watson–Crick base pairing of target loci with single guide (sg)RNA to induce the desired edits. CRISPR-associated proteins and other engineered nucleases are opening new avenues of research in crops to induce heritable mutations. Here, we review the diversity of CRISPR-associated proteins and strategies to deregulate genome-edited (GEd) crops by considering them to be close to natural processes. This technology ensures yield without penalties, advances plant breeding, and guarantees manipulation of the genome for desirable traits. DNA-free and off-target-free GEd crops with defined characteristics can help to achieve sustainable global food security under a changing climate, but need alignment of international regulations to operate in existing supply chains. The CRISPR/Cas system comprises RNA-guided nucleases the target specificity of which is directed by Watson–Crick base pairing of target loci with single guide (sg)RNA to induce the desired edits. CRISPR-associated proteins and other engineered nucleases are opening new avenues of research in crops to induce heritable mutations. Here, we review the diversity of CRISPR-associated proteins and strategies to deregulate genome-edited (GE) crops by considering them to be close to natural processes. This technology ensures yield without penalties, advances plant breeding, and guarantees manipulation of the genome for desirable traits. DNA-free and off-target-free GE crops with defined characteristics can help to achieve sustainable global food security under a changing climate, but need alignment of international regulations to operate in existing supply chains. [ABSTRACT FROM AUTHOR]

Understanding plant sex chromosomes involves studying interactions between developmental and physiological genetics, genome evolution, and evolutionary ecology. We focus on areas of overlap between these. Ideas about how species with separate sexes (dioecious species, in plant terminology) can evolve are even more relevant to plants than to most animal taxa because dioecy has evolved many times from ancestral functionally hermaphroditic populations, often recently. One aim of studying plant sex chromosomes is to discover how separate males and females evolved from ancestors with no such genetic sex-determining polymorphism, and the diversity in the genetic control of maleness vs femaleness. Different systems share some interesting features, and their differences help to understand why completely sex-linked regions may evolve. In some dioecious plants, the sex-determining genome regions are physically small. In others, regions without crossing over have evolved sometimes extensive regions with properties very similar to those of the familiar animal sex chromosomes. The differences also affect the evolutionary changes possible when the environment (or pollination environment, for angiosperms) changes, as dioecy is an ecologically risky strategy for sessile organisms. Dioecious plants have repeatedly reverted to cosexuality, and hermaphroditic strains of fruit crops such as papaya and grapes are desired by plant breeders. Sex-linked regions are predicted to become enriched in genes with sex differences in expression, especially when higher expression benefits one sex function but harms the other. Such trade-offs may be important for understanding other plant developmental and physiological processes and have direct applications in plant breeding. Plant sex chromosomes can add to understanding of sex chromosomes generally, including regular absence of recombination near the sex-determining loci, and repeated expansion of sex-linked regions. [ABSTRACT FROM AUTHOR]

Plant height (PH) is an essential agronomic trait that can be used to assist in crop breeding pipelines, assess crop productivity and make crop management decisions. Improving the accuracy of the digital terrain model (DTM) and optimising the PH features of the crop surface model obtained from unmanned aerial vehicle (UAV) images contribute to PH estimation. The influence of the fractional vegetation cover (FVC) on DTM reconstruction accuracy was investigated for the first time, and the influence of the view angle (oblique and nadir) and spatial resolution on the accuracy of maize PH estimation was explored. The results show that the accuracy of the DTM constructed using the inverse distance weighted algorithm was significantly influenced by the FVC conditions. Compared with the DTM constructed using UAV images over bare soil, FVC less than 0.4 was necessary for the accurate construction of the DTM, with average estimation errors of 0.15 m in 2018 and 0.09 m in 2019. Compared with the nadir view, the oblique view resulted in a more accurate 3D reconstruction. When the original spatial resolution of 15 mm was upscaled to 20, 30, 60 and 120 mm, a decreasing trend of PH estimation accuracy was observed, with root mean square error increasing from 0.35 to 0.40 m and mean absolute error increasing from 0.30 to 0.36 m. Overall, this study investigated the optimal FVC conditions for accurate DTM construction and the influence of the view angle and spatial resolution on PH estimation based on UAV RGB images. • UAV missions were implemented across two maize growing seasons. • Influences of FVC on the interpolation accuracy of DTM were investigated. • Effects of acquisition views and spatial resolution on PH estimation were explored. • FVC less than 0.4 is required for the accurate construction of DTM. • The oblique view could result in a more accurate 3-D reconstruction. [ABSTRACT FROM AUTHOR]

This article discusses the challenges facing agriculture in Africa, such as low productivity, climate change, and issues of obesity and undernutrition. The African Potato Association (APA) is working to address these challenges by promoting research, production, and utilization of potatoes and sweet potatoes in Africa. The article highlights the 12th Triennial African Potato Association Conference, which focused on using potato and sweet potato innovations to create resilient and healthier agri-food systems. The conference covered topics such as breeding, sustainable seed systems, pest and disease management, and policies for achieving impact at scale. Collaboration and dissemination of research findings are emphasized as crucial for ensuring that technical innovations have a meaningful impact on food and nutrition security. The article also mentions a special issue of the African Potato Association's journal, which covers various aspects of potato and sweet potato production in Africa, including seed systems, pest management, marketing, and policies. The document expresses gratitude to the authors, editor, and technical editor for their contributions to the special issue. The next triennial meeting of the African Potato Association will take place in Kampala, Uganda in 2025. [Extracted from the article]

Over the past decade, genomic selection (GS) has gained significant traction as a valuable tool for predicting the phenotypic performance in plant breeding populations and for expediting the development of new cultivars. Diverse statistical models and approaches have been developed to facilitate the integration of GS into plant breeding practices, with a growing emphasis on strategies that enhance accurate and resource‐efficient prediction. Since its inception in 2010, the sweet sorghum [Sorghum bicolor (L.) Moench] breeding program at Centre Haïtien d'Innovation en Biotechnologies et pour une Agriculture Soutenable has taken the lead in endeavors to cultivate and introduce varieties that exhibit resilience against both abiotic and biotic stresses. Among these challenges, drought stress holds particular prominence, given the reliance of growers on unpredictable rainfall patterns for successful sorghum production. The central objective of this study was to assess the predictive ability of genomic prediction models across varying environmental conditions in Haiti, employing two statistical methods. Our assessment encompassed 12 distinct sorghum traits, with genomic predictions conducted both within and across irrigated and water‐stress treatments, executed at different planting dates. Overall, the two methods showed similar results. Prediction accuracy was notably higher for within‐environment scenarios (ranging from 0.30 to 0.71) as opposed to across‐environment scenarios (ranging from 0.08 to 0.68). Furthermore, there was considerable variation in the prediction accuracy for all traits, with "total soluble solids" displaying the highest mean value (0.71), while "total stem number" exhibited the lowest (0.38). The attained genomic prediction accuracies in this study offer encouraging insights for the integration of GS strategies in small‐scale breeding programs, particularly those aimed at enhancing drought tolerance. Core Ideas: The phenotypic distribution of the 12 phenotypic sorghum traits was close to symmetric.Prediction accuracy varied significantly among all traits, with total soluble solids having the highest mean value, while maturity time and grain yield exhibited the lowest.Prediction accuracy was higher within environments than across environments.Bayes B and Bayes ridge regression performed similarly for all 12 traits.The prediction accuracy for grain yield across environments involving the water stress 2 condition is low.Genomic heritability is higher in favorable environmental conditions than unfavorable conditions.Total soluble solids exhibited high genomic heritability across all water regime levels. [ABSTRACT FROM AUTHOR]

Feeding the world's ever‐increasing population requires continuous development of high‐yielding and disease‐resistant cultivars of food crops such as wheat (Triticum aestivum L.). Speed breeding, which utilizes longer photoperiod times and higher temperatures, is a technique that accelerates plant development and is rapidly being adopted by wheat breeders across the globe to fast‐track cultivar development. Plant diseases are a major threat to crop production, and breeding for disease resistance is a major goal of crop breeders. Fusarium head blight (FHB), caused by Fusarium graminearum, is a major disease of small grain cereals, affecting their yield and quality. The aim of present work was to assess if speed breeding conditions can be used to accelerate reliable assessment of FHB severity and mycotoxin deoxynivalenol (DON) accumulation in wheat varieties. We screened a set of six spring wheat genotypes with different levels of genetic resistance (two moderately susceptible, two highly susceptible, one moderately resistant, and one resistant) for their response to FHB at 14 days after inoculation (dai) and 21 dai and DON accumulation under normal versus speed breeding conditions. FHB severity and DON accumulation were found to be highly correlated at all time points under normal and speed breeding conditions. Robust differentiation between resistant and susceptible genotypes could be achieved at 14 dai rather than the normal period of 21 dai, saving at least a week in phenotyping. Combined with the accelerated growth, flowering, and maturity under these conditions, efficient FHB screening and DON evaluation under speed breeding conditions will fast‐track development of resistant wheat varieties. Core Ideas: Speed breeding is increasingly being adopted by crop breeding programs.We evaluated spring wheat genotypes with different levels of genetic resistance for Fusarium head blight (FHB) and deoxynivalenol (DON) levels under speed breeding versus regular conditions.Reliable distinction could be made in FHB severity at 14 days after inoculation (dai) under speed breeding as compared to 21 dai under normal growth conditions.Growing and testing the plants under speed breeding conditions saved a total of 21–23 days as compared to regular conditions. [ABSTRACT FROM AUTHOR]

The article provides a list of individuals who have received awards in the field of crop science, highlighting their contributions to research, teaching, mentoring, and service. It also profiles various individuals involved in agricultural research, including undergraduate and graduate students, who are pursuing degrees or working in fields related to agronomy, plant science, soil science, and related disciplines. These individuals come from diverse backgrounds and are passionate about improving agricultural practices, sustainability, and crop productivity. Their research focuses on topics such as plant breeding, soil health, water resources, and crop management. [Extracted from the article]

The principal selection objective in crop breeding has for a long time been driven by agronomic gains like yield maximization and climate resilience. Nevertheless, the continued low adoption of new varieties and documented gender technology adoption gap has triggered re‐thinking of this strategy, with end‐user acceptability of released varieties a key strategy in breeding objectives. Using a mixed‐methods approach with a survey of 122 producers and focus group discussions with 200 male and female producers in two major sweetpotato [Ipomoea batatas (L.) Lam] producing districts in Uganda, this study set out to understand gender‐disaggregated traits that drive acceptance for improved sweetpotato varieties as a guide to development of new varieties in the region. A generalized structural equation model approach is used to analyze how interrelated trait preferences shape acceptance for improved varieties, while in‐depth insights from a qualitative approach are used to further ground observed results. Traits such as high root yields, drought tolerance, and vitamin A are shown to be key drivers to acceptance of improved varieties, while good taste and dry matter content dampen acceptance of improved varieties in favor of landraces. Male farmers are also shown to mainly prefer agronomic traits such as high yields and stress tolerance, while women mostly prefer quality traits such as good taste, vitamin A, and high dry matter content. To achieve higher acceptability and adoption of improved varieties across the gender divide, new varieties need to not only consider agronomic gains, but also quality‐related traits such as taste and dry matter content. Core Ideas: End‐user acceptability is critical in crop breeding for adoption at scale of new released varieties.Quality traits are important for variety acceptance and need to be prioritized in variety breeding.For inclusive impacts, breeding programs need to consider gender implications of new varieties. [ABSTRACT FROM AUTHOR]

Context: Long-term multi-environment trials (METs) could improve genomic prediction models for plant breeding programs by better representing the target population of environments (TPE). However, METs are generally highly unbalanced because genotypes are routinely dropped from trials after a few years. Furthermore, in the presence of genotype × environment interaction (GEI), selection of the environments to include in a prediction set becomes critical to represent specific TPEs. Aims: The goals of this study were to compare strategies for modelling GEI in genomic prediction, using large METs from oat (Avena sativa L.) breeding programs in the Midwest United States, and to develop a variety decision tool for farmers and plant breeders. Methods: The performance of genotypes in TPEs was predicted by using different strategies for handling GEI in genomic prediction models including systematic and/or random GEI components. These strategies were also used to build the variety decision tool for farmers. Key results: Genomic prediction for unknown genotypes, locations and years within TPEs had moderate to high predictive ability, accuracy and reliability. Modelling GEI was beneficial in small, but not in large, mega-environments. The latest 3 years were highly predictive of performance in an upcoming year for most years but not for years with unusual weather patterns. High predictive ability, accuracy and reliability were obtained when large datasets were used in TPEs. Conclusions: Deployment of historical datasets can be accomplished through meaningful delineation and prediction for TPEs. Implications: We have shown the performance of a simple modelling strategy for handling prediction for TPEs when deploying large historical datasets. Rankings of genotypic performance may change from one environment to the next, creating genotype × environment interaction (GEI), which can impact genomic prediction and complicate identification of superior genotypes. We compared strategies for predicting the performance of individuals in the presence of GEI. The results provide useful tools for the optimisation of training populations and testing environments for the prediction of individuals in the targeted populations of environments. [ABSTRACT FROM AUTHOR]

Starch is a significant ingredient of the seed endosperm with commercial importance in food and industry. Crop varieties with glutinous (waxy) grain characteristics, i.e. starch with high amylopectin and low amylose, hold longstanding cultural importance in some world regions and unique properties for industrial manufacture. The waxy character in many crop species is regulated by a single gene known as GBSSI (or waxy), which encodes the enzyme Granule Bound Starch Synthase1 with null or reduced activity. Several allelic variants of the waxy gene that contribute to varying levels of amylose content have been reported in different crop plants. Phylogenetic analysis of protein sequences and the genomic DNA encoding GBSSI of major cereals and recently sequenced millets and pseudo-cereals have shown that GBSSI orthologs form distinct clusters, each representing a separate crop lineage. With the rapidly increasing demand for waxy starch in food and non-food applications, conventional crop breeding techniques and modern crop improvement technologies such as gene silencing and genome editing have been deployed to develop new waxy crop cultivars. The advances in research on waxy alleles across different crops have unveiled new possibilities for modifying the synthesis of amylose and amylopectin starch, leading to the potential creation of customized crops in the future. This article presents molecular lines of evidence on the emergence of waxy genes in various crops, including their genesis and evolution, molecular structure, comparative analysis and breeding innovations. [ABSTRACT FROM AUTHOR]

Genetic diversity in plant breeding is key to dissecting the genetic architecture of complex economical traits. Genome-wide association studies (GWAS) and genomic selection (GS) have emerged as promising tools to accelerate agronomic trait improvement efficiency, defining current breeding strategies. The key objective of this study was to investigate the genetic architecture and perform genomic prediction of yield, specific gravity (SG), and dry matter (DM) traits, using a diversity panel of 568 Solanum tuberosum Andigenum accessions. Analyses were carried out using a total of 4271 Single Nucleotide Polymorphisms (SNPs) obtained using the SolCAP SNP array 8 K version. Yield data were collected from field evaluations during three consecutive years, while tuber quality traits (SG and DM) were evaluated in 1 year. To this end, population structure was first examined and revealed two main subpopulations. GWAS analysis identified candidate loci for yield in chromosomes 1, 3, 4 and 11, with minor effects on phenotypic variation (< 1–10%). Important genomic regions were detected for SG in chromosomes 5, 6, and 8, and in DM in chromosome 7, though they explained only a small fraction of the phenotypic variation (< 1–2% for SG and 3% for DM). Functional annotation of candidate genes showed promising genomic regions related to tuber growth, quality and development that could further be verified by other tools (i.e., gene editing). Furthermore, the predicted capacity of the cross-validation process between subpopulations was low for yield and specific gravity. However, when the prediction process was conducted across the entire population, the predictive power increase, as a greater diversity in the data enables better prediction. Instead, dry matter genomic prediction accuracies were higher in accordance with its higher narrow sense heritability value. These findings enriched GWAS analyses in an Andigenum potato collection and reinforce the potential of applying GS in Colombian breeding programs using diverse populations. [ABSTRACT FROM AUTHOR]

Mutagenesis is the process of creating mutations in an organism's DNA. Induced mutagenesis can be used to create crops with higher yields, better quality, disease and insect resistance, and stress tolerance, all of which are critical for food security and sustainable agriculture. Physical, biological and chemical mutagens can induce mutations in seeds and other plant propagules, followed by selection for superior agronomic traits in the first generation. The phenotypic stability of agronomic features generated by the mutagenesis process is established in the second and third generations, with the following generations undergoing further evaluation. Only mutant lines exhibiting the desired characteristics are chosen as new varieties or parent lines for a breeding program. New crop varieties are developed around the world utilizing induced mutagenesis techniques such as irradiation or chemical mutagens. In this review, we examine the different approaches to mutagenesis, their applications, challenges and prospects for increasing crop productivity and quality. [ABSTRACT FROM AUTHOR]