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Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability., (© 2024 The Author(s). Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype-phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties., (© 2024. The Author(s).)

Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data analysis and pattern recognition, and is revolutionizing numerous scientific domains including plant breeding. We explore the wider potential of AI tools in various facets of breeding, including data collection, unlocking genetic diversity within genebanks, and bridging the genotype-phenotype gap to facilitate crop breeding. This will enable the development of crop cultivars tailored to the projected future environments. Moreover, AI tools also hold promise for refining crop traits by improving the precision of gene-editing systems and predicting the potential effects of gene variants on plant phenotypes. Leveraging AI-enabled precision breeding can augment the efficiency of breeding programs and holds promise for optimizing cropping systems at the grassroots level. This entails identifying optimal inter-cropping and crop-rotation models to enhance agricultural sustainability and productivity in the field., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Domestication syndrome, selection pressure, and modern plant breeding programs have reduced the genetic diversity of the wheat germplasm. For the genetic gains of breeding programs to be sustainable, plant breeders require a diverse gene pool to select genes for resistance to biotic stress factors, tolerance to abiotic stress factors, and improved quality and yield components. Thus, old landraces, subspecies and wild ancestors are rich sources of genetic diversity that have not yet been fully exploited, and it is possible to utilize this diversity. Compared with durum wheat, tetraploid wheat subspecies have retained much greater genetic diversity despite genetic drift and various environmental influences, and the identification and utilization of this diversity can make a greater contribution to the genetic enrichment of wheat. In addition, using the pre-breeding method, the valuable left-behind alleles in the wheat gene pool can be re-introduced through hybridization and introgressive gene flow to create a sustainable opportunity for the genetic gain of wheat. This review provides some insights about the potential of tetraploid wheats in plant breeding and the genetic gains made by them in plant breeding across past decades, and gathers the known functional information on genes/QTLs, metabolites, traits and their direct involvement in wheat resistance/tolerance to biotic/abiotic stresses., Competing Interests: Declaration of Competing Interest There is no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Wheat (Triticum sp.) is a staple cereal crop, providing nearly a fifth of the world's protein and available calories. While fungi associated with wheat plants have been known for centuries, attention to fungi associated with wheat seeds has increased over the last hundred years. Initially, research focused on fungal taxa that cause seed-borne diseases. Seeds act as a physical link between generations and host specialized fungal communities that affect seed dormancy, germination, quality, and disease susceptibility. Interest in beneficial, non-disease-causing fungal taxa associated with seeds has grown since the discovery of Epichloë in fescue, leading to a search for beneficial fungal endophytes in cereal grains. Recent studies of the wheat seed mycobiome have shown that disease, seed development, and temporal variation significantly influence the composition and structure of these fungal communities. This research, primarily descriptive, aims to better understand the wheat seed mycobiome's function in relation to the plant host. A deeper understanding of the wheat seed mycobiome's functionality may offer potential for microbiome-assisted breeding., (© 2024 The Author(s). Environmental Microbiology Reports published by John Wiley & Sons Ltd.)

Advancements in New Plant Breeding Techniques have emerged as promising tools for enhancing crop productivity, quality, and resilience in the face of global challenges, such as climate change and food security. However, the successful implementation of these techniques relies also on public acceptance of this innovation. Understanding what shapes public perception and acceptance of New Plant Breeding Techniques is crucial for effective science communication, policymaking, and the sustainable adoption of these innovations. The objective of this systematic review was to synthesize existing research on the public perception of New Plant Breeding Techniques applied to food crops and explore the psychosocial determinants that influence acceptance. Twenty papers published between 2015 and 2023 were included on various New Plant Breeding Techniques and their reception by the general public. Determinants affecting the acceptance of food crops derived from New Plant Breeding Techniques were categorized into six areas: sociodemographic factors, perceived benefits and risks, attitudes toward science, communication strategies, personal values, and product characteristics., Competing Interests: Declaration of conflicting interestsThe author(s) declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

This study focuses on the promising use of biospeckle technology to detect water stress in plants, a complex physiological mechanism. This involves monitoring the temporal activity of biospeckle pattern to study the occurrence of stress within the leaf. The effects of water stress in plants can involve physical and biochemical changes. Some of these changes may alter the optical scattering properties of leaves. The present study therefore proposes to test the potential of a biospeckle measurement to observe the temporal evolution in different varieties of sunflower plants under water stress. An experiment applying controlled water stress with osmotic shock using polyethylene glycol 6000 (PEG) was conducted on two sunflower varieties: one sensitive, and the other more tolerant to water stress. Temporal monitoring of biospeckle activity in these plants was performed using the average value of difference (AVD) indicator. Results indicate that AVD highlights the difference in biospeckle activity between day and night, with lower activity at night for both varieties. The addition of PEG entailed a gradual decrease in values throughout the experiment, particularly for the sensitive variety. The results obtained are consistent with the behaviour of the varieties submitted to water stress. Indeed, a few days after the introduction of PEG, a stronger decrease in AVD indicator values was observed for the sensitive variety than for the resistant variety. This study highlights the dynamics of biospeckle activity for different sunflower varieties undergoing water stress and can be considered as a promising phenotyping tool.

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., Competing Interests: Declaration of interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Abstract Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype–phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties.

At the turn of 2000 many authors envisioned future plant breeding. Twenty years after, which of those authors' visions became reality or not, and which ones may become so in the years to come. After two decades of debates, climate change is a "certainty," food systems shifted from maximizing farm production to reducing environmental impact, and hopes placed into GMOs are mitigated by their low appreciation by consumers. We revise herein how plant breeding may raise or reduce genetic gains based on the breeder's equation. "Accuracy of Selection" has significantly improved by many experimental-scale field and laboratory implements, but also by vulgarizing statistical models, and integrating DNA markers into selection. Pre-breeding has really promoted the increase of useful "Genetic Variance." Shortening "Recycling Time" has seen great progression, to the point that achieving a denominator equal to "1" is becoming a possibility. Maintaining high "Selection Intensity" remains the biggest challenge, since adding any technology results in a higher cost per progeny, despite the steady reduction in cost per datapoint. Furthermore, the concepts of variety and seed enterprise might change with the advent of cheaper genomic tools to monitor their use and the promotion of participatory or citizen science. The technological and societal changes influence the new generation of plant breeders, moving them further away from field work, emphasizing instead the use of genomic-based selection methods relying on big data. We envisage what skills plant breeders of tomorrow might need to address challenges, and whether their time in the field may dwindle., (© 2023 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP-theoretically reaching one when using the Pearson's correlation as a metric-is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding., (Copyright © 2024 The Author. Published by Elsevier Inc. All rights reserved.)

Plant breeding, often known as the science of plant development, is the study and practice of modifying a plant’s genetic makeup through a variety of breeding techniques to produce higher-quality, more prolific, and more resistant to harsh environmental circumstances. Classical breeding programs are indispensable techniques for increasing yields and improving plant characteristics, but they are progressing too slowly to meet the increasing food demand of the rapidly growing world population alone. Considering that the development periods of plants are generally long in traditional plant breeding, the opportunity to develop higher quality and more productive species that are more resistant to abiotic and biotic stress factors is very limited. Because there are multiple steps required in producing new plant varieties, including hybridization, selection, and testing, the process of creating a new variation takes several years. However, it is important to rapidly develop plant varieties with desirable characteristics to meet the increasing food demand of the rapidly growing world population, so the application of biotechnological methods integrated into plant breeding and combined with traditional methods can help reduce food shortages. Today, with the quick acceleration of biotechnology, molecular DNA marker technology has been developed in plant breeding and very important developments have been experienced. Thanks to the development of molecular tools for genetic research aimed at improving agricultural traits in plants related to crop yield, crop quality, or tolerance to adverse environmental conditions, we now have a much better understanding of plant genetics and the architecture and function of plant genomes. Therefore, it is of critical importance to revise current breeding procedures by incorporating molecular markers into breeding programs in the future.

ABSTRACT Check varieties are used in plant breeding and variety testing for a number of reasons. One important use of checks is to provide connectivity between years, which facilitates comparison among genotypes of interest that are tested in different years. When long‐term data are available, such comparisons allow an assessment of realized genetic gain (RGG). Here, we consider the question of how many check varieties are needed per cycle for a reliable assessment of RGG. We propose an approach that makes use of variance component estimates for relevant random effects in a linear mixed model and plugs them into an analysis of dummy datasets set up to represent the design options being considered. Our results show that it is useful to employ a larger number of checks and to keep the replacement rate low. Furthermore, there is intercycle information to be recovered, especially when there are few checks and replacement rates are high, so modelling the cycle main effect as random pays off. [ABSTRACT FROM AUTHOR]

Plant breeding started when humans transitioned to settled agriculture, focusing on domestication, selection, and crop introduction. Initially, the processes were slow until the scientific revolution accelerated the development of new varieties. The establishment of the first plant breeding institute in the 18th century highlighted its economic importance. Mendel's experiment established a scientific foundation for plant breeding, which was further advanced by cytological studies focusing on chromosomes, pure-line theory, inbreeding depression, backcross, single seed descent (SSD), and recurrent selection. Later, mutation breeding added new variations. The 20th century's Green Revolution resulted in high-yielding crop varieties. In the 21st century, biotechnology and molecular biology such as genetic engineering, genomics, marker-assisted selection, CRISPR, and bioinformatics techniques revolutionized plant breeding. These technologies have led to the development of novel, resistant, and high-yielding varieties, contributing to sustainable agriculture and food security. This review explores plant breeding evolution, discussing traditional breeding methods, the impact of Mendelian genetics, the Green Revolution, and recent biotechnological advancements. By integrating these diverse materials, this review provides a comprehensive resource for breeders, highlighting how the innovations improved crop varieties to address food challenges. This information is particularly valuable for developing countries in their breeding strategies for sustainable food security. [ABSTRACT FROM AUTHOR]

Spatial adjustments are used to improve the estimate of plot seed yield across crops and geographies. Moving means (MM) and P‐Spline are examples of spatial adjustment methods used in plant breeding trials to deal with field heterogeneity. Within the trial, spatial variability primarily comes from soil feature gradients, such as nutrients, but a study of the importance of various soil factors including nutrients is lacking. We analyzed plant breeding progeny row (PR) and preliminary yield trial (PYT) data of a public soybean breeding program across 3 years consisting of 43,545 plots. We compared several spatial adjustment methods: unadjusted (as a control), MM adjustment, P‐spline adjustment, and a machine learning‐based method called XGBoost. XGBoost modeled soil features at: (a) the local field scale for each generation and per year, and (b) all inclusive field scale spanning all generations and years. We report the usefulness of spatial adjustments at both PR and PYT stages of field testing and additionally provide ways to utilize interpretability insights of soil features in spatial adjustments. Our work shows that using soil features for spatial adjustments increased the relative efficiency by 81%, reduced the similarity of selection by 30%, and reduced the Moran's I from 0.13 to 0.01 on average across all experiments. These results empower breeders to further refine selection criteria to make more accurate selections and select for macro‐ and micro‐nutrients stress tolerance. [ABSTRACT FROM AUTHOR]

In the background of the new agricultural science, universities need to focus on the fundamental task of cultivating morality and talents, focusing on national major strategies such as rural revitalization, and cultivating a group of applied innovative talents with solid professional knowledge, practical and innovative abilities, as well as understanding agriculture, loving rural areas, and loving farmers. The cultivation of talents relies on the construction of high-quality professional courses. Horticultural plant breeding is a major backbone course of the horticulture major. Through preliminary exploration and practice, this course has constructed a "Trinity" ideological and political teaching system, which has certain reference significance for the ideological and political construction of agricultural related courses. [ABSTRACT FROM AUTHOR]

Increasing cropping system diversity has great potential to address environmental problems associated with modern agriculture, such as erosion, soil carbon loss, nutrient runoff, water pollution, and loss of biodiversity. As with other agricultural sciences, plant breeding has primarily been conducted in the context of dominant monoculture cropping systems, with little focus on multicrop systems. Multicrop systems have increased temporal and/or spatial diversity and include a diverse set of crops and practices. In order to support a transition to multicrop systems, plant breeders must shift their breeding programs and objectives to better represent more diverse systems, including diverse rotations, alternate-season crops, ecosystem service crops, and intercropping systems. The degree to which breeding methods need to change will depend on the cropping system context in question. Plant breeding alone, however, cannot drive adoption of multicrop systems. Alongside shifts in breeding approaches, changes are needed within broader research, private sector, and policy contexts. These changes include policies and investments that support a transition to multicrop systems, increased collaboration across disciplines to support cropping system development, and leadership from both the public and private sectors to develop and promote adoption of new cultivars.

Gene editing has the potential to make new crop varieties faster and more efficiently. New and more suitable crop varieties can increase sustainable agriculture, for instance, in the form of disease-resistant varieties that facilitate integrated pest management. The European Commission's proposal on the regulation of gene-edited and cisgenic plants produced with New Genomic Techniques (including CRISPR/Cas) has re-opened the discussion on Intellectual Property Rights on plants in Europe. We provide an overview of the possible impact of patent rights and Plant Variety Rights on the availability of technology and gene-edited alleles to breeders on an European level. We highlight potential problems with the two Intellectual Property Right systems and indicate potential avenues to solutions. [ABSTRACT FROM AUTHOR]

The Multitrait Genotype Ideotype Distance Index (MGIDI) is a strong and adaptable technique for choosing superior genotypes of diverse crops based on numerous attributes. It is a multivariate selection indicator that incorporates different characteristic information into a single value and ranks genotypes based on their distance from an ideal genotype. Breeders can use variable selection criteria including weighting traits and assessing genetic strengths and weaknesses. It organizes attributes into components and chooses optimal genotypes based on many traits using principal component analysis. This review covered the available information regarding the background, applications, prospects, and limitations of MGIDI for crop improvement and breeding in this research. We discussed the significant discoveries and consequences of several studies that used MGIDI to enhance the productivity, excellence, and flexibility of numerous crops, such as bush yam, barley, cassava, cucumber, guar, lentil, maize, rice, bean, soybean, wheat, etc. Additionally, we talked about some of the potential applications of MGIDI for breeding and crop improvement, such as tolerance to salinity, stability analysis, tolerance to waterlogging, mechanism of drought response, performance in agronomy and tuber quality, nutritional value and productivity, adaptability, increased yield, early maturity, and stress resistance etc. Following the upward trend, MGIDI can be considered as a valuable index technique for selection of crop genotypes that can address food security, climate change, and nutritional quality problems worldwide. We expect that this study will spark more research and use of MGIDI in different crops characteristics, contributing to the improvement of plant breeding science.

Background: Andrographis paniculata (Burm.f.) Nees is a plant native to Thailand. Thais use andrographis as an herb for treating the common cold. During pandemic the Andrographis leaves and stem has been used to treat COVID-19. In Thailand, there is a demand for andrographis, leading to a shortage of andrographis. Breeding andrographis by inducing polyploid plants is one way to increase yields in stem and leaf sections. Methods: The study was conducted in May-September 2022 at Kasetsart University, Chalermprakiat Sakon Nakhon Campus, Thailand, by inducing andrographis of Phichit 4-4 variety into polyploids with colchicine concentrations of 0.0, 0.1, 0.2, 0.3 and 0.4%. After that, study of agricultural characteristics and identification of polyploids with flow cytometry analysis were carried out. Result: A study on the characteristics of andrographis Phichit 4-4 after inducing colchicine in various treatments at 2 months of age showed that andrographis received with colchicine had a higher stem height and number of node than those without colchicine. Comparison of characteristics of andrographis Phichit 4-4 at 4 months of age. The number of leaves per plant and leaf weight are greater than those treated without colchicine. When examining the polyploids of andrographis plants using flow cytometry analysis, it was found that the plants with abnormal characteristics with tall stems, large leaves, thick leaves, dark green leaves are mixoploids. Studies have found that there are many abnormal plants in colchicine-treated treatments. 0.1% for 24 and 48 hours. [ABSTRACT FROM AUTHOR]

Genetic diversity is a key factor for plant breeding. The birth of novel genic and genomic variants is also crucial for plant adaptation in nature. Therefore, the genomes of almost all living organisms possess natural mutagenic mechanisms. Transposable elements (TEs) are a major mutagenic force driving genetic diversity in wild plants and modern crops. The relatively rare TE transposition activity during the thousand-year crop domestication process has led to the phenotypic diversity of many cultivated species. The utilization of TE mutagenesis by artificial and transient acceleration of their activity in a controlled mode is an attractive foundation for a novel type of mutagenesis called TE-mediated biological mutagenesis. Here, I focus on TEs as mutagenic sources for plant breeding and discuss existing and emerging transgene-free approaches for TE activation in plants. Furthermore, I also review the non-randomness of TE insertions in a plant genome and the molecular and epigenetic factors involved in shaping TE insertion preferences. Additionally, I discuss the molecular mechanisms that prevent TE transpositions in germline plant cells (e.g., meiocytes, pollen, egg and embryo cells, and shoot apical meristem), thereby reducing the chances of TE insertion inheritance. Knowledge of these mechanisms can expand the TE activation toolbox using novel gene targeting approaches. Finally, the challenges and future perspectives of plant populations with induced novel TE insertions (iTE plant collections) are discussed.

Main Conclusion: Genomics-assisted breeding represents a crucial frontier in enhancing the balance between sustainable agriculture, environmental preservation, and global food security. Its precision and efficiency hold the promise of developing resilient crops, reducing resource utilization, and safeguarding biodiversity, ultimately fostering a more sustainable and secure food production system. Agriculture has been seriously threatened over the last 40 years by climate changes that menace global nutrition and food security. Changes in environmental factors like drought, salt concentration, heavy rainfalls, and extremely low or high temperatures can have a detrimental effects on plant development, growth, and yield. Extreme poverty and increasing food demand necessitate the need to break the existing production barriers in several crops. The first decade of twenty-first century marks the rapid development in the discovery of new plant breeding technologies. In contrast, in the second decade, the focus turned to extracting information from massive genomic frameworks, speculating gene-to-phenotype associations, and producing resilient crops. In this review, we will encompass the causes, effects of abiotic stresses and how they can be addressed using plant breeding technologies. Both conventional and modern breeding technologies will be highlighted. Moreover, the challenges like the commercialization of biotechnological products faced by proponents and developers will also be accentuated. The crux of this review is to mention the available breeding technologies that can deliver crops with high nutrition and climate resilience for sustainable agriculture., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Forage plant breeding aims to deliver cultivars that increase on-farm productivity through improved seasonal and annual yield, persistence of yield in perennials, and nutritive and feeding value. Breeding is generally undertaken in highly controlled field trials with individual plants or rows. However, the correlation of trait values between spaced plant trials and sward plots of forages is often low and non-significant. Heritability of traits, a measure of likely gains that can be achieved from plant breeding, can be moderate to high for many traits. The upper level of genetic gains in forage yield measured in small plot trials ranges between 6% and 15% per decade depending on species, indicating significant and lasting improvements have been achieved. Results from some farmlet scale grazing trials measuring animal performance support this but some others, particularly with dairy cows, fail to show advantage to improved cultivars. Factors contributing to this include aspects of systems management, systems trial design, and/or breeding objectives and evaluation systems; occurrence of environmental stresses; insufficient statistical power; and scaling interactions that restrict or dilute trait expression. Several factors are identified that should be considered as evaluation systems evolve in response to the changing economic, climatic, and regulatory forces affecting grassland farming. [ABSTRACT FROM AUTHOR]

ABSTRACTCRISPR/Cas9 gene editing system is recently developed robust genome editing technology for accelerating plant breeding. Various modifications of this editing system have been established for adaptability in plant varieties as well as for its improved efficiency and portability. This review provides an in-depth look at the various strategies for synthesizing gRNAs for efficient delivery in plant cells, including chemical synthesis and in vitro transcription. It also covers traditional analytical tools and emerging developments in detection methods to analyze CRISPR/Cas9 mediated mutation in plant breeding. Additionally, the review outlines the various analytical tools which are used to detect and analyze CRISPR/Cas9 mediated mutations, such as next-generation sequencing, restriction enzyme analysis, and southern blotting. Finally, the review discusses emerging detection methods, including digital PCR and qPCR. Hence, CRISPR/Cas9 has great potential for transforming agriculture and opening avenues for new advancements in the system for gene editing in plants.

Key Message: Mating designs determine the realized additive genetic variance in a population sample. Deflated or inflated variances can lead to reduced or overly optimistic assessment of future selection gains. The additive genetic variance [Formula: see text] inherent to a breeding population is a major determinant of short- and long-term genetic gain. When estimated from experimental data, it is not only the additive variances at individual loci (QTL) but also covariances between QTL pairs that contribute to estimates of [Formula: see text]. Thus, estimates of [Formula: see text] depend on the genetic structure of the data source and vary between population samples. Here, we provide a theoretical framework for calculating the expectation and variance of [Formula: see text] from genotypic data of a given population sample. In addition, we simulated breeding populations derived from different numbers of parents (P = 2, 4, 8, 16) and crossed according to three different mating designs (disjoint, factorial and half-diallel crosses). We calculated the variance of [Formula: see text] and of the parameter b reflecting the covariance component in [Formula: see text] standardized by the genic variance. Our results show that mating designs resulting in large biparental families derived from few disjoint crosses carry a high risk of generating progenies exhibiting strong covariances between QTL pairs on different chromosomes. We discuss the consequences of the resulting deflated or inflated [Formula: see text] estimates for phenotypic and genome-based selection as well as for applying the usefulness criterion in selection. We show that already one round of recombination can effectively break negative and positive covariances between QTL pairs induced by the mating design. We suggest to obtain reliable estimates of [Formula: see text] and its components in a population sample by applying statistical methods differing in their treatment of QTL covariances., (© 2023. The Author(s).)

In plant heredity, the phenotype is the result of observation that can be directly observed, while the genotype is the underlying hidden factor that underlies the expression of the phenotype. The genotype is an important aspect that needs to be understood to explain the pattern of trait inheritance and predict trait inheritance in subsequent generations. The discrete hidden Markov model is a model generated by pair of an unobserved Markov chain and an observation process. This model can be applied to tetraploid plant crosses by modeling genotypes as hidden state and phenotypes as the obeservation process. The probability of dominant phenotype in monohybrid, dihybrid and trihybrid crosses occurring over ten generations during that period is as follows 61,305%, 37,583%, and 23,041%. Furthermore, as more traits are crossed, the probability of dominant phenotype appearing within ten generations decreases. When the dominant phenotype occurs over ten generations, the same genotype can be obtained in monohybrid, dihybrid, and trihybrid crosses, which is heterozygous in the first and second generations, while from the third to the tenth generation it is homozygous dominant.

Diversifying and perennializing cropping systems can increase productivity while supporting ecosystem services such as soil protection, nutrient retention, and greenhouse gas mitigation. New crops can help achieve these goals, and advanced computational tools allow plant breeders to rapidly domesticate new crops and select for many traits that support both ecosystem services and profitable production. Intermediate wheatgrass [Thinopyrum intermedium (Host.) Barkworth. & D.R. Dewey; IWG] is a cool‐season perennial grass undergoing domestication to function as a perennial grain crop. Key aboveground domestication traits have been improved to support economically viable yields using genomic selection. However, few studies have quantified belowground traits despite their potential role in conferring ecosystem services. We present a platform for using minirhizotron cameras and machine learning software to analyze rhizotron images for inclusion in genomic selection models. The strength and direction of pairwise correlations between traits were variable with correlation coefficients (r) ranging from −0.27 to 0.99. Grain yield was positively, although weakly, correlated with total root length, area, and volume (r = 0.21, 0.21, and 0.19, respectively). Estimates of narrow sense heritabilities ranged from 0.41 to 0.76 for all traits and 0.46 to 0.66 for root traits. Root trait predictions using a genomic prediction model, measured by correlating model‐predicted values and field‐observed values, ranged from 0.08 to 0.23. Aboveground traits were better predicted (0.17 < r < 0.33). Simply selecting for aboveground traits could result in populations with desirable root traits, but our results demonstrate the potential for genomic selection to aid in advancing populations with specific root traits important for ecosystem services. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) proposed by Meuwissen et al. more than 20 years ago, is revolutionizing plant and animal breeding. Although GS has been widely accepted and applied to plant and animal breeding, there are many factors affecting its efficacy. We studied 14 real datasets to respond to the practical question of whether the accuracy of genomic prediction increases when considering genomic as compared with not using genomic. We found across traits, environments, datasets, and metrics, that the average gain in prediction accuracy when genomic information is considered was 26.31%, while only in terms of Pearson's correlation the gain was of 46.1%, while only in terms of normalized root mean squared error the gain was of 6.6%. If the quality of the makers and relatedness of the individuals increase, major gains in prediction accuracy can be obtained, but if these two factors decrease, a lower increase is possible. Finally, our findings reinforce genomic is vital for improving the prediction accuracy and, therefore, the realized genetic gain in genomic assisted plant breeding programs., (© 2023 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

This review paper addresses the importance of increasing agrobiodiversity to cope with climate change and, at the same time, providing a sufficient amount of healthy food. This is in agreement with the messages from ecology and medicine indicating the advantages of biodiversity in general and agrobiodiversity in particular for the planet and for our health. Plant breeding is considered to be one of the causes of the decline in agrobiodiversity, and therefore, this paper illustrates alternatives to the commonly used approach based on centralized selection. The first alternative is decentralized participatory breeding, which adapts crops to both different agronomic environments and client preferences, representing an "option by context" model of research. The second alternative is evolutionary breeding, which is a more dynamic strategy than participatory plant breeding because it merges the advantages of decentralization with the ability of dynamic mixtures and evolutionary populations to cope with biotic and abiotic stresses and evolve, thus adapting to climate change and to the associated changes in the spectrum of pests. A crop capable of evolving as the environment around it evolves appears to be the most ideal way of responding to climate change and increasing agricultural biodiversity. [ABSTRACT FROM AUTHOR]