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Soil salinity drastically hinders cotton productivity (Gossypium hirsutum), and fiber quality. The current study evaluated morpho-physiological and biochemical responses of fifty cotton genotypes under different salinity levels (control, 12 dS/m, and 17 dS/m) at the seedling stage. The experiment was performed in a factorial complete randomized design with three replications. Significant genotype × treatment interactions were observed for most traits, including shoot length (SL), root length (RL), fresh and dry shoot weight (FSW, DSW), fresh and dry root weight (FRW, DRW), total soluble protein (TSP), proline content, and antioxidant enzymes. Severe salinity stress reduces shoot length (SL) and root length (RL) along with notable decreases in biomass and altered biochemical responses, including increased antioxidant activities and proline content, indicating stress adaptation. Moreover, PCA and Pearson's correlation analyses unveiled strong positive and negative correlations among studied attributes while MGIDI analyses assist in determining the salt-resilient cotton genotypes under applied treatments. The best-performing genotypes under control conditions were G2, G8, and G12, while G7, G43, and G30 showed resilience under severe salinity stress. MGIDI effectively identified genotypes with outstanding salinity tolerance, such as G2, G43, G40, and G26, across all stress levels. This research assists in determining the salinity stress-tolerant cotton genotypes using morpho-physiological and biochemical parameters and MGIDI is used as a precise method for identifying salt-resilient cotton accessions. [ABSTRACT FROM AUTHOR]

Perennial flax (Linum austriacum, Linum perenne, L. austriacum) has a wide range of uses for the horticultural and agronomic markets. Protocols for vegetative propagation culture and production scheduling of perennial flax are needed to advance development of potential ornamental or specialty cut flower (CF) cultivars, specifically for the floriculture market. The purpose of this research was to establish vegetative propagation practices for perennial flax CF selections. Fifteen CF genotypes were tested in four experiments between week 8 of 2022 and week 37 of 2023, using 5-cm cuttings from greenhouse (GH) or field cuttings. We tested mist house (MH) rooting time (2 or 3 weeks) and rooting hormone concentrations [1000 or 2000 ppm indole-3-butyric acid (IBA)]. Experiments tested rooting time over 3 or 4 total weeks, which included 2 or 3 weeks under mist, respectively, and 1 week in GH culture before rating. Rooting success was rated using a six-point Likert scale to gauge number and length of roots per cutting. Expt. 1 rooted for 3 weeks using 1000 ppm IBA, resulting in 66.5% rooting. Expt. 2 (4 weeks, 1000 ppm IBA) had 96.4% rooting. Experiment 3 (4 weeks, 2000 ppm IBA) had 82.0% rooting. Expt. 4 (replicate of Expt. 2 but rated using a binary rooted vs. unrooted rating scale, as done in a commercial setting), resulted in 85.4% rooting. Overall, Expts. 2 and 4 resulted in the greatest mean success rates, despite the differences in root rating methods. An increased IBA concentration is not recommended for Linum genotypes, as it decreased rooting success in this study. Perennial flax vegetative propagation may be successful using 1000 ppm IBA for 4 weeks to multiply GH stock plants and produce plugs (liners) for shipping and CF production. Additional research will be needed to define the timing and cultural requirements for successful shipping of vernalized, finished (rooted, robust growth) plugs for perennial CF flax cultivars.

Despite all the complications that arise with root research, such as slow, laborious, and unclear genetics, roots are a promising object of interest for breeders because many root traits are compatible with high yield potential. It is a great challenge for further research that there is a wide demand for information on the "hidden half of plant metabolism" from many research fields. We have summarized the main obstacles in root system research and sketched a solution for breeding in field conditions so that the result was more meaningful to the farmer. (i) The most important challenge in root research is linking the functional identification of root system properties with the aboveground parts. (ii) Field breeding is irreplaceable, and methods allowing the evaluation of roots under field conditions are indispensable. (iii) Low heritability of root system trait discourages breeders. However, root properties show broad genotypic variability, allowing the efficient use of these traits as selection criteria. (iv) The root traits are variable, and many fluctuate under the influence of environmental factors, which complicates efforts to define ideotypes and explains the different conclusions obtained by researchers from different environments. The breeding programs targeting the root system are sporadic even in a global context. This is a great reserve for breeding progress in the era of climate change, water scarcity, a possible shift to extensive farming systems, and in the era of environmental programs.

Modifying root systems by crop breeding has been attracting increasing attention as a potentially effective strategy to enhance the sustainability of agriculture by increasing soil organic matter (SOM) stocks and soil quality, whilst maintaining or even improving yields. We used the new soil‐crop model USSF (Uppsala model of Soil Structure and Function) to investigate the potential of this management strategy using winter wheat as a model crop. USSF combines a simple (generic) crop growth model with physics‐based descriptions of soil water flow, water uptake and transpiration by plants. It also includes a model of the interactions between soil structure dynamics and organic matter turnover that considers the effects of physical protection and microbial priming on the decomposition of SOM. The model was first calibrated against field data on soil water contents and both above‐ground and root biomass of winter wheat measured during one growing season in a clay soil in Uppsala, Sweden using the GLUE method to identify five 'acceptable' parameter sets. We created four model crops (ideotypes) by modifying root‐related parameters to mimic winter wheat phenotypes with improved root traits. Long‐term (30‐year) simulations of a conventionally tilled monoculture of winter wheat were then performed to evaluate the potential effects of cultivating these ideotypes on the soil water balance, soil organic matter stocks and grain yields. Our results showed that ideotypes with deeper root systems or root systems that are more effective for water uptake increased grain yields by 3% and SOM stocks in the soil profile by ca. 0.4%–0.5% in a 30‐year perspective (as an average of the five parameter sets). An ideotype in which below‐ground allocation of dry matter was increased at the expense of stem growth gave even larger increases in SOM stocks (ca. 1.4%). An ideotype combining all three modifications (deeper and more effective root systems and greater root production) showed even more promising results: compared with the baseline scenario, surface runoff decreased while yields were predicted to increase by ca. 7% and SOM stocks in the soil profile by ca. 2%, which is roughly equivalent to ca. 20% of the 4‐per‐mille target (https://4p1000.org/). [ABSTRACT FROM AUTHOR]

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This study evaluated 24 rice genotypes, including 22 pipeline varieties from the National Rice Research Program (NRRP) in Dhanusa and two checks, Bahaguni-2 and Sabitri. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was used as selection tool to rank genotypes based on their proximity to an ideal genotype. Broad-sense heritability (h²) estimates ranged from 0.03 for panicle length to 0.96 for days to 80% maturity, suggesting high potential for selection gains in days to 80% maturity (h² = 0.96) and plant height (h² = 0.91), while tiller number and grain yield showed low heritability (h² > 0.5). Variance analysis indicated substantial genetic control for plant height and days to 80% maturity, while panicle length and grain yield were more influenced by environmental factors. Principal component analysis revealed four factors explaining 76.5% of the trait variation, with FA1 (days to 50% flowering, days to 80% maturity) accounting for the most variation. Selection gains were assessed using MGIDI and FAI-BLUP indexes, with MGIDI achieving a 15.13% gain for targeted traits and FAI-BLUP yielding 1.25%. Selected genotypes from MGIDI included SVIN 127, SVIN 098, SVIN 643, SVIN 084, and IR 18F1085, with SVIN 127 and SVIN 098 also appearing in the FAIBLUP index, highlighting their potential value for breeding. This research demonstrates the effectiveness of both selection indexes in identifying superior genotypes for enhanced breeding efficiency. [ABSTRACT FROM AUTHOR]

Breeding activities for winged bean plants (Psophocarpus tetragonolobus (L.) DC.) necessitate genetic diversity from local varieties. Identifying winged bean lines adds valuable initial information for shaping policies in plant breeding. Before proceeding with varietal development, it is crucial to establish the ideal type (ideotype) for superior winged bean varieties. The primary objective of this research is to ascertain the idiotype for superior winged bean varieties. The research was conducted in 2023 at Universitas Brawijaya, Indonesia, and involves the evaluation of five improved lines. The initial evaluation focuses on qualitative and quantitative characteristics of ideotype. The second evaluation concerns winged bean seeds' ideal morphological and physiological qualities. The third evaluation assesses winged bean pods' ideal physical and organoleptic preferences. The research outcomes have yielded the ideal morphological characteristics for winged bean varieties. This idiotype will be the foundation for the direction and target of winged bean plant breeding efforts, among the lines evaluated. NSM2 exhibits ideal flowering time and pod length characteristics, and lines PTL and PTL display ideal pod forms. MML and PBL lines have flavors aligned with market preferences regarding organoleptic qualities. These lines will be further improved through crossing to develop ideal varieties.

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20–25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) stands as a important cereal sustaining over half of the world’s population. This study delves into the challenges confronting breeders in the realm of crop improvement, specifically focusing on the intricate task of designing an ideotype—a genotype amalgamating diverse attributes for optimal performance. Traditional methodologies, exemplified by the Smith–Hazel (SH) index, grapple with issues such as multicollinearity and the complexities of economic weighting decisions. In response to these challenges, the Multi-Trait Genotype–Ideotype Distance Index (MGIDI), conceptualized by Olivoto and Nardino (2021), emerges as a ground breaking approach. Principal Component Analysis (PCA) aids in the reduction of trait dimensionality, revealing four key factors that collectively contribute to 79.444% of total variability. The Scree plot guides factor selection, ensuring a targeted analysis. The MGIDI index computation yields a total genetic gain of 273.025%, with specific traits like spikelet fertility and seedling dry weight exhibiting significant gains. Six high-performing rice accessions—SM227, NLR33892, MTU3626, 239(3), SMB3, and 405C3 were identified through MGIDI. These identified genotypes serve as valuable resources for developing recombinant populations, aligning with sustainable and effective crop improvement strategies. Additionally, these promising varieties exhibit strengths across various traits, offering potential for simultaneous trait improvement in future breeding programmes. The efficiency of MGIDI is highlighted through its innovative application in simultaneous trait selection, underscoring its significance across a wide range of crops.

Wheat consumption represents a large part of human diet. The quality of wheat grains and derived products depends on the genotype and its interaction with the environment. This work aimed to identify the effects of different wheat genotypes grown in different environments, performing nutraceutical multitrait selection, seeking the wheat ideotype based on wheat quality indicators. In total, 16 wheat genotypes were evaluated in five environments, using two sowing times. The contents of proteins, lipids, fibers, mineral material, and carbohydrates were evaluated. The residual or restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) methodology was used to estimate variance components and genetic parameters. Moreover, the multi-trait genotype-ideotype distance index (MGIDI) was used to select the genotypes that demonstrated superiority. Except for the lipid content, high values of genotypic variance were identified. FPS Certero, ORS 1403, LG Prisma, and Tbio Iguaçú genotypes, conducted in São Gabriel and Cachoeira do Sul, met the sought ideotype during the first sowing time. FPS Certero, Tbio Tibagi, and LG Supra genotypes were superior when conducted in the Santo Augusto environment during the second sowing time.

Multiple abiotic stresses negatively impact wheat production all over the world. We need to increase productivity by 60% to provide food security to the world population of 9.6 billion by 2050; it is surely time to develop stress-tolerant genotypes with a thorough comprehension of the genetic basis and the plant's capacity to tolerate these stresses and complex environmental reactions. To approach these goals, we used multivariate analysis techniques, the additive main effects and multiplicative interaction (AMMI) model for prediction, linear discriminant analysis (LDA) to enhance the reliability of the classification, multi-trait genotype-ideotype distance index (MGIDI) to detect the ideotype, and the weighted average of absolute scores (WAASB) index to recognize genotypes with stability that are highly productive. Six tolerance multi-indices were used to test twenty wheat genotypes grown under multiple abiotic stresses. The AMMI model showed varying differences with performance indices, which disagreed with the trait and genotype differences used. The G01, G12, G16, and G02 were selected as the appropriate and stable genotypes using the MGIDI with the six tolerance multi-indices. The biplot features the genotypes (G01, G03, G11, G16, G17, G18, and G20) that were most stable and had high tolerance across the environments. The pooled analyses (LDA, MGIDI, and WAASB) showed genotype G01 as the most stable candidate. The genotype (G01) is considered a novel genetic resource for improving productivity and stabilizing wheat programs under multiple abiotic stresses. Hence, these techniques, if used in an integrated manner, strongly support the plant breeders in multi-environment trials. [ABSTRACT FROM AUTHOR]

Currently, sharp contradiction exists between edible oil supply and demand in China. Developing edible oil production largely depends on the development of rapeseed production. For less land competition between cereal crops and rapeseed, the Yangtze River Basin is the main rapeseed producing area in China. But, problems (such as a large amount of labor, high labor cost and low efficiency) seriously restrict the development of rapeseed industry. The whole-process mechanization (including sowing, management, and harvesting) is the key to boosting rapeseed production. Thus we reviewed the research on rapeseed biological characteristics, planting habits, and rotation systems, to focus on high yield loss rate during harvesting. We expected to improve mechanized harvesting of rapeseed in China. The research processes on breeding ideotype rapeseed suitable for mechanized harvesting as resistance to lodging, pod cracking, and sclerotinia disease were also discussed. The aim was to provide an insight on breeding and cultivation management of rapeseed suitable for high efficient mechanized harvesting. [ABSTRACT FROM AUTHOR]

Copyright of Forestry Chronicle is the property of Canadian Institute of Forestry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Shoot architecture refers to the three-dimensional body plan of the above ground organs of the plant. The patterning of this body plan results from the tight genetic control of the size and maintenance of meristems, the initiation of axillary growth, and the timing of developmental phase transition. Variation in shoot architecture can result in dramatic differences in plant productivity and/or grain yield due to their effects on light interception, photosynthetic efficiency, response to agronomic inputs, and environmental adaptation. The fine-tuning of shoot architecture has consequently been of great interest to plant breeders, driving the need for deeper understanding of the genes and molecular mechanisms governing these traits. In soybean, the world's most important oil and protein crop, major components of shoot architecture include stem growth habit, plant height, branch angle, branch number, leaf petiole angle, and the size and shape of leaves. Key genes underlying some of these traits have been identified to integrate hormonal, developmental, and environmental signals modulating the growth and orientation of shoot organs. Here we summarize the current knowledge and recent advances in the understanding of the genetic control of these important architectural traits in soybean. [ABSTRACT FROM AUTHOR]

Current study is devoted to the development of an ideotype of winter wheat variety for cultivation in the conditions of the South of Ukraine. The investigation is based on the results of regional ecological varietal testing, conducted in the Southern Steppe zone on the non-irrigated lands. Varietal traits, included in the study, embraced growing season duration, 1000 grains weight, plant height, and ear length. The results of the testing were further processed using statistical procedures of linear Pearson's correlation analysis and multiple regression analysis. As a result, the model of a winter wheat variety for the non-irrigated lands of the South of Ukraine was developed. The developed model is characterized by very high fitting quality (R² = 0.9476) and good prediction accuracy (MAPE = 23.27%). According to the model, the variety should be late ripening with moderate to high plant height to provide the highest grain yield. The trait of 1000 grains weight was found out to be unimportant. The main trait, providing for the grain yield increase, is growing season duration, which must be long enough. Further ecological varietal testing studies with inclusion of additional varietal traits, such as cold-resistance, drought-resistance, frost-resistance, tolerance to diseases, etc., are to be conducted to extend the ideotype of winter wheat. [ABSTRACT FROM AUTHOR]

Food crops are a vital source of nutrition for humans and domestic animals, with an estimated 4 billion metric tons of food produced per year. Crops do not only provide yields, but their traits also play a significant role in regulating the ecosystem processes of croplands, affecting local biotas, water balance, nutrient and carbon cycling. Domestication has led to significant changes in crop traits, making it important to understand the recent evolution of crops and how they differ from wild plants.In this paper I review the evidence on how the ecological traits of herbaceous crops have evolved during and after domestication. Loss of seed dispersal mechanisms, increased plant and organ sizes, high rates of consumption by herbivores and fast decomposition of residues by decomposer microbes in the soil, all have evolved independently in domestication processes of different crops.I also point out types of traits for which we have not identified common responses to domestication, be it because domestication processes of the different crop species are disparate, or because of lack of strong evidence. Those traits include resource acquisition rates of leaves and roots, and whole‐plant growth rates. Then, I discuss research gaps in the field, including how to advance knowledge for those traits that show apparently idiosyncratic responses to domestication.Finally, I emphasize the importance of understanding the interactions of crops with other organisms and the environment to breed crops that deliver yield and other services required from croplands. To this end, I introduce an ideotype for sustainable agriculture, which might inspire the breeding of multipurpose herbaceous crops, in the same way than the ideotypes of the Green Revolution inspired the breeding of elite varieties to foster yields under conventional agriculture. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

The shade avoidance syndrome (SAS) in soybean can have destructive effects on yield, as essential carbon resources reserved for yield are diverted to the petiole and stem for exaggerated elongation, resulting in lodging and susceptibility to disease. Despite numerous attempts to reduce the unfavorable impacts of SAS for the development of cultivars suitable for high-density planting or intercropping, the genetic bases and fundamental mechanisms of SAS remain largely unclear. The extensive research conducted in the model plant Arabidopsis provides a framework for understanding the SAS in soybean. Nevertheless, recent investigations suggest that the knowledge obtained from model Arabidopsis may not be applicable to all processes in soybean. Consequently, further efforts are required to identify the genetic regulators of SAS in soybean for molecular breeding of high-yield cultivars suitable for density farming. In this review, we present an overview of the recent developments in SAS studies in soybean and suggest an ideal planting architecture for shade-tolerant soybean intended for high-yield breeding. [ABSTRACT FROM AUTHOR]

To address the global demand for rapeseed while considering farmers’ profit, we face the challenges of making a quantum leap in seed yield and, at the same time, reducing yield loss due to biotic and abiotic stresses. We also face the challenge of efficiently applying new transformative biotechnology tools such as gene editing and breeding by genome design to increase rapeseed productivity and profitability. In this Perspective, we review advances in research on the physiological and genetic bases of both stress factors-affected yield stability and seed yield potential, focusing on source–sink relationships and allocation of photosynthetic assimilates to vegetative growth and seed development. We propose research directions and highlight the role of plant architecture in the relative contributions of the root system, leaves, and pods to seed yield. We call for de novo design of new rapeseed crops. We review trait variation in existing germplasm and biotechnologies available for crop design. Finally, we discuss opportunities to apply fundamental knowledge and key germplasm to rapeseed production and propose an ideotype for de novo design of future rapeseed cultivars.

Abstract The objective of this work was to select white oat (Avena sativa) genotypes for environments with and without fungicide application, as well as to identify relationships between meteorological variables and agronomic traits. Two experiments were carried out: one without and the other with the use of the tebuconazole fungicide. In each experiment, 26 genotypes were evaluated, conducted during ten years in the same experimental area; cultivation years were considered as one environment. The methodologies of genotype and of the genotypes x environments interaction were used to define the ideal genotype. 'URS Corona' is considered an ideal genotype due to its excellent responses in the environment with tebuconazole. The 'Brisasul', 'IPR Aphrodite', and 'URS Taura' genotypes respond better in the environment without the fungicide. However, based on multitraits, the 'URS Taura' and 'IPR Afrodite' genotypes can be positioned in environments with or without the use of tebuconazole. Genotypes with a rust incidence lower than 15% and a height higher than 93 cm in an environment with a relative humidity lower than 70.75% have a higher grain yield regardless of fungicide use. Greater magnitudes of air temperature and solar radiation result in a higher grain yield of white oat, regardless of fungicide use.

Multiple abiotic stresses negatively impact wheat production all over the world. We need to increase productivity by 60% to provide food security to the world population of 9.6 billion by 2050; it is surely time to develop stress-tolerant genotypes with a thorough comprehension of the genetic basis and the plant’s capacity to tolerate these stresses and complex environmental reactions. To approach these goals, we used multivariate analysis techniques, the additive main effects and multiplicative interaction (AMMI) model for prediction, linear discriminant analysis (LDA) to enhance the reliability of the classification, multi-trait genotype-ideotype distance index (MGIDI) to detect the ideotype, and the weighted average of absolute scores (WAASB) index to recognize genotypes with stability that are highly productive. Six tolerance multi-indices were used to test twenty wheat genotypes grown under multiple abiotic stresses. The AMMI model showed varying differences with performance indices, which disagreed with the trait and genotype differences used. The G01, G12, G16, and G02 were selected as the appropriate and stable genotypes using the MGIDI with the six tolerance multi-indices. The biplot features the genotypes (G01, G03, G11, G16, G17, G18, and G20) that were most stable and had high tolerance across the environments. The pooled analyses (LDA, MGIDI, and WAASB) showed genotype G01 as the most stable candidate. The genotype (G01) is considered a novel genetic resource for improving productivity and stabilizing wheat programs under multiple abiotic stresses. Hence, these techniques, if used in an integrated manner, strongly support the plant breeders in multi-environment trials.

Both from the environmental and economical perspective, reducing the use of mineral nitrogen and herbicides is one of the future challenges in cereal production. Growing winter cereals on perennial legume living mulch such as white clover (Trifolium repens L.) or lucerne (Medicago sativa L.) is one of several options to reduce the need for mineral nitrogen fertilizer and herbicides in winter cereal production. Given the importance of winter cereals in the world, adopting this technique could greatly improve the sustainability of crop production. Through competition with the crop however, the living mulch can negatively affect cereal yield. Here, we (i) review how living mulch can be introduced in the system, (ii) synthetize potential advantages and disadvantages of that system, and (iii) explore different strategies to control the competition between the crop and living mulch. The major findings are that (i) competition between cereals and mulch can lead to significant yield reductions if not controlled properly and (ii) perennial legume varieties used as living mulch so far are varieties bred for forage production. We hypothesize that a dedicated breeding program might lead to living mulch varieties with a smaller impact on cereal yield compared to forage varieties, allowing to grow cereals with reduced nitrogen and herbicide inputs. We propose the main characteristics of an ideotype for such a perennial legume variety. [ABSTRACT FROM AUTHOR]

A field experiment for the AD268 with large leaf and dwarf structure and the XY335 with small leaf and high structure at three planting densities of low (3 plants·m-2), medium (6 plants·m-2) and high (9 plants·m-2) was conducted. This study integrated the vertical distribution of canopy photosynthetically active radiation (PAR), a 3D canopy model, and a canopy photosynthesis model to analyze responses of the extinction coefficients estimated by the logarithmic approach (klog) and the regression approach (knls) to cultivar and density and their differences, and to evaluate the effects on simulating canopy light utilization. The results showed that there was a difference between klog and knls, and this difference was more obvious for AD268 and aggravated with increasing density. The fitness based on knls for canopy light distribution (R2=0.86) was better than klog (R2=0.77). The daily CO2 assimilation, above-ground dry matter accumulation and radiation use efficiency of AD268 simulated by klog and knls did not differ significantly at low densities, but the difference became larger with increasing density. The critical densities at which the difference become larger were 0.7-2.5plants·m-2. [ABSTRACT FROM AUTHOR]

Rye is the only cross-pollinating small-grain cereal. The unique reproduction biology results in an exceptional complexity concerning genetic improvement of rye by breeding. Rye is a close relative of wheat and has a strong adaptation potential that refers to its mating system, making this overlooked cereal readily adjustable to a changing environment. Rye breeding addresses the emerging challenges of food security associated with climate change. The systematic identification, management, and use of its valuable natural diversity became a feasible option in outbreeding rye only following the establishment of hybrid breeding late in the 20th century. In this article, we review the most recent technological advances to improve yield and yield stability in winter rye. Based on recently released reference genome sequences, SMART breeding approaches are described to counterbalance undesired linkage drag effects of major restorer genes on grain yield. We present the development of gibberellin-sensitive semidwarf hybrids as a novel plant breeding innovation based on an approach that is different from current methods of increasing productivity in rye and wheat. Breeding of new rye cultivars with improved performance and resilience is indispensable for a renaissance of this healthy minor cereal as a homogeneous commodity with cultural relevance in Europe that allows for comparatively smooth but substantial complementation of wheat with rye-based diets, supporting the necessary restoration of the balance between human action and nature. [ABSTRACT FROM AUTHOR]

Abstract Sorghum currently contributes to the species portfolio that is supporting bioenergy production including anaerobic digestion. Although agro‐morphological ideotypes maximizing biogas production have been recently proposed, there is a crucial need to refine our understanding of the impacts of the stem composition and structure on this processing trait in order to ensure genetic gains in the mid to long terms. This study aims to assess the potential of Sorghum bicolor ssp bicolor stem genetic diversity to maximize genetic gains for biogas production and define a biogas stem ideotype. In this context, a panel of 57 genotypes, encompassing most of the stem composition variability available in cultivated sorghum, was characterized over five sites. Simultaneous histological and biochemical characterizations were performed. A high broad sense heritability associated with a moderate genetic variability was detected for stem biogas potential ensuring significant genetic gains in the future. In addition, the development of a stem histological phenotyping pipeline made it possible to describe the genetic diversity available for the internode anatomy and the repartition of key cell wall components. Consistently with previous studies, moderate to high heritability was observed for stem biochemical components. Genetic correlation, hierarchical clustering, and multiple stepwise regression analyses identified soluble sugar content as the first main driver of biogas potential genetic variability. Nevertheless, breeding programs should anticipate that biogas yield improvement will also rely on the monitoring of the cell wall components and their distribution in the stem jointly with the soluble sugar content. According to the assets of sorghum in terms of adaptation to environmental stresses and the present results regarding the identification of stem ideotypes suitable for different value chains, this species will surely play a key role to optimize the economic and environmental sustainability of the agrosystems that are currently facing the effects of climate change.

Why are legume crops rare in Europe even though they grow well there? This opinion paper brings together concepts from crop physiology, classical economics and sociotechnical theory to address this question. It argues for increased focus on research and innovation on crop performance. The starting point is that trade policy no longer explains the marginalisation of legumes. A more recent premise that mutually supporting social, technical and agricultural factors have combined over time to establish and maintain the current cropping systems is also incomplete. However, these propositions have led to significant investment in research on niche value chains in the hope that these will combine within transition pathways to break through system incumbency that "locks out" legumes. It is argued here that this approach is incomplete for crops because the scaling up and agglomeration of niche processing and marketing activities does not improve the fundamental crop resource capture and conversion processes in the field upon which farm productivity depends. Reconsideration of some economic and crop physiological basics is required. Farmers aim to make rational decisions and to focus on what they do best. The principles behind international trade described in the 19th century and the fundamental biophysical crop‐level processes that were elucidated in the 1960s together explain the cropping choices many European farmers make. We need more focus on raising the on‐farm performance and competitiveness of the legume crops themselves and the farming systems in which they are grown. Efficient, productive legume crops are important also if we are to avoid a trade‐off between environmental gains in Europe and disbenefits elsewhere because of effects on global trade. [ABSTRACT FROM AUTHOR]

The creation of green areas within urban centers was born as a response to profoundly different problems, such as the demographic increase and the progressive urbanization of landscapes. Moreover, up to date, the genetics of plants has not been considered for urban contexts. The purpose of this review is to discuss the state of the art and the advantages in planning genetic improvement for plants for urban destinations, also providing technical information, that may contribute in a concrete way. Firstly, recent genomic sources and their potential contribution to breeding programs are discussed. Then, dividing the urban scenarios into four macro areas (i.e., urban/metropolitan parks, urban gardens, road verges and roofs/terraces/balconies), we described the role of genetics in the adaptability and sustainability of plants in these different contexts. In addition, we analyzed the genetic traits plants need to provide services for a city environment and population (e.g., pollution reduction, biodiversity conservation, soil stability, and food production). [ABSTRACT FROM AUTHOR]

Climate change (CC) is already impacting Arabica coffee cultivation in the intertropical zone. To deal with this situation, it is no longer possible to manage this crop using industrial agriculture techniques, which has been the main strategy implemented since the Green Revolution. Developing a more sustainable agriculture system that respects people and the environment is essential to guarantee future generations' access to natural resources. In the case of Arabica coffee, the solution has been found. Agroforestry is proposed as an ecosystem-based strategy to mitigate and adapt to CC. At least 60% of Arabica coffee is produced in agroforestry systems (AFSs), which are the most sustainable way to produce coffee. Nevertheless, AFS coffee cultivation is currently uncompetitive partly because all modern varieties, selected for full-sun intensive cropping systems, have low yields in shaded environments. Here we review the reasons why agroforestry is part of the solution to CC, and why no breeding work has been undertaken for this cropping system. Based on the literature data, for breeding purposes we also define for the first time one possible coffee ideotype required for AFS coffee cultivation. The four main traits are: (1) productivity based on F1 hybrid vigor, tree volume and flowering intensity under shade; (2) beverage quality by using wild Ethiopian accessions as female progenitors and selecting for this criterion using specific biochemical and molecular predictors; (3) plant health to ensure good tolerance to stress, especially biotic; and (4) low fertilization to promote sustainable production. For each of these traits, numerous criteria with threshold values to be achieved per trait were identified. Through this research, an ecosystem-based breeding strategy was defined to help create new F1 hybrid varieties within the next 10 years. [ABSTRACT FROM AUTHOR]

Over the past few years, rapeseed yields have been considerably lower than those of cereal crops, and progress has been slow due to its limitations for genetic improvement. Here, we propose a comprehensive strategy to consider the interactions between genetics, management practices, and environment, concentrating on using ideotype and heterosis to maximize yield. [ABSTRACT FROM AUTHOR]

Crop models are powerful tools to support breeding because of their capability to explore genotype × environment×management interactions that can help design promising plant types under climate change. However, relationships between plant traits and model parameters are often model specific and not necessarily direct, depending on how models formulate plant morphological and physiological features. This hinders model application in plant breeding. We developed a novel trait‐based multi‐model ensemble approach to improve the design of rice plant types for future climate projections. We conducted multi‐model simulations targeting enhanced productivity, and aggregated results into model‐ensemble sets of phenotypic traits as defined by breeders rather than by model parameters. This allowed to overcome the limitations due to ambiguities in trait‐parameter mapping from single modelling approaches. Breeders' knowledge and perspective were integrated to provide clear mapping from designed plant types to breeding traits. Nine crop models from the AgMIP‐Rice Project and sensitivity analysis techniques were used to explore trait responses under different climate and management scenarios at four sites. The method demonstrated the potential of yield improvement that ranged from 15.8% to 41.5% compared to the current cultivars under mid‐century climate projections. These results highlight the primary role of phenological traits to improve crop adaptation to climate change, as well as traits involved with canopy development and structure. The variability of plant types derived with different models supported model ensembles to handle related uncertainty. Nevertheless, the models agreed in capturing the effect of the heterogeneity in climate conditions across sites on key traits, highlighting the need for context‐specific breeding programmes to improve crop adaptation to climate change. Although further improvement is needed for crop models to fully support breeding programmes, a trait‐based ensemble approach represents a major step towards the integration of crop modelling and breeding to address climate change challenges and develop adaptation options. [ABSTRACT FROM AUTHOR]

Pea or Pisum sativum L. is a key diversification crop, but current varieties are not very competitive against weeds. The objective was to identify, depending on the type of cropping system and weed flora, (1) the key pea parameters that drive crop production, weed control and weed contribution to biodiversity, (2) optimal combinations of pea-parameter values and crop-management techniques to maximize these goals. For this, virtual experiments were run, using FLORSYS, a mechanistic simulation model. This individual-based 3D model simulates daily crop-weed seed and plant dynamics over the years, from the cropping system and pedoclimate. Here, this model was parameterized for seven pea varieties, from experiments and literature. Moreover, ten virtual varieties were created by randomly combining variety-parameter values according to a Latin Hypercube Sampling (LHS) plan, respecting parameter ranges and correlations observed in the actual varieties. A global sensitivity analysis was run, using another LHS plan to combine pea varieties, crop rotations and management techniques in nine contrasting situations (e.g., conventional vs. organic, no-till, type of weed flora). Simulated data were analyzed with classification and regression trees (CART). We highlighted (1) Parameters that drive potential yield and competitivity against weeds (notably the ability to increase plant height and leaf area in shaded situations), depending on variety type (spring vs. winter) and cropping system. These are pointers for breeding varieties to regulate weeds by biological interactions; (2) Rules to guide farmers to choose the best pea variety, depending on the production goal and the cropping system; (3) The trade-off between increasing yield potential and minimizing yield losses due to weeds when choosing pea variety and management, especially in winter peas. The main pea-variety rules were the same for all performance goals, management strategies, and analyses scales, but further rules were useful for individual goals, strategies, and scales. Some variety features only fitted to particular systems (e.g., delayed pea emergence is only beneficial in case of herbicide-spraying and disastrous in unsprayed systems). Fewer variety rules should be compensated by more management rules. If one of the two main weed-control levers, herbicide or tillage, was eliminated, further pea-variety and/or management rules were needed. [ABSTRACT FROM AUTHOR]

Abstract Identification of traits strongly associated with high yield can help future gene engineering towards improvements of productivity. Here we systematically determine the major architectural and physiological features associated with high yield in two elite historical hybrid rice cultivars, i.e., YLY1 and LYP9. Data from a six-year experiment show that high yield of YLY1 are related to a number of architectural and physiological parameters. Compared to LYP9, YLY1 had 5.5% and 47.3% higher canopy photosynthesis under high and low photosynthetic photon flux densities, respectively, during the grain filling stage, an average 1.5% higher proportion of biomass allocation to above-ground tissues, a 4.5%–10.5% higher photosynthate reserve in leaf sheath before grain filling, and a more efficient photosynthate translocation during grain filling and finally an average 25.2% higher number of productive tillers. These features differ dramatically from features associated with high yield in YLY900 and Yongyou12#, two other high-yielding rice cultivars in China. These identified features and their combinations can support designing new strategies in the future high-yield rice breeding.

Pea or Pisum sativum L. is a key diversification crop, but current varieties are not very competitive against weeds. The objective was to identify, depending on the type of cropping system and weed flora, (1) the key pea parameters that drive crop production, weed control and weed contribution to biodiversity, (2) optimal combinations of pea-parameter values and crop-management techniques to maximize these goals. For this, virtual experiments were run, using FLORSYS, a mechanistic simulation model. This individual-based 3D model simulates daily crop-weed seed and plant dynamics over the years, from the cropping system and pedoclimate. Here, this model was parameterized for seven pea varieties, from experiments and literature. Moreover, ten virtual varieties were created by randomly combining variety-parameter values according to a Latin Hypercube Sampling (LHS) plan, respecting parameter ranges and correlations observed in the actual varieties. A global sensitivity analysis was run, using another LHS plan to combine pea varieties, crop rotations and management techniques in nine contrasting situations (e.g., conventional vs. organic, no-till, type of weed flora). Simulated data were analyzed with classification and regression trees (CART). We highlighted (1) Parameters that drive potential yield and competitivity against weeds (notably the ability to increase plant height and leaf area in shaded situations), depending on variety type (spring vs. winter) and cropping system. These are pointers for breeding varieties to regulate weeds by biological interactions; (2) Rules to guide farmers to choose the best pea variety, depending on the production goal and the cropping system; (3) The trade-off between increasing yield potential and minimizing yield losses due to weeds when choosing pea variety and management, especially in winter peas. The main pea-variety rules were the same for all performance goals, management strategies, and analyses scales, but further rules were useful for individual goals, strategies, and scales. Some variety features only fitted to particular systems (e.g., delayed pea emergence is only beneficial in case of herbicide-spraying and disastrous in unsprayed systems). Fewer variety rules should be compensated by more management rules. If one of the two main weed-control levers, herbicide or tillage, was eliminated, further pea-variety and/or management rules were needed.

Sustaining irrigated corn (Zea mays L.) production under changing climate and reduced irrigation water availability presents a key challenge for producers in the Northern High Plains (NHP) of Texas. We assessed climate change impacts on corn production at Bushland in the NHP region using the CERES-Maize model under 36 future climate scenarios. These scenarios included nine global climate models (GCMs), two representative concentration pathways (RCPs) 4.5 and 8.5, and two future time periods 2050s (2036–2065) and 2080s (2066–2095). Simulated grain corn yield decreased, under all scenarios in the future, by approximately 31 % on average in the 2050s and by approximately 55 % in the 2080s, under RCP 8.5, mainly due to reduced unit grain weight and biomass, and shorter crop cycle. Seasonal irrigation water use was simulated to either increase or decrease in the future depending on the rainfall projection of a GCM. Adaptation strategies considered in this study included using ideotypes with a longer maturity, higher yield potential, and greater heat tolerance than the reference cultivar, and shifting of planting dates. The ideotypes were created by modifying thermal times from emergence to end-of-juvenile phase, thermal time from silking to maturity, maximum kernel number per plant, radiation use efficiency (RUE), and optimum and failure temperature thresholds during relative grain filling. The planting dates considered were 16 April, 1 May, 16 May (reference), 1 June, and 16 June. By increasing the reproductive period by 13 days, grain yield could increase by 40 %, but that could increase seasonal irrigation water requirement by 10 %. Grain corn yield increased by 13 % on average when the maximum number of kernels per plant or RUE were increased by 15 %, with minor changes in seasonal irrigation water requirement. Heat tolerant ideotypes showed yield advantage over the reference cultivar without much change in irrigation. Delayed planting increased grain yield in the future. Overall, grain yield could decline under climate change without adaptation. Ideotypes with greater silking to maturity period, potential number of kernels per plant, RUE, and heat tolerance during grain filling, showed yield benefits in the future.

Cultivar recommendation is crucial for achieving high and stable yields, and it can be successfully supported by crop models because of their capability of exploring genotype × environment × management interactions. Different modelling approaches have been developed to this end, mostly relying on dedicated field trials to characterize the germplasm of interest. Here, we show how even data routinely collected in operational contexts can be used for model-based cultivar recommendation, with a case study on phenological traits and field pea (Pisum sativum L.). Eight hundred and four datasets including days from sowing to plant emergence, first flower, and maturity were collected in Northern Italy from 2017 to 2020 and they were used to optimize six parameters (base, optimum, and maximum temperature for development, growing degree days to reach emergence, flowering and maturity) of the crop model WOFOST-GT2 for 13 cultivars. This allowed obtaining the phenotypic profiles for these cultivars at functional traits level, without the need of carrying out dedicated phenotypizations. Sensitivity analysis (SA) techniques (E-FAST) and the statistical distributions of the optimized parameters were used to design pea ideotypes able to maximize yields and yield stability in 24 agro-climatic contexts (three soil conditions × two sowing times × four agro-climatic classes). For each of these contexts, the 13 cultivars were ranked according to their similarity to the ideotype based on the weighted Euclidean distance. Results of SA identified growing degree days to reach flowering as the trait mainly affecting crop productivity, although cardinal temperatures also played a role, especially in case of early sowings. This reflected in the ideotypes and, therefore, in cultivar ranking, leading to recommend a panel of cultivars characterized by low base temperature and high thermal requirements to reach flowering. Despite the limits of the study, which is focused only on phenological traits, it represents an extension of available approaches for model-aided cultivar recommendation, given the methodology we propose is able to take full advantage of the potentialities of crop models without requiring dedicated experiments aimed at profiling the germplasm of interest at the level of functional traits.

Mechanical impedance constrains root growth in most soils. Crop cultivation changed the impedance characteristics of native soils, through topsoil erosion, loss of organic matter, disruption of soil structure and loss of biopores. Increasing adoption of Conservation Agriculture in high‐input agroecosystems is returning cultivated soils to the soil impedance characteristics of native soils, but in the low‐input agroecosystems characteristic of developing nations, ongoing soil degradation is generating more challenging environments for root growth. We propose that root phenotypes have evolved to adapt to the altered impedance characteristics of cultivated soil during crop domestication. The diverging trajectories of soils under Conservation Agriculture and low‐input agroecosystems have implications for strategies to develop crops to meet global needs under climate change. We present several root ideotypes as breeding targets under the impedance regimes of both high‐input and low‐input agroecosystems, as well as a set of root phenotypes that should be useful in both scenarios. We argue that a 'whole plant in whole soil' perspective will be useful in guiding the development of future crops for future soils. SUMMARY STATEMENT: Root phenotypes can be selected to optimize crop performance in response to mechanical impedance in agricultural soils. [ABSTRACT FROM AUTHOR]

Soybean (Glycine max (L.) Merr.) may contribute to the agro-ecological transition of cropping systems in Europe, but its productivity is severely affected by summer drought. The crop is mainly grown in southern and continental parts of Europe, whereby increasing drought and heat waves are expected in the near future. Agronomic strategies, such as early sowing, require cultivars with enhanced early plant growth traits under suboptimal conditions. Moreover, efficient water uptake by root delays dehydration and promotes drought avoidance. In general, changes in root morphology and root architecture are important pathways for plant adaptation to water stress conditions. This paper reviews the cultivar differences in soybean for root morphological and architectural traits especially during early growth stage. Previous works reported cultivar differences for root traits in soybean but they did not deal with cultivars commonly grown in Europe on which little information is available to date. Genotypic differences in available early-stage root traits can be used as a framework to design soybean ideotypes less vulnerable to drought. To this aim, high-throughput phenotyping supported by digital methods and crop modelling offer new avenues for the exploration of target root traits involved in drought avoidance. [ABSTRACT FROM AUTHOR]

Cultivar recommendation is crucial for achieving high and stable yields, and crop models can successfully support it because of their capability of exploring genotype x environment x management interactions. Different modelling approaches have been developed to this end, primarily relying on dedicated field trials to characterize the germplasm of interest. Here, we show how even data routinely collected in operational contexts can be used for model-based cultivar recommendation, with a case study on phenological traits and field pea (Pisum sativum L.). Eight hundred and four datasets, including days from sowing to plant emergence, first flower, and maturity, were collected in Northern Italy from 2017 to 2020, and they were used to optimise six parameters (base, optimum, and maximum temperature for development, growing degree days to reach emergence, flowering, and maturity) of the crop model WOFOST-GT2 for 13 cultivars. This allowed obtaining the phenotypic profiles for these cultivars at the level of the functional trait, without the need of carrying out dedicated phenotypisations. Sensitivity analysis (SA) techniques (E-FAST) and the statistical distributions of the optimised parameters were used to design pea ideotypes able to maximise yields and yield stability in 24 agro-climatic contexts (three soil conditions x two sowing times x four agro-climatic classes). For each context, the 13 cultivars were ranked according to their similarity to the ideotype based on the weighted Euclidean distance. Results of SA identified growing degree days to reach flowering as the trait mainly affecting crop productivity, although cardinal temperatures also played a role, especially in the case of early sowings. This is reflected in the ideotypes and, therefore, in cultivar ranking, leading to recommend a panel of cultivars characterised by low base temperature and high thermal requirements to reach flowering. Despite the limits of the study, which is focused only on phenological traits, it represents an extension of available approaches for model-aided cultivar recommendation, given that the methodology we propose can take full advantage of the potentialities of crop models without requiring dedicated experiments aimed at profiling the germplasm of interest at the level of functional traits. [ABSTRACT FROM AUTHOR]

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Using classical breeding, plant breeders envision a plant type whose yield they aim to enhance by selecting for individual traits to create model/ideal plants or ideotypes. The experiment was carried out as a randomized complete blocks design with four replications and 15 local rice cultivars, required were collected for using path coefficient analysis and mahalanobis distance analysis. The results revealed that the higher positive effect on paddy yield was determined by panicle weight and number of spikelet per panicle. The higher negative effect on paddy yield was determined by DFM and FT. The highest genetic distance was observed between cv. 'Langroudi' and cv. 'Tarom Hashemi' and the least one was between cv. 'Gharib Reihani' and 'Ahlami Tarom'. Totally, all local cultivars were close to each other in terms of the genetic distance. This result shows that ideotype, this ideotype yield gap can be compensated. According to the findings, the high level of paddy-yield changes and contribution of each factor affecting it shows that with proper management, a significant part of this change can be compensated and lead to potential yield. [ABSTRACT FROM AUTHOR]