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Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h in vitro neutral detergent fiber digestibility in stems. Phenotypic traits of stem color, presence of stem pith cells, winter standability, and winter injury were modeled using univariate and multivariate spatial mixed linear models (MLM), and the predicted values were used as response variables in genome-wide association studies (GWAS). The alfalfa panel was genotyped using a 3K DArTag SNP markers for the evaluation of the genetic structure and GWAS. Principal component and population structure analyses revealed differentiations between populations selected for high- and low-digestibility. Thirteen molecular markers were significantly associated with stem traits using either univariate or multivariate MLM. Additionally, support vector machine (SVM) and random forest (RF) algorithms were implemented to determine marker importance scores for stem traits and validate the GWAS results. The top-ranked markers from SVM and RF aligned with GWAS findings for solid stem pith, winter standability, and winter injury. Additionally, SVM identified additional markers with high variable importance for solid stem pith and winter injury. Most molecular markers were located in coding regions. These markers can facilitate marker-assisted selection to expedite breeding programs to increase winter hardiness or stem palatability.

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Phenotypic plasticity (PP) is the ability of an organism to produce multiple phenotypes in response to environmental changes. In cultivated species, such as maize (Zea mays L.), the PP of plant architecture traits will play an important role in the adaptation of genotypes to unpredictable scenarios given by climate change, marginal areas, and seeding with variable plant density (D). We bring information to improve the understanding of the environmental modulation of PPs of plant architecture traits of maize, untangling their genetic bases, and testing the hypothesis of independent genetic control of the traits per se and their PPs. The PP of traits related to leaf area, spatial distribution of leaf area and stem architecture [(leaf area, maximum leaf width, maximum leaf length (LL), leaf orientation value, vertical leaf angle, leaf length to the flagging point (LF), LF/LL relationship (LFLL), azimuthal leaf orientation, ear height (EH), plant eight (PH), EH/PH relatioship (EHPH) and stem diameter] were estimated using 160 RILs from the IBM B73 × Mo17 Syn4 population, cultivated under two contrasting D (5 and 10 pl m−2) during two growing seasons that determined different environmental conditions. Data were phenotypically analyzed and quantitative traits loci (QTLs) were mapped. For leaf area and stem architecture related traits, high mean values of traits per se were related with high PPs values at low intraspecific competition while low mean values were observed at high intraspecific competition. The opposite response was found on leaf orientation related traits, with the exception of AZ. Forty-eight QTLs were detected for PP of plant architecture related traits on all chromosomes with exception of chromosome 7. There was no phenotypic correlation and no co-located QTLs for traits per se and their PPs. This independent genetic control for traits per se and their PPs would allow breeders to develop genotypes adapted to specific environments selecting for high or low PP in combination with high or low values for relevant agronomic traits. [ABSTRACT FROM AUTHOR]

Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h in vitro neutral detergent fiber digestibility in stems. Phenotypic traits of stem color, presence of stem pith cells, winter standability, and winter injury were modeled using univariate and multivariate spatial mixed linear models (MLM), and the predicted values were used as response variables in genome-wide association studies (GWAS). The alfalfa panel was genotyped using a 3K DArTag SNP markers for the evaluation of the genetic structure and GWAS. Principal component and population structure analyses revealed differentiations between populations selected for high- and low-digestibility. Thirteen molecular markers were significantly associated with stem traits using either univariate or multivariate MLM. Additionally, support vector machine (SVM) and random forest (RF) algorithms were implemented to determine marker importance scores for stem traits and validate the GWAS results. The top-ranked markers from SVM and RF aligned with GWAS findings for solid stem pith, winter standability, and winter injury. Additionally, SVM identified additional markers with high variable importance for solid stem pith and winter injury. Most molecular markers were located in coding regions. These markers can facilitate marker-assisted selection to expedite breeding programs to increase winter hardiness or stem palatability., Competing 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 © 2024 Medina, Heuschele, Zhao, Lin, Beil, Sheehan and Xu.)

Irrigation practices are important agronomic measures that influence maize yield and lodging resistance. However, the impact of irrigation practices on the spatial distribution of maize roots and stem traits, as well as their interaction with nitrogen application, remains unclear. This study examined the combined and single-factor effects of irrigation and nitrogen fertilizer on the root distribution, stem traits, and grain yield of different lodging-resistant maize hybrids. Three irrigation practices, drip irrigation (DI), flood irrigation (FI), and rainfed (RF), along with three nitrogen application rates, 0 (N0), 180 (N180), and 360 kg hm–1 (N360), were employed. Irrigation and nitrogen optimized maize root distribution, leaf productivity, and grain biomass allocation, leading to increased maize yield. Irrigation and nitrogen increased root length density (RLD) and the proportion of coarse root length (CRP). Compared with FI and RF, DI enlarged the difference in RLD among nitrogen application rates. N180 and N360 did not differ in RLD regardless of irrigation practice except in interplant. The difference in RLD of interplant across treatments was smaller than that of interrow, especially at the 20–60 cm soil depth. Irrigation and nitrogen increased dry matter accumulation and yield by increasing leaf area and chlorophyll content. However, excessive nitrogen reduced the remobilization of nitrogen and dry matter to the grains. DI and FI increased grain yield by 70.9 % and 55.0 % in ZD958, and by 33.8 % and 20.3 % in FM985 regardless of nitrogen application rate, respectively, compared to RF. Consequently, the combination of DI and N180 significantly increased RLD, stem puncture strength, dry matter accumulation, and yield of maize. Moreover, root length at different soil layers was closely related to yield, while the proportion of coarse roots at the surface layer contributing the most to yield. [Display omitted] • Drip irrigation boosts maize yield and lodging resistance by shaping root architecture. • Coarse root proportion in the surface layer contributes more greatly to maize yield. • Fine root extend the foraging range in deep soil layer with lower metabolic costs. • Root length plays an important role in maize yield across soil layers. [ABSTRACT FROM AUTHOR]

Functional traits are critical indicators for assessing and predicting plant environmental adaptations and survival strategies. However, less attention has been paid to root functional traits due to the costly and destructive nature of field excavations. This has resulted in a poor understanding of organ trait associations and vegetation survival strategies, particularly for plants in arid environments. In this study, we investigated 11 classical plant functional traits (leaf, stem, and root) and the intact root systems of three dominant coexisting shrubs, Calligonum mongolicum , Nitraria sphaerocarpa , and Haloxylon ammodendron , in a typical oasis–desert ecotone in northwestern China. These three coexisting shrubs generally converge on conservative resource strategies with dimorphic root systems and small leaf mass fractions to cope with strong habitat filtering and survive in arid environments. However, we found significant interspecific divergences in functional traits. Specifically, C. mongolicum had the most conserved traits, the medium root depth (370 cm), and the highest root-shoot ratio (1.72). H. ammodendron had relatively conserved traits, with the most extensive root depth (420 cm, access to groundwater) and the lowest root–shoot ratio (0.45). N. sphaerocarpa had the least conservative traits, the shallowest root depth (200 cm), and the medium root–shoot ratio (1.14). These divergences promote ecological niche segregation and ensure the stable coexistence of shrubs in this resource-limited environment. In contrast to the whole-plant economics spectrum, there was limited coordination between aboveground and belowground functional traits across the three species. Therefore, it is speculated that the different organs of these three species may operate independently to manage different constraints. The deep-rooted H. ammodendron is highly dependent on groundwater; therefore, planting them extensively in the ecotone may increase local groundwater consumption, resulting in the severe degradation of these species, particularly in the context of consecutive oasis expansion and intensified climate change. These results are expected to contribute to the development of effective ecosystem restoration and afforestation practices in such oasis–desert ecotones. [Display omitted] • Three coexisting shrub species converge on conservative resource strategies. • Interspecific trait divergences are beneficial to compete for water resources. • There is limited coordination between above- and belowground traits across species. • All three shrubs take advantage of their dimorphic root systems for water uptake. • Afforested shrubs may experience more severe degradation in the future. [ABSTRACT FROM AUTHOR]

Dead wood is a source of life as it provides habitat and substrate for a wide range of fungal species. A growing number of studies show an important role of wood quality for fungal diversity, but in most cases for a limited number of wood traits or tree species. In this study, we evaluate how abiotic and biotic factors affect the fungal diversity and composition during dead wood decomposition. For ten common European tree species, fresh similar‐sized logs were incubated simultaneously in two Dutch forests. Annual surveys of fungal fruiting bodies were made for an 8‐year period. For each tree species, 20 fresh stem traits were measured that are important for chemical and physical defence and for nutritional quality. Throughout eight years, 4644 fruiting bodies belonging to 255 species and 90 genera were recorded on the logs of ten tree species. Fungal frequency and richness were higher for Angiosperms than for Gymnosperms, both for individual tree species and as a group, and higher for tree species with more acquisitive stem trait strategies (i.e. high nutritional value and low physical defence). Differences in fungal communities were strongly driven by phylogenetic group (Gymnosperms versus Angiosperms), stem traits, decay time and forest sites, together explaining 23% of the variation. Fungal communities in sandy site diverged early in the decay process but converged later because of substrate homogenization. Of the 128 fungal species included in the analyses, 41% showed a preference for specific tree species and 34% for a specific successional year. In conclusion, dead wood quality, determined by tree species and decay stage, is an important driver of fungal diversity. For forest management, promoting a wide array of dead tree species (especially angiosperm species), a range of stem trait values and decay stages will increase fungal and, thereby, forest biodiversity. [ABSTRACT FROM AUTHOR]

The fast–slow plant economy hypothesis predicts strong co-variation in key resource-use traits due to the trade-off between growth and survival of species. Accordingly, it is expected that trait variation may be reduced to a single dimension along a growth-survival gradient. However, some studies warn against such reductionism and promote investigating how a multi-dimensional trait space can be interpreted in a growth-survival trade-off context. To quantify the dimensionality of the trait variation of trees and tree-like species to test the fast–slow plant economy hypothesis in a subtropical rain forest. We conducted phylogenetic Principal Components Analyses and correlation test on traits describing carbon and water economy in the leaves, stem, and seeds to evaluate the dimensionality of trait space and covariation among traits. We found five axes explaining 71% of trait variation. The first and second axes described carbon capture and allocation. Water use economy was related to carbon capture and was also represented on the third axis. Stomata traits were related to the fourth axis and plant potential height to the fourth and fifth axes. The high dimensionality we found suggests that ecological strategies to water and carbon use are diverse in (sub)tropical montane forest species. Therefore, contrary to the expectation, these plants could use different ecological strategies to achieve a similar fitness in the growth–survival gradient. [ABSTRACT FROM AUTHOR]

【Objective】To determine the performance of stem related characters in direct seeding rice and their relationship with lodging resistance under different sowing dates,to provide reference for lodging resistance breeding in direct seeding rice.【Methods】Lianjing7, Xudao3 (Medium-maturing medium Japonica Rice) and Lianjing15, Lianjing 13ZJ61 (Early-maturing medium Japonica Rice) were used as experimental materials, three sowing dates were set on June 10, June 20 and June 30. The effects of sowing date on the growth dynamics of the above ground and yield in direct seeding rice were studied, and the correlation between the stem characters and the lodging resistance in rice plants were analyzed.【Results】The yield components and actual yield of four varieties all decreased with the delay of sowing date, but the degree of decline was different. With the delay of sowing date, the bending resistance of stem and the bending moment decreased, the spike length and the plant height significantly decreased, the dry weight per unit internode of basal internode and the anti-overturning force per plant also decreased. The lodging resistance of different varieties was closely related to internode length, stem dry weight and dry weight per unit internode.【Conclusion】Early sowing (June 10), shorter for the first and second internodes, its stem with high dry weight and plumpness, was conducive to lodging resistance for direct seeding rice. [ABSTRACT FROM AUTHOR]

Plant architecture has played an important role in the adaptation of maize (Zea mays L.) hybrids to historical increases in plant density in order to maximize yields per unit area. At high density, a compact plant structure would allow for less interference by light among plants of the row and a deeper penetration of the radiation towards the lowest canopy layers, without compromising the capture of radiation at crop level. The genetic control of plant architecture traits of maize under contrasting plant densities remains poorly understood. In this work, traits related to leaf and stem architecture were phenotypically analyzed and QTLs were mapped using 160 RILs from the IBM B73 × Mo17 Syn4 population cultivated at low density and high density during 2013–2014 and 2014–2015 growing seasons in Buenos Aires province, Argentina. Forty-nine QTLs were detected on chromosomes 1, 3, 4, 5, 9 and 10. Most QTLs of vertical insertion angle of leaves and leaf orientation value (i.e., vertical angle affected by the curvature of leaves) were detected on chromosome 5 at high density and showed a high percentage of co-location. Detected QTLs for plant and ear height, and the relationship between them were concentrated on chromosome 9, with consistent effect under different density × environment combinations. These regions had large-effect QTLs and constitute hot spots that need to be studied in more detail to determine their potential use in breeding programs. [ABSTRACT FROM AUTHOR]

Aim: Plant trait databases often contain traits that are correlated, but for whom direct (undirected statistical dependency) and indirect (mediated by other traits) connections may be confounded. The confounding of correlation and connection hinders our understanding of plant strategies, and how these vary among growth forms and climate zones. We identified the direct and indirect connections across plant traits relevant to competition, resource acquisition and reproductive strategies using a global database and explored whether connections within and between traits from different tissue types vary across climates and growth forms. Location: Global. Major taxa studied: Plants. Time period: Present. Methods: We used probabilistic graphical models and a database of 10 plant traits (leaf area, specific leaf area, mass‐ and area‐based leaf nitrogen and phosphorous content, leaf life span, plant height, stem specific density and seed mass) with 16,281 records to describe direct and indirect connections across woody and non‐woody plants across tropical, temperate, arid, cold and polar regions. Results: Trait networks based on direct connections are sparser than those based on correlations. Land plants had high connectivity across traits within and between tissue types; leaf life span and stem specific density shared direct connections with all other traits. For both growth forms, two groups of traits form modules of more highly connected traits; one related to resource acquisition, the other to plant architecture and reproduction. Woody species had higher trait network modularity in polar compared to temperate and tropical climates, while non‐woody species did not show significant differences in modularity across climate regions. Main conclusions: Plant traits are highly connected both within and across tissue types, yet traits segregate into persistent modules of traits. Variation in the modularity of trait networks suggests that trait connectivity is shaped by prevailing environmental conditions and demonstrates that plants of different growth forms use alternative strategies to cope with local conditions. [ABSTRACT FROM AUTHOR]

With the use of terrestrial laser scanning (TLS) in forest stands, surveys are now equipped to obtain dense point cloud data. However, the data range, i.e., the number of points, often reaches the billions or even higher, exceeding random access memory (RAM) limits on common computers. Moreover, the processing time often also extends beyond acceptable processing lengths. Thus, in this paper, we present a new method of efficiently extracting stem traits from huge point cloud data obtained by TLS, without subdividing or downsampling the point clouds. In this method, each point cloud is converted into a wireframe model by connecting neighboring points on the same continuous surface, and three-dimensional points on stems are resampled as cross-sectional points of the wireframe model in an out-of-core manner. Since the data size of the section points is much smaller than the original point clouds, stem traits can be calculated from the section points on a common computer. With the study method, 1381 tree stems were calculated from 3.6 billion points in ~20 min on a common computer. To evaluate the accuracy of this method, eight targeted trees were cut down and sliced at 1-m intervals; actual stem traits were then compared to those calculated from point clouds. The experimental results showed that the efficiency and accuracy of the proposed method are sufficient for practical use in various fields, including forest management and forest research.

Modern sugarcane cultivars are derived from the interspecific crossing between Saccharum officinarum and wild sugarcane, Saccharum spontaneum. The introgression of valuable characteristics from wild sugarcane is recognized as extremely important, but this process typically requires long-term effort over multiple generations of backcrosses owing to the low sugar content of the initial interspecific hybrids. In this study, we aimed to identify Japanese wild sugarcanes with high juice brix in order to promote effective interspecific crossing of sugarcane. Sixty-four accessions from the Nansei Islands and 70 accessions from the Honshu were evaluated for juice brix. Wild sugarcanes with high juice brix were demonstrated to exist among wild sugarcanes indigenous to the Honshu. A significant difference was observed between the median juice brix values of wild sugarcanes of the Nansei Islands and those of the Honshu. The relationship between juice brix and stem traits was then examined in 20 wild sugarcanes, 10 each from the Nansei Islands and the Honshu. The reproducibility of juice brix value in both experiments was confirmed. In contrast to juice brix, stem traits, such as length, diameter, and volume, were typically smaller in wild sugarcanes from the Honshu. Moreover, a negative correlation was observed between the index of stem volume and juice brix. In this study, we identified outstanding wild sugarcanes with high juice brix. Using germplasms from the identified wild sugarcanes in interspecific crossing could contribute to the increases in both yield and sugar content.

With the use of terrestrial laser scanning (TLS) in forest stands, surveys are now equipped to obtain dense point cloud data. However, the data range, i.e., the number of points, often reaches the billions or even higher, exceeding random access memory (RAM) limits on common computers. Moreover, the processing time often also extends beyond acceptable processing lengths. Thus, in this paper, we present a new method of efficiently extracting stem traits from huge point cloud data obtained by TLS, without subdividing or downsampling the point clouds. In this method, each point cloud is converted into a wireframe model by connecting neighboring points on the same continuous surface, and three-dimensional points on stems are resampled as cross-sectional points of the wireframe model in an out-of-core manner. Since the data size of the section points is much smaller than the original point clouds, stem traits can be calculated from the section points on a common computer. With the study method, 1381 tree stems were calculated from 3.6 billion points in ~20 min on a common computer. To evaluate the accuracy of this method, eight targeted trees were cut down and sliced at 1-m intervals; actual stem traits were then compared to those calculated from point clouds. The experimental results showed that the efficiency and accuracy of the proposed method are sufficient for practical use in various fields, including forest management and forest research. [ABSTRACT FROM AUTHOR]