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1

Liu, Xiaoman, Xiaolei Zhao, Lijun Zhang, Wenjing Lu, Xiaojuan Li et Kai Xiao. « TaPht1;4, a high-affinity phosphate transporter gene in wheat (Triticum aestivum), plays an important role in plant phosphate acquisition under phosphorus deprivation ». Functional Plant Biology 40, no 4 (2013) : 329. http://dx.doi.org/10.1071/fp12242.

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An expressed sequence tag (EST) highly similar to BdPT1–4, a phosphate transporter (PT) gene in Brachypodium distachyon, was obtained in a wheat root cDNA subtractive suppression library containing genes that respond to low-phosphate (Pi) stress. The DNA sequence covering this EST (designated as TaPht1;4) was determined based on screening a wheat DNA library. TaPht1;4 consists of two exons and one intron and encodes a 555 amino acid (aa) polypeptide with a molecular weight of 60.85 kDa and an isoelectric point of 7.60. TaPht1;4 contains 12 conserved membrane-spanning domains similar to previously reported PTs in diverse plant species. Yeast complement analysis in low-Pi medium confirmed that TaPht1;4 confers the capacity to uptake Pi to MB192, a yeast strain with a defective high-affinity PT; with an apparent Km of 35.3 μM. The TaPht1;4 transcripts were specifically detected in the root and were highly induced under Pi deficiency. TaPht1;4 was also expressed following a diurnal pattern, i.e. high levels during daytime and low levels during night-time. TaPht1;4 overexpression and downregulation dramatically altered the plant phenotypic features under low-Pi conditions. Samples that overexpressed TaPht1;4 had significantly improved growth traits and accumulated more Pi than the wild-type plant and those with downregulated TaPht1;4 expression. Therefore, TaPht1;4 is a high-affinity PT gene that plays a critical role in wheat Pi acquisition under Pi deprivation.
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Koven, Charles D., Ryan G. Knox, Rosie A. Fisher, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto et al. « Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama ». Biogeosciences 17, no 11 (15 juin 2020) : 3017–44. http://dx.doi.org/10.5194/bg-17-3017-2020.

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Abstract. Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.
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Verheijen, L. M., V. Brovkin, R. Aerts, G. Bönisch, J. H. C. Cornelissen, J. Kattge, P. B. Reich, I. J. Wright et P. M. van Bodegom. « Impacts of trait variation through observed trait-climate relationships on performance of a representative Earth System model : a conceptual analysis ». Biogeosciences Discussions 9, no 12 (19 décembre 2012) : 18907–50. http://dx.doi.org/10.5194/bgd-9-18907-2012.

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Abstract. In current dynamic global vegetation models (DGVMs), including those incorporated into Earth System Models (ESMs), terrestrial vegetation is represented by a small number of plant functional types (PFTs), each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA), maximum carboxylation rate at 25 °C (Vcmax25) and maximum electron transport rate (Jmax25)) to vary within PFTs via trait-climate relationships based on a large trait database. For all three traits, the means of observed natural trait values strongly deviated from values used in the default model, with mean differences of 32.3% for Vcmax25, 26.8% for Jmax25 and 17.3% for SLA. Compared to the default simulation, allowing trait variation within PFTs resulted in GPP differences up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating observational data based on the ecological concepts of environmental filtering will improve the modeling of vegetation behavior in DGVMs and as such will enable more reliable projections in unknown climates.
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Butler, Ethan E., Abhirup Datta, Habacuc Flores-Moreno, Ming Chen, Kirk R. Wythers, Farideh Fazayeli, Arindam Banerjee et al. « Mapping local and global variability in plant trait distributions ». Proceedings of the National Academy of Sciences 114, no 51 (1 décembre 2017) : E10937—E10946. http://dx.doi.org/10.1073/pnas.1708984114.

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Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.
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Meng, T. T., H. Wang, S. P. Harrison, I. C. Prentice, J. Ni et G. Wang. « Responses of leaf traits to climatic gradients : adaptive variation vs. compositional shifts ». Biogeosciences Discussions 12, no 9 (13 mai 2015) : 7093–124. http://dx.doi.org/10.5194/bgd-12-7093-2015.

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Abstract. Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait–climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must also take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits.
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Meng, T. T., H. Wang, S. P. Harrison, I. C. Prentice, J. Ni et G. Wang. « Responses of leaf traits to climatic gradients : adaptive variation versus compositional shifts ». Biogeosciences 12, no 18 (17 septembre 2015) : 5339–52. http://dx.doi.org/10.5194/bg-12-5339-2015.

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Abstract. Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.
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Verheijen, L. M., V. Brovkin, R. Aerts, G. Bönisch, J. H. C. Cornelissen, J. Kattge, P. B. Reich, I. J. Wright et P. M. van Bodegom. « Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model : a conceptual analysis ». Biogeosciences 10, no 8 (15 août 2013) : 5497–515. http://dx.doi.org/10.5194/bg-10-5497-2013.

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Abstract. In many current dynamic global vegetation models (DGVMs), including those incorporated into Earth system models (ESMs), terrestrial vegetation is represented by a small number of plant functional types (PFTs), each with fixed properties irrespective of their predicted occurrence. This contrasts with natural vegetation, in which many plant traits vary systematically along geographic and environmental gradients. In the JSBACH DGVM, which is part of the MPI-ESM, we allowed three traits (specific leaf area (SLA), maximum carboxylation rate at 25 °C (Vcmax25) and maximum electron transport rate at 25 °C (Jmax25)) to vary within PFTs via trait–climate relationships based on a large trait database. The R2adjusted of these relationships were up to 0.83 and 0.71 for Vcmax25 and Jmax25, respectively. For SLA, more variance remained unexplained, with a maximum R2adjusted of 0.40. Compared to the default simulation, allowing trait variation within PFTs resulted in gross primary productivity differences of up to 50% in the tropics, in > 35% different dominant vegetation cover, and a closer match with a natural vegetation map. The discrepancy between default trait values and natural trait variation, combined with the substantial changes in simulated vegetation properties, together emphasize that incorporating climate-driven trait variation, calibrated on observational data and based on ecological concepts, allows more variation in vegetation responses in DGVMs and as such is likely to enable more reliable projections in unknown climates.
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Liu, Chun-Yan, Xiao-Niu Guo, Xiao-Long Wu, Feng-Jun Dai et Qiang-Sheng Wu. « The Comprehensive Effects of Rhizophagus intraradices and P on Root System Architecture and P Transportation in Citrus limon L. » Agriculture 12, no 3 (22 février 2022) : 317. http://dx.doi.org/10.3390/agriculture12030317.

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Both arbuscular mycorrhizal fungi (AMF) and phosphorus (P) collectively influence the root system architecture (RSA), but whether the combination of the two affects RSA, particularly lateral root formation, is unknown. In the present study, a pot experiment was conducted to evaluate the effects of an arbuscular mycorrhizal fungus (Rhizophagus intraradices) on the RSA of lemon (Citrus limon L.) seedlings under 0 (P0) and 50 mg/kg (P50) P levels. Moreover, P and carbohydrate content; acid phosphatase activity; and the expression of P transporter genes (PTs), phosphatase genes (PAPs), and lateral-root-related genes; were determined. Our results show that root mycorrhizal colonization and mycorrhizal dependency of lemon plants are significantly higher under P0 than under P50 conditions. AMF significantly promoted the plant growth performance of lemon, irrespective of substrate P levels. The RSA parameters of AMF plants, including total root length, projected area, surface area, average diameter, volume, and second- and third-order lateral root numbers, were distinctly increased under the two P levels compared to those of non-AMF plants. Mycorrhizal treatment also induced higher carbohydrate (sucrose, glucose, and fructose) and P contents, along with a higher activity of root acid phosphatase. The expression of P-related genes, including ClPAP1, ClPT1, ClPT3, ClPT5, and ClPT7, as well as the expression of lateral-root-related genes (ClKRP6, ClPSK6, and ClRSI-1), was dramatically upregulated by AMF inoculation, irrespective of substrate P levels. Principal component analysis showed that root P and carbohydrate contents, as well as the expression of ClKRP6 and ClPSK6, were positively correlated with RSA traits and lateral root development. Our study demonstrates that mycorrhizas accelerate the P acquisition and carbohydrate accumulation of lemon plants by upregulating the expression of lateral-root-related genes, thereby positively improving the RSA. Furthermore, AMF had a greater impact on the RSA of lemon than substrate P levels.
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Buotte, Polly C., Charles D. Koven, Chonggang Xu, Jacquelyn K. Shuman, Michael L. Goulden, Samuel Levis, Jessica Katz et al. « Capturing functional strategies and compositional dynamics in vegetation demographic models ». Biogeosciences 18, no 14 (30 juillet 2021) : 4473–90. http://dx.doi.org/10.5194/bg-18-4473-2021.

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Abstract. Plant community composition influences carbon, water, and energy fluxes at regional to global scales. Vegetation demographic models (VDMs) allow investigation of the effects of changing climate and disturbance regimes on vegetation composition and fluxes. Such investigation requires that the models can accurately resolve these feedbacks to simulate realistic composition. Vegetation in VDMs is composed of plant functional types (PFTs), which are specified according to plant traits. Defining PFTs is challenging due to large variability in trait observations within and between plant types and a lack of understanding of model sensitivity to these traits. Here we present an approach for developing PFT parameterizations that are connected to the underlying ecological processes determining forest composition in the mixed-conifer forest of the Sierra Nevada of California, USA. We constrain multiple relative trait values between PFTs, as opposed to randomly sampling within the range of observations. An ensemble of PFT parameterizations are then filtered based on emergent forest properties meeting observation-based ecological criteria under alternate disturbance scenarios. A small ensemble of alternate PFT parameterizations is identified that produces plausible forest composition and demonstrates variability in response to disturbance frequency and regional environmental variation. Retaining multiple PFT parameterizations allows us to quantify the uncertainty in forest responses due to variability in trait observations. Vegetation composition is a key emergent outcome from VDMs and our methodology provides a foundation for robust PFT parameterization across ecosystems.
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Uddin, Md Shalim, Masum Billah, Rozina Afroz, Sajia Rahman, Nasrin Jahan, Md Golam Hossain, Shamim Ara Bagum et al. « Evaluation of 130 Eggplant (Solanum melongena L.) Genotypes for Future Breeding Program Based on Qualitative and Quantitative Traits, and Various Genetic Parameters ». Horticulturae 7, no 10 (8 octobre 2021) : 376. http://dx.doi.org/10.3390/horticulturae7100376.

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Eggplant is an essential widespread year-round fruit vegetable. This study was conducted using 130 local germplasm of brinjal to select diverse parents based on the multiple traits selection index for the future breeding program. This selection was performed focusing on 14 qualitative and 10 quantitative traits variation and genetic parameters namely, phenotypic and genotypic variance (PV and GV) and genotypic and phenotypic coefficients of variation (GCV and PCV), broad-sense heritability (hBS), genetic advance, traits association, genotype by trait biplot (G × T), heatmap analysis and multi-trait index based on factor analysis and genotype-ideotype distance (MGIDI). Descriptive statistics and analysis of variance revealed a wide range of variability for morpho-physiological traits. Estimated hBS for all the measured traits ranged from 10.6% to 93%, indicating that all the traits were highly inheritable. Genetic variances were low to high for most morpho-physiological traits, indicating complex genetic architecture. Yield per plant was significantly correlated with fruit diameter, fruits per plant, percent fruits infestation by brinjal shoot and fruit borer, and fruit weight traits indicating that direct selection based on fruit number and fruit weight might be sufficient for improvement of other traits. The first two principal components (PCs) explained about 81.27% of the total variation among lines for 38 brinjal morpho-physiological traits. Genotype by trait (G × T) biplot revealed superior genotypes with combinations of favorable traits. The average genetic distance was 3.53, ranging from 0.25 to 20.01, indicating high levels of variability among the germplasm. The heat map was also used to know the relationship matrix among all the brinjal genotypes. MGIDI is an appropriate method of selection based on multiple trait information. Based on the fourteen qualitative and ten quantitative traits and evaluation of various genetic parameters, the germplasm G80, G54, G66, and G120 might be considered as best parents for the future breeding program for eggplant improvement.
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Tiwari, Priya, et Stuti Sharma. « Principal component analyses in mungbean genotypes under summer season ». INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES 17, no 2 (15 juin 2021) : 287–92. http://dx.doi.org/10.15740/has/ijas/17.2/287-292.

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Yield is a complex trait subjective to several components and environmental factors. Therefore, it becomes necessary to apply such technique which can identify and prioritize the key traits to lessen the number of traits for valuable selection and genetic gain. Principal component analysis is primarily a renowned data reduction technique which identifies the least number of components and explain maximum variability, it also rank genotypes on the basis of PC scores. PCA was calculated using Ingebriston and Lyon (1985) method. In present study, PCA performed for phenological and yield component traits presented that out of thirteen, only five principal components (PCs) exhibited more than 1.00 eigen value, and showed about 80.28 per cent of total variability among the traits. Scree plot explained the percentage of variance associated with each principal component obtained by illustrating a graph between eigen values and principal component numbers. PC1 showed 26.12 per cent variability with eigen value 3.40. Graph depicted that the maximum variation was observed in PC1 in contrast to other four PCs. The PC1 was further associated with the phenological and yield attributing traits viz., number of nodes per plant, number of pod cluster per plant, number of pod per plant. PC2 exhibited positive effect for harvest index. The PC3 was more related to yield related traits i.e., number of seeds per pod, number of seeds per plant and biological yield per plant, whereas PC4 was more loaded with phenological traits. PC5 was further related to yield and yield contributing traits i.e. number of primary branches per plant, seed yield per plant and 100 seed weight. A high value of PC score of a particular genotype in a particular PC denotes high value for those variables falling under that specific principal component. Pusa Vishal found in PC 2, in PC 3, PC 4 and PC 5, can be considered as an ideal breeding material for selection and for further deployment in defined breeding programme.
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XU, SHIZHONG, et ZHIQIU HU. « Methods of plant breeding in the genome era ». Genetics Research 92, no 5-6 (décembre 2010) : 423–41. http://dx.doi.org/10.1017/s0016672310000583.

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SummaryMethods of genomic value prediction are reviewed. The majority of the methods are related to mixed model methodology, either explicitly or implicitly, by treating systematic environmental effects as fixed and quantitative trait locus (QTL) effects as random. Six different methods are reviewed, including least squares (LS), ridge regression, Bayesian shrinkage, least absolute shrinkage and selection operator (Lasso), empirical Bayes and partial least squares (PLS). The LS and PLS methods are non-Bayesian because they do not require probability distributions for the data. The PLS method is introduced as a special dimension reduction scheme to handle high-density marker information. Theory and methods of cross-validation are described. The leave-one-out cross-validation approach is recommended for model validation. A working example is used to demonstrate the utility of genome selection (GS) in barley. The data set contained 150 double haploid lines and 495 DNA markers covering the entire barley genome, with an average marker interval of 2·23 cM. Eight quantitative traits were included in the analysis. GS using the empirical Bayesian method showed high predictability of the markers for all eight traits with a mean accuracy of prediction of 0·70. With traditional marker-assisted selection (MAS), the average accuracy of prediction was 0·59, giving an average gain of GS over MAS of 0·11. This study provided strong evidence that GS using marker information alone can be an efficient tool for plant breeding.
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Mazur, Oleksandr, et Roman Stashevsky. « DIFFERENCES IN COMMON BEAN VARIETIES WITH RESPECT TO VALUABLE ECONOMIC TRAITS ». Agriculture and Forestry, no 1 (29 avril 2022) : 46–60. http://dx.doi.org/10.37128/2707-5826-2022-1-4.

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As a result of this research, a number of variety varieties have been identified, which are distinguished by a set of valuable economic traits. The differences of variety samples were established by a comparative evaluation of the manifestation of traits in comparison with the standard. Among the bean varieties under study, 25 pieces were classified as early-ripening (27.8%). (27.8%), medium-early - 36.0 pcs. (40.0%), medium-ripening - 18.0 pcs. - (20%) and medium-early - 11 pcs. (12,2%). Common bean varieties with high attachment of the lower beans on the plant were identified. Among the totality of the original material submitted varieties were: UD0302930 (Ukraine) - 16.7 cm, UD0302957 (Ukraine) - 16.5 cm, UD0301502 (Ukraine) - 16.0 cm, Local 2 (Ukraine) - 15.6 cm. Compared with the standard, only cultivars UD0302930 (Ukraine) and UD0302957 (Ukraine) significantly exceeded the standard in terms of the height of lower bean attachment. The number of seeds per plant is a derived trait of the number of beans, so the varieties with the highest number of beans were also characterized by higher rates of seed number per plant. Consequently, UD0300411 (Romania) with 45.7 and UD0301736 with 44.2 seeds per plant were noted to have significantly exceeded the standard in this indicator. At level with the standard number of seeds per plant was found in samples UD0301043 (Turkey), Local 1 (Ukraine) - 38.9 pcs. The quantitative expression of the trait 1000 grains weight is a confirmation of the previously reported material, that in order to form the maximum expression of the trait in grain legume crops, including common bean, parental forms are included in hybridization for the expression of yield structure elements slightly above the average in the whole sample. That is, the varieties that stood out both in the number of beans per plant and the number of seeds per plant were inferior to other samples, in which the number of beans and the number of seeds per plant were lower. The highest mass of 1000 grains was characterized by the variety samples UD0300227 (USA) - 248.3 g, UD0300782 (Ukraine) - 221.2 g, Local 1 (Ukraine) - 224.3 g, UD0303753 ) - 214.3 g, UD0301736 - 208.3 g. In terms of yield as well as grain productivity, the following varieties stood out: UD0300227 (USA) - 402 g, UD0301736 - 405 g, UD0300411 (Romania) - 391 g, Local 1 (Ukraine) - 3 (4) g, which exceeded the standard at a significant level.
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Souza, Augusto, et Yang Yang. « High-Throughput Corn Image Segmentation and Trait Extraction Using Chlorophyll Fluorescence Images ». Plant Phenomics 2021 (21 juillet 2021) : 1–15. http://dx.doi.org/10.34133/2021/9792582.

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Plant segmentation and trait extraction for individual organs are two of the key challenges in high-throughput phenotyping (HTP) operations. To address this challenge, the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University utilizes chlorophyll fluorescence images (CFIs) to enable consistent and efficient automatic segmentation of plants of different species, age, or color. A series of image analysis routines were also developed to facilitate the quantitative measurements of key corn plant traits. A proof-of-concept experiment was conducted to demonstrate the utility of the extracted traits in assessing drought stress reaction of corn plants. The image analysis routines successfully measured several corn morphological characteristics for different sizes such as plant height, area, top-node height and diameter, number of leaves, leaf area, and angle in relation to the stem. Data from the proof-of-concept experiment showed how corn plants behaved when treated with different water regiments or grown in pot of different sizes. High-throughput image segmentation and analysis basing on a plant’s fluorescence image was proved to be efficient and reliable. Extracted trait on the segmented stem and leaves of a corn plant demonstrated the importance and utility of this kind of trait data in evaluating the performance of corn plant under stress. Data collected from corn plants grown in pots of different volumes showed the importance of using pot of standard size when conducting and reporting plant phenotyping data in a controlled-environment facility.
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Wang, Xingyi, Hui Liu, Md Sultan Mia, Kadambot H. M. Siddique et Guijun Yan. « Development of near-isogenic lines targeting a major QTL on 3AL for pre-harvest sprouting resistance in bread wheat ». Crop and Pasture Science 69, no 9 (2018) : 864. http://dx.doi.org/10.1071/cp17423.

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Resistance to pre-harvest sprouting (PHS) in wheat (Triticum aestivum L.) is one of the most valuable traits in many breeding programs. However, the quantitative nature of inheritance of PHS resistance challenges the study of this trait. Near-isogenic lines (NILs) can turn a complicated quantitative trait into a Mendelian factor (qualitative) and are, therefore, valuable materials for identification of the gene(s) responsible for a specific phenotypic trait and for functional studies of specific loci. Five pairs of NILs were developed and confirmed for a major quantitative trait locus (QTL) located on the long arm of chromosome 3A contributing to PHS resistance in wheat. These NILs were generated by using the heterogeneous inbred family method and a fast generation-cycling system. Significant differences in PHS resistance between the isolines were detected in the NILs. The presence of the PHS-resistance allele from the resistant parent increased resistance to sprouting on spikes by 26.7–96.8%, with an average of 73.8%, and increased seed dormancy by 36.9–87.2%, with an average of 59.9% across the NILs. These NILs are being used for the identification of candidate genes responsible for this major PHS-resistance locus on wheat chromosome arm 3AL.
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Liu, Yanlan, Nataniel M. Holtzman et Alexandra G. Konings. « Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion ». Hydrology and Earth System Sciences 25, no 5 (10 mai 2021) : 2399–417. http://dx.doi.org/10.5194/hess-25-2399-2021.

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Abstract. Droughts are expected to become more frequent and severe under climate change, increasing the need for accurate predictions of plant drought response. This response varies substantially, depending on plant properties that regulate water transport and storage within plants, i.e., plant hydraulic traits. It is, therefore, crucial to map plant hydraulic traits at a large scale to better assess drought impacts. Improved understanding of global variations in plant hydraulic traits is also needed for parameterizing the latest generation of land surface models, many of which explicitly simulate plant hydraulic processes for the first time. Here, we use a model–data fusion approach to evaluate the spatial pattern of plant hydraulic traits across the globe. This approach integrates a plant hydraulic model with data sets derived from microwave remote sensing that inform ecosystem-scale plant water regulation. In particular, we use both surface soil moisture and vegetation optical depth (VOD) derived from the X-band Japan Aerospace Exploration Agency (JAXA) Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; collectively AMSR-E). VOD is proportional to vegetation water content and, therefore, closely related to leaf water potential. In addition, evapotranspiration (ET) from the Atmosphere–Land Exchange Inverse (ALEXI) model is also used as a constraint to derive plant hydraulic traits. The derived traits are compared to independent data sources based on ground measurements. Using the K-means clustering method, we build six hydraulic functional types (HFTs) with distinct trait combinations – mathematically tractable alternatives to the common approach of assigning plant hydraulic values based on plant functional types. Using traits averaged by HFTs rather than by plant functional types (PFTs) improves VOD and ET estimation accuracies in the majority of areas across the globe. The use of HFTs and/or plant hydraulic traits derived from model–data fusion in this study will contribute to improved parameterization of plant hydraulics in large-scale models and the prediction of ecosystem drought response.
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Yang, Yanzheng, Qiuan Zhu, Changhui Peng, Han Wang et Huai Chen. « From plant functional types to plant functional traits ». Progress in Physical Geography : Earth and Environment 39, no 4 (7 mai 2015) : 514–35. http://dx.doi.org/10.1177/0309133315582018.

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Dynamic global vegetation models (DGVMs) typically track the material and energy cycles in ecosystems with finite plant functional types (PFTs). Increasingly, the community ecology and modelling studies recognize that current PFT scheme is not sufficient for simulating ecological processes. Recent advances in the study of plant functional traits (FTs) in community ecology provide a novel and feasible approach for the improvement of PFT-based DGVMs. This paper reviews the development of current DGVMs over recent decades. After characterizing the advantages and disadvantages of the PFT-based scheme, it summarizes trait-based theories and discusses the possibility of incorporating FTs into DGVMs. More importantly, this paper summarizes three strategies for constructing next-generation DGVMs with FTs. Finally, the method’s limitations, current challenges and future research directions for FT theory are discussed for FT theory. We strongly recommend the inclusion of several FTs, namely specific leaf area (SLA), leaf nitrogen content (LNC), carbon isotope composition of leaves (Leaf δ13C), the ratio between leaf-internal and ambient mole fractions of CO2 (Leaf Ci/Ca), seed mass and plant height. These are identified as the most important in constructing DGVMs based on FTs, which are also recognized as important ecological strategies for plants. The integration of FTs into dynamic vegetation models is a critical step towards improving the results of DGVM simulations; communication and cooperation among ecologists and modellers is equally important for the development of the next generation of DGVMs.
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Cardenas, Julian, Fernando Santa et Eva Kaštovská. « The Exudation of Surplus Products Links Plant Functional Traits and Plant-Microbial Stoichiometry ». Land 10, no 8 (11 août 2021) : 840. http://dx.doi.org/10.3390/land10080840.

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The rhizosphere is a hot spot of soil microbial activity and is largely fed by root exudation. The carbon (C) exudation flux, coupled with plant growth, is considered a strategy of plants to facilitate nutrient uptake. C exudation is accompanied by a release of nutrients. Nitrogen (N) and phosphorus (P) co-limit the productivity of the plant-microbial system. Therefore, the C:N:P stoichiometry of exudates should be linked to plant nutrient economies, plant functional traits (PFT) and soil nutrient availability. We aimed to identify the strongest links in C:N:P stoichiometry among all rhizosphere components. A total of eight grass species (from conservative to exploitative) were grown in pots under two different soil C:nutrient conditions for a month. As a result, a wide gradient of plant–microbial–soil interactions were created. A total of 43 variables of plants, exudates, microbial and soil C:N:P stoichiometry, and PFTs were evaluated. The variables were merged into four groups in a network analysis, allowing us to identify the strongest connections among the variables and the biological meaning of these groups. The plant–soil interactions were shaped by soil N availability. Faster-growing plants were associated with lower amounts of mineral N (and P) in the soil solution, inducing a stronger competition for N with microorganisms in the rhizosphere compared to slower-growing plants. The plants responded by enhancing their N use efficiency and root:shoot ratio, and they reduced N losses via exudation. Root growth was supported either by reallocated foliar reserves or by enhanced ammonium uptake, which connected the specific leaf area (SLA) to the mineral N availability in the soil. Rapid plant growth enhanced the exudation flux. The exudates were rich in C and P relative to N compounds and served to release surplus metabolic products. The exudate C:N:P stoichiometry and soil N availability combined to shape the microbial stoichiometry, and N and P mining. In conclusion, the exudate flux and its C:N:P stoichiometry reflected the plant growth rate and nutrient constraints with a high degree of reliability. Furthermore, it mediated the plant–microbial interactions in the rhizosphere.
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Pavlick, R., D. T. Drewry, K. Bohn, B. Reu et A. Kleidon. « The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) : a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs ». Biogeosciences Discussions 9, no 4 (17 avril 2012) : 4627–726. http://dx.doi.org/10.5194/bgd-9-4627-2012.

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Abstract. Dynamic Global Vegetation Models (DGVMs) typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical Plant Functional Types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity DGVM (JeDi-DGVM) as a new approach to global vegetation modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly-generated plant growth strategies (PGSs), each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a PGS is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other PGSs. The biogeochemical fluxes and land-surface properties of the individual PGSs are aggregated to the grid cell scale using a mass-based weighting scheme. Simulated global biogeochemical and biogeographical patterns are evaluated against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favorably with other state-of-the-art terrestrial biosphere models. This is despite the parameters describing the ecophysiological functioning and allometry of JeDi-DGVM plants evolving as a function of vegetation survival in a given climate, as opposed to typical approaches that fix land surface parameters derived from observational datasets for each PFT. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.
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Lobos, Gustavo, Alejandro Escobar-Opazo, Félix Estrada, Sebastián Romero-Bravo, Miguel Garriga, Alejandro del Pozo, Carlos Poblete-Echeverría, Jaime Gonzalez-Talice, Luis González-Martinez et Peter Caligari. « Spectral Reflectance Modeling by Wavelength Selection : Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions ». Remote Sensing 11, no 3 (7 février 2019) : 329. http://dx.doi.org/10.3390/rs11030329.

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To overcome the environmental changes occurring now and predicted for the future, it is essential that fruit breeders develop cultivars with better physiological performance. During the last few decades, high-throughput plant phenotyping and phenomics have been developed primarily in cereal breeding programs. In this study, plant reflectance, at the level of the leaf, was used to assess several physiological traits in five Vaccinium spp. cultivars growing under four controlled conditions (no-stress, water deficit, heat stress, and combined stress). Two modeling methodologies [Multiple Linear Regression (MLR) and Partial Least Squares (PLS)] with or without (W/O) prior wavelength selection (multicollinearity, genetic algorithms, or in combination) were considered. PLS generated better estimates than MLR, although prior wavelength selection improved MLR predictions. When data from the environments were combined, PLS W/O gave the best assessment for most of the traits, while in individual environments, the results varied according to the trait and methodology considered. The highest validation predictions were obtained for chlorophyll a/b (R2Val ≤ 0.87), maximum electron transport rate (R2Val ≤ 0.60), and the irradiance at which the electron transport rate is saturated (R2Val ≤ 0.59). The results of this study, the first to model modulated chlorophyll fluorescence by reflectance, confirming the potential for implementing this tool in blueberry breeding programs, at least for the estimation of a number of important physiological traits. Additionally, the differential effects of the environment on the spectral signature of each cultivar shows this tool could be directly used to assess their tolerance to specific environments.
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Jankulovska, Mirjana, Sonja Ivanovska, Ana Marjanovic-Jeromela, Snjezana Bolaric, Ljupcho Jankuloski, D. DimovZoran, Dane Bosev et Biljana Kuzmanovska. « Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm ». Genetika 46, no 2 (2014) : 545–59. http://dx.doi.org/10.2298/gensr1402545j.

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In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP). NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes? clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods can assist in deciding how, and based on which traits to select the genotypes, especially in early generations, at the beginning of a breeding program.
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Benelli, Victoria G., Fred L. Allen et Ming Li Wang. « Variability in seed oil content and fatty acid composition, phenotypic traits and self-incompatibility among selected niger germplasm accessions ». Plant Genetic Resources 15, no 4 (3 mars 2016) : 348–54. http://dx.doi.org/10.1017/s1479262115000702.

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AbstractNiger (Guizotia abyssinica, L.) is a desirable oilseed crop for birdseed, especially for finches (Spinus spp.) because of its high ratio of unsaturated to saturated fatty acids and relatively high oil content. In 2012, phenotypic traits, seed oil and fatty acid content measurements were made on 14 plant introductions (PIs) from the United States Department of Agriculture germplasm collection. The PIs originated in Ethiopia (ten), India (three) and USA (one). The phenotypic traits analysed included seed/plant, branches/plant, capitula/plant1, average seed/capitulum and plant height. After initial assessments of the 14 PIs, three were selected for use as parents to produce two one-way and two two-way F1 crosses for the purpose of evaluating self-incompatibility (SI). Parent and F1 progeny seeds were planted in a greenhouse and transplanted to a field site at the East Tennessee Research and Education Center (2012, 2013 and 2014). Comparisons from 2012 showed seed oil of the 14 PIs ranging from 32.9 to 37.9% (PI 508076 (Ethiopia) and PI 509436 (India), respectively). Major fatty acids included stearic, palmitic, oleic and linoleic; with linoleic acid in highest amount. PI508079 (Ethiopia) had the best combination of seed yield, seed oil and linoleic acid content. Over 2013 and 2014, SI ranged from 91.1 to 100.0%. W6 18860 (USA) had the most self-compatibility, and the F1 plants generated from crosses between W6 18860 and other plants tended to be self-compatible when the former was used as a pollen recipient. The results obtained from this study should be useful for niger breeding and production purposes.
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Karim, Kumba Y., Beatrice Ifie, Daniel Dzidzienyo, Eric Y. Danquah, Essie T. Blay, Jim B. A. Whyte, Peter Kulakow et al. « Genetic characterization of cassava (Manihot esculenta Crantz) genotypes using agro-morphological and single nucleotide polymorphism markers ». Physiology and Molecular Biology of Plants 26, no 2 (23 décembre 2019) : 317–30. http://dx.doi.org/10.1007/s12298-019-00740-x.

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AbstractDearth of information on extent of genetic variability in cassava limits the genetic improvement of cassava genotypes in Sierra Leone. The aim of this study was to assess the genetic diversity and relationships within 102 cassava genotypes using agro-morphological and single nucleotide polymorphism markers. Morphological classification based on qualitative traits categorized the germplasm into five different groups, whereas the quantitative trait set had four groups. The SNP markers classified the germplasm into three main cluster groups. A total of seven principal components (PCs) in the qualitative and four PCs in the quantitative trait sets accounted for 79.03% and 72.30% of the total genetic variation, respectively. Significant and positive correlations were observed between average yield per plant and harvest index (r = 0.76***), number of storage roots per plant and harvest index (r = 0.33*), height at first branching and harvest index (0.26*), number of storage roots per plant and average yield per plant (r = 0.58*), height at first branching and average yield per plant (r = 0.24*), length of leaf lobe and petiole length (r = 0.38*), number of leaf lobe and petiole length (r = 0.31*), width of leaf lobe and length of leaf lobe (r = 0.36*), number of leaf lobe and length of leaf lobe (r = 0.43*), starch content and dry matter content (r = 0.99***), number of leaf lobe and root dry matter (r = 0.30*), number of leaf lobe and starch content (r = 0.28*), and height at first branching and plant height (r = 0.45**). Findings are useful for conservation, management, short term recommendation for release and genetic improvement of the crop.
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Abdullah Al, Mamun, Islam Monirul, Adhikary Sanjoy Kumar et Sultana Sabiha. « Appraisal of genetic variability in sodium azide induced rice mutants to identify selection criteria for higher yield using quantitative attributes ». Plant Science Today 9, no 4 (4 octobre 2022) : 1001–11. http://dx.doi.org/10.14719/pst.1826.

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Induced mutation is an effective tool in generating variability of crop plants. Identification of efficient genotypes with improved yield requires knowledge of genetic variation in yield and yield contributing traits. Therefore, an investigation was conducted to develop variants through azide mutagenesis and estimation of genetic variability of the mutants to detect selection standards towards higher yield. Mature rice seeds were mutagenized with estimated LD50 concentration. A hundred mutants were grown-up accordingly and their quantitative traits were evaluated through multivariate analysis to assess genetic variability. Every assessed trait except grain length exhibited highly significant variation for all mutants. The high genotypic and phenotypic coefficient of variation along with high heritability and genetic advance as a % of mean was accounted for total and filled grains panicle-1. Grain yield was positively and significantly correlated with total grains panicle-1, filled grains panicle-1 and straw yield hill-1. Besides, higher variance was also associated with these traits. Ward’s Agglomerative clustering grouped the mutants into 7 major clusters. More than 36% of total variation was associated with first 2 principal components (PCs) and was mostly with total grains panicle-1 and filled grains panicle-1 whereas third and fourth PCs were mainly accounted for straw yield hill-1. Thus, these traits should receive special attention during selection of yield potential genotypes. Presence of genetic variation in mutants was ensured for most of the traits and selection based on greater tillers hill-1, grains panicle-1 and straw yield hill-1 may open a new avenue towards improved yield and other traits in rice.
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Babalola, Olubukola, et Oluwaseun Adeyinka Fasusi. « The multifaceted plant-beneficial rhizobacteria toward agricultural sustainability ». Plant Protection Science 57, No. 2 (1 mars 2021) : 95–111. http://dx.doi.org/10.17221/130/2020-pps.

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Agricultural practices depend mainly on the use of chemical fertilisers, pesticides, and herbicides which have caused serious health hazards and have also contributed to the pollution of the environment at large. The application of plant-beneficial rhizobacteria in agrarian practices has become paramount in increasing soil fertility, promoting plant growth, ensuring food safety, and increasing crop production to ensure sustainable agriculture. Beneficial rhizobacteria are soil microorganisms that are eco-friendly and serve as a modern method of improving the plant yield, protecting the plant and soil fertility that pose no harm to humans and the environment. This eco-friendly approach requires the application of beneficial rhizobacteria with plant growth-promoting traits that can improve the nutrient uptake, enhance the resistance of plants to abiotic and biotic stress, protect plants against pathogenic microorganisms and promote plant growth and yield. This review article has highlighted the multitasking roles that beneficial rhizobacteria employ in promoting plant growth, food production, bioremediation, providing defence to plants, and maintaining soil fertility. The knowledge acquired from this review will help in understanding the bases and importance of plant-beneficial rhizobacteria in ensuring agricultural sustainability and as an alternative to the use of agrochemicals.
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Limberger, Oliver, Jürgen Homeier, Nina Farwig, Franz Pucha-Cofrep, Andreas Fries, Christoph Leuschner, Katja Trachte et Jörg Bendix. « Classification of Tree Functional Types in a Megadiverse Tropical Mountain Forest from Leaf Optical Metrics and Functional Traits for Two Related Ecosystem Functions ». Forests 12, no 5 (20 mai 2021) : 649. http://dx.doi.org/10.3390/f12050649.

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Few plant functional types (PFTs) with fixed average traits are used in land surface models (LSMs) to consider feedback between vegetation and the changing atmosphere. It is uncertain if highly diverse vegetation requires more local PFTs. Here, we analyzed how 52 tree species of a megadiverse mountain rain forest separate into local tree functional types (TFTs) for two functions: biomass production and solar radiation partitioning. We derived optical trait indicators (OTIs) by relating leaf optical metrics and functional traits through factor analysis. We distinguished four OTIs explaining 38%, 21%, 15%, and 12% of the variance, of which two were considered important for biomass production and four for solar radiation partitioning. The clustering of species-specific OTI values resulted in seven and eight TFTs for the two functions, respectively. The first TFT ensemble (P-TFTs) represented a transition from low to high productive types. The P-TFT were separated with a fair average silhouette width of 0.41 and differed markedly in their main trait related to productivity, Specific Leaf Area (SLA), in a range between 43.6 to 128.2 (cm2/g). The second delineates low and high reflective types (E-TFTs), were subdivided by different levels of visible (VIS) and near-infrared (NIR) albedo. The E-TFTs were separated with an average silhouette width of 0.28 and primarily defined by their VIS/NIR albedo. The eight TFT revealed an especially pronounced range in NIR reflectance of 5.9% (VIS 2.8%), which is important for ecosystem radiation partitioning. Both TFT sets were grouped along elevation, modified by local edaphic gradients and species-specific traits. The VIS and NIR albedo were related to altitude and structural leaf traits (SLA), with NIR albedo showing more complex associations with biochemical traits and leaf water. The TFTs will support LSM simulations used to analyze the functioning of mountain rainforests under climate change.
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Khoth, Nivesh, Sanjay Singh, R. Shiv Ramakrishnan, GK Koutu, Radheshyam Sharma, Ashish Kumar, Nidhi Pathak et al. « Genetic evaluation of farmer's rice varieties for physiological and yield attributing responses exploiting principal component analysis ». Oryza-An International Journal on Rice 58, no 3 (30 septembre 2021) : 384–93. http://dx.doi.org/10.35709/ory.2021.58.3.5.

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An experiment was conducted on 30 farmer's rice varieties collected from different districts of Madhya Pradesh to identify the genetic components contributing to phenophasic development, physiological, yield attributes and biochemical traits. Principal component analysis was performed to rank the farmer's varieties based on PC scores acquired as per the trait studied. Out of twenty-six traits, only five principal components (PCs) exhibited more than 1.00 Eigen value and showed 85.80% of total cumulative variability. The PC1 showed 58.55%, while PC 2, PC 3, PC 4 and PC 5, exhibited 10.29%, 7.03%, 5.23% and 4.69% variability, respectively. The PC 1 reported the highest variability, which was associated with physiological and yield related traits. The PC 2 was dominated by biochemical traits, while PC3 was mostly dominated for yield traits. The PC 4 was dominated by physiological traits, and PC5 for phenological and yield-related traits. Farmer's variety Pandu was superior for Chlorophyll content index (38.27), total dry matter production (38.15 g plant-1), Leaf area index (4.09), Leaf area duration (17982 cm2 days) and crop growth rate (0.00282 g m-2 day-1). PCA revealed that genotype Pandu (7.224) acquired highest PC score followed by Raibua (5.364), Bahurupi (5.103) and Chinnor 1 (4.750) respectively. Farmers varieties Pandu, Chhindikapoor, Bahurupi, Sitha Chandan, Chinnor 2, Chinnor 1 and ChhotaSathiya were contributed their presence in maximum PCs of this investigation. The identified lines will be utilized in the rice breeding programme to develop improved rice varieties for high yield and maximum physiological efficiency.
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Patni, B., A. S. Panwar, P. Negi et Gopal Krishna Joshi. « Plant growth promoting traits of psychrotolerant bacteria : A boon for agriculture in hilly terrains ». Plant Science Today 5, no 1 (4 janvier 2018) : 24–28. http://dx.doi.org/10.14719/pst.2018.5.1.352.

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Plant growth promoting bacteria (PGPB) are well known to promote plant growth in a number of ways. It is important to study plant growth promoting potential of bacteria capable of growing in extreme environments to establish their role in promoting agricultural yield under harsh conditions. Psychrophilic or psychrotolerant bacteria with plant growth promoting traits may improve the quality of agricultural practices in hilly terrain. The agricultural importance of such microbes stems from the fact that the world over temperate agro-ecosystems are characterized by low temperatures and short growing seasons that subject both plant and microbial life to cold temperature induced stress. Hence, there is a need to identify potential microbes that retain their functional traits under low temperature conditions. Such microbes can be used to enhance the agricultural yields in low temperature areas of the world. This review describes plant growth promoting activities identified in cold adapted bacteria.
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Alikulov, Begali, Vyacheslav Shurigin, Kakhramon Davranov et Zafar Ismailov. « Plant growth-promoting endophytic bacteria associated with Halocnemum strobilaceum (Pall.) M.Bieb and their plant beneficial traits ». Plant Science Today 8, sp1 (22 février 2022) : 44–50. http://dx.doi.org/10.14719/pst.1605.

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Halocnemum strobilaceum (Pall.) M.Bieb. is a halophyte desert plant. The plant is known for its antioxidant, antimicrobial, insecticidal and phytoremediation properties. Halocnemum strobilaceum grows in severe salinity and drought conditions and its’ survival can be associated with activity of endophytic bacteria. The aim of the research was to reveal and study plant growth-promoting endophytic bacteria isolated from Halocnemum strobilaceum (Pall.) M.Bieb. The plants were collected from Kyzylkum desert in Uzbekistan. The endophytic bacteria were isolated from Halocnemum strobilaceum (Pall.) M.Bieb. tissues and screened for cotton (Gossypium hirsutum L.) growth-promoting activity. As a result the most active isolates HAST-2, HAST-7, HAST-9, HAST-10 and HAST-17 were selected. The cotton seeds’ inoculation with these bacterial isolates resulted in significant improvement of seeds germination, root and shoot length, and fresh plant weight due to their ability to fix nitrogen, produce indole-3-acetic acid (IAA), 1-aminocyclopropane-1-carboxylate (ACC) deaminase, siderophores and solubilize phosphates. The chosen isolates were identified using 16S rRNA gene analysis and registered in GenBank (NCBI) as Bacillus megaterium HAST-2, Bacillus aryabhattai HAST-7, Pseudomonas plecoglossicida HAST-9, Pseudomonas putida HAST-10 and Pseudomonas chlororaphis HAST-17. These strains can be used as bio-inoculants to improve the growth of cotton and other crops.
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Nouraein, Mojtaba. « Effect of Nanofertilizers and Biofertilizers on Yield of Maize : Biplot Analysis ». Botanica 25, no 2 (1 décembre 2019) : 121–30. http://dx.doi.org/10.2478/botlit-2019-0014.

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AbstractOne of the newest and most interesting fields of science is nanotechnology, which is exploiting many areas such as life sciences; however, its application in agriculture is rarely studied. In order to examine the environmentfriendly fertilizers (nano-sized and biological fertilizers), and control the agricultural nonpoint source pollution from the source, a field experiment was arranged to study the effects of bulk fertilizers (NPK, nitrogen biofertilizer, and phosphorus biofertilizer), nanofertilizers (nanoboron, nanozinc and nanocomplete) and no fertilizer treatment (control) on morphological traits of maize. The first two Principal Components (PCs) were used to create a biplot, which accounted for 72% of the variance of the treatment × trait interaction. The nanozinc fertilizers following nanoboron fertilizer were the best in most of the biological yield, seed yield, harvest index, and 100-grain weight. The vector-view biplot revealed a strong positive association between chlorophyll and protein content, seed yield with the number of kernels per ears and the number of rows per kernel. Nanocomplete fertilizer was the best treatment for chlorophyll content, protein percent and straw yield, while NPK did not high increase in the most traits of maize. This investigation indicated that treatment × trait biplot can graphically show the interrelationships among traits and facilitate visual comparison of fertilizers. In conclusion, it was found that zinc and boron nanofertilizers increased the production of most of the traits in maize. This study indicated that nano types of fertilizers could promote the studied traits in maize plant.
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Kona, Praveen, M. K. Mahatma, K. Gangadhara, B. C. Ajay, Narendra Kumar, Kiran Kumar Reddy, M. C. Dagla, T. Lokesh Kumar et H. K. Gor. « Evaluation and identification of promising advanced breeding lines for quality and yield traits in groundnut (Arachis hypogaea L.) ». INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES 17, no 2 (15 juin 2021) : 280–86. http://dx.doi.org/10.15740/has/ijas/17.2/280-286.

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Kernel size coupled with the nutritional quality will determine the worth of groundnut for direct consumption or export. Focusing on this objective one hundred and fifty advanced breeding lines (ABLs) in both Spanish and Virginia botanical varieties were evaluated with four checks under Augmented Design during Kharif, 2018 at ICAR- Directorate of Groundnut Research, Junagadh, Gujarat. Significant difference was observed for days to 50% flowering, hundred pod weight (g), hundred kernel weight (g), sound mature kernel (%), shelling percent, pod weight per plant (g), and protein percent. Pod yield per plant (g) registered highest estimates of GCV and PCV. High heritability coupled with high genetic advance as per cent of mean was recorded for 100 pod weight (g), 100 kernel weight (g), sound mature kernel percentage and pod yield per plant (g) traits which indicates a significant role of additive gene action for inheritance of these traits which may be exploited through simple selection methods. Eleven genotypes viz., PBS 19013, PBS 19015, PBS 19018, PBS 29079 B, PBS 29082, PBS 29124, PBS 29167, PBS 29196, PBS 29197, PBS 29212 and PBS 29219 had good confectionery quality traits viz., large seed size (HKW: >55 g; KL: >1.5cm and KW: >0.7cm), high protein (>30%), high total soluble sugar (>5 %), moderate oil (42- 48%), uniform pod size and shape, high pod yield per plant (> 10g) and good shelling percentage (>60%). These promising genotypes can directly be released as a variety after testing in multi-location AICRP-G trials or can be used in hybridization programmes as donor parents for improving confectionery qualities in groundnut.
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Kong, Yun, Katherine Schiestel et Youbin Zheng. « Maximum elongation growth promoted as a shade-avoidance response by blue light is related to deactivated phytochrome : a comparison with red light in four microgreen species ». Canadian Journal of Plant Science 100, no 3 (1 juin 2020) : 314–26. http://dx.doi.org/10.1139/cjps-2019-0082.

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To clarify detailed patterns of responses to blue light associated with decreasing phytochrome activity, the growth and morphology traits of arugula, cabbage, mustard, and kale microgreens were compared under the treatments: (1) R, pure red light; (2) B, pure blue light; (3) BRF0, (4) BRF2, (5) BRF4, and (6) BRF6: unpure blue lights created by mixing B with low-level (6%) R, and further adding 0, 2, 4, and 6 μmol m−2 s−1 of far-red light, respectively. The calculated phytochrome photostationary state (PPS) value, indicating phytochrome activity, gradually decreased in the order of R (0.89), BRF0 (0.69), BRF2 (0.65), BRF4 (0.63), BRF6 (0.60), and B (0.50). Generally, the elongation growth (including stem extension rate, hypocotyl length, or petiole length) under blue lights increased with the decreasing PPS values, showing the highest and lowest sensitivity for arugula and mustard, respectively. However, the elongation promoted by blue lights gradually became saturated once the PPS values decreased below 0.60, a level which deactivates phytochrome. Other plant traits, such as biomass allocation and plant color, varied with increasing shade-avoidance responses to blue lights with decreasing PPS values relative to R, and these traits reached saturation at a similar PPS value as elongation. The response sensitivity was highest in elongation growth for arugula and cabbage, and highest in plant color for kale and mustard. This suggests that deactivated phytochrome contributes to the maximum elongation promotion as a shade-avoidance response induced by blue light, although the response sensitivity varies with plant traits and species.
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Duan, Gaohui, Zhongming Wen, Wei Xue, Yuankun Bu, Jinxin Lu, Bojin Wen, Boheng Wang et Sihui Chen. « Agents Affecting the Plant Functional Traits in National Soil and Water Conservation Demonstration Park (China) ». Plants 11, no 21 (28 octobre 2022) : 2891. http://dx.doi.org/10.3390/plants11212891.

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Plant functional traits (PFTs) can reflect the response of plants to environment, objectively expressing the adaptability of plants to the external environment. In previous studies, various relationships between various abiotic factors and PFTs have been reported. However, how these factors work together to influence PFTs is not clear. This study attempted to quantify the effects of topographic conditions, soil factors and vegetation structure on PFTs. Four categories of variables were represented using 29 variables collected from 171 herb plots of 57 sites (from different topographic and various herb types) in Xindian SWDP. The partial least squares structural equation modeling showed that the topographic conditions and soil properties also have a direct effect on plant functional traits. Among the topographic conditions, slope (SLO) has the biggest weight of 0.629, indicating that SLO contributed the most to plant functional traits and vegetation structure. Among soil properties, maximum water capacity (MWC) contributes the most and is followed by soil water content (SWC), weighted at 0.588 and 0.416, respectively. In a word, the research provides new points into the quantification of the correlation between different drivers that may be important for understanding the mechanisms of resource utilization, competition and adaptation to the environment during plant recovery.
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Maharajan, Theivanayagam, Thumadath Palayullaparambil Ajeesh Krishna, Kasinathan Rakkammal, Muthusamy Ramakrishnan, Stanislaus Antony Ceasar, Manikandan Ramesh et Savarimuthu Ignacimuthu. « Identification of QTL Associated with Agro-Morphological and Phosphorus Content Traits in Finger Millet under Differential Phosphorus Supply via Linkage Mapping ». Agriculture 13, no 2 (20 janvier 2023) : 262. http://dx.doi.org/10.3390/agriculture13020262.

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Finger millet (Eleusine coracana (L.) Gaertn.) is one of the most important cereal crops for people in Asia and Africa. It supplies energy and nutrients for all people, particularly poor people in these continents. Phosphorus (P) is an essential macronutrient for plant growth and grain quality, so an adequate amount of P is required for healthy plant life. There is considerable evidence that P deficiency affects the growths and yields of all cereals, including finger millet. The present study aimed at identifying the quantitative trait loci (QTL) for various agro-morphological and P-content traits under low P (LP) and high P (HP) conditions through linkage mapping. Two cultivars, IE-2606 (low-P-susceptible) and PR-202 (low-P-tolerant) were used to develop 100 recombinant inbred lines (RILs). In total, 55 QTL, associated with various agro-morphological (primary root length (PRL), shoot fresh weight (SFW), root fresh weight (RFW), shoot dry weight (SDW), root dry weight (RDW), and root hair density (RHD)) and P-content traits (inorganic phosphate content in shoots (PiS), inorganic phosphate content in roots (PiR), and total P content in shoots (TPS)) were detected under LP conditions. Similarly, 37 QTL for various agro-morphological (PRL, RFW, SDW, and root hair length (RHL)) and P-content traits (PiS, PiR, TPS, and total P content in roots (TPR)) were detected under HP conditions. Biotic and abiotic stress-responsive candidate genes linked to a few QTL were also identified. The identified QTL associated with agro-morphological and P-content traits in finger millet under P deficiency could be used in breeding programs to develop finger millet with better P use efficiency (PUE). Furthermore, improving finger millet growth and yield under LP soil will help to reduce Pi application and eutrophication, which may help to improve the lives of poor farmers and maintain sustainable environments in Asia and African countries.
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35

Uikey, Shivani, Stuti Sharma, M. K. Shrivastava et Pawan K. Amrate. « Study of principal component analyses for pod traits in soybean ». INTERNATIONAL JOURNAL OF AGRICULTURAL SCIENCES 17, no 2 (15 juin 2021) : 341–49. http://dx.doi.org/10.15740/has/ijas/17.2/341-349.

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Yield being a complex entity influenced by several components and environments. PCA is a well-known method of dimension reduction that can be used to reduce a large set of variables to a small set that still contains most of the information in the large set (Massay, 1965 and Jolliffie, 1986). In present study, PCA preformed for pod and yield traits revealed that out of fourteen, only five principal components (PCs) exhibited more than 1.0 eigen value and showed about 70.44% total variability among the traits. PC1 showed 23.83% variability with eigen value 3.33 indicating the maximum variation in comparison to other four PCs. The PC1 was more related to traits viz., days to 50% flowering, total number of pods per plant, number of seeds per plant, biological yield per plant and seed yield per plant. Thus, PC1 allowed for simultaneous selection of yield related traits and it can be regarded as yield factor. PC2 exhibited positive effect for days to maturity, number of primary branches per plant and number of nodes per plant, The PC3 was more related to number of two seeded pods per plant, 100 seed weight and harvest index traits, whereas PC4 was more loaded with three seeded pods per plant. PC5 was more related to plant height and number of one seeded pods per plant. A high value of PC score of a particular advanced line in a particular PC denotes high value for those variables. Genotypes namely KS 103, JS 20-15, PS 1423, Cat 1957, Cat 1958, JS 20-06 and JS 20-66 can be considered an ideotype breeding material for selection and for further utilization in precise breeding programme.
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Azeem, Ahmad, Mai Wenxuan, Tian Changyan, Qaiser Javed et Adeel Abbas. « Competition and Plant Trait Plasticity of Invasive (Wedelia trilobata) and Native Species (Wedelia chinensis, WC) under Nitrogen Enrichment and Flooding Condition ». Water 13, no 23 (6 décembre 2021) : 3472. http://dx.doi.org/10.3390/w13233472.

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Nitrogen (N) is the important nutrition that regulatory plant functioning and environmental stability of invasive plant species under flooding (F) conditions. Little information clarifies the role of nitrogen enrichment and flooding on the invasive plant functional traits and competition with native competitors. Plant functional traits play an essential role in the successful growth of plants under different environmental conditions. Therefore, greenhouse pots experiment was conducted with invasive plant species (Wedelia trilobata, WT), and its native competitor (Wedelia chinensis, WC) in monoculture and cocultivation culture, along with flooding and nitrogen enrichment conditions. Considering the impact of flooding (F) and nitrogen (N) on an individual basis, the plant physiological traits of WC were nonsignificant compared to that of WT. However, in the combination of flooding × additional nitrogen (F.N, F.2N), plant physiological traits of WT were comparatively higher than those of WC, especially in cocultivation. In flooding × additional nitrogen (F.N and F.2N), better phenotypic plasticity at different plant traits makes WT more dominant in resource competition over WC. In conclusion, improved functional traits of WT under nitrogen enrichment and flooding conditions enhanced its competitiveness over native competitors.
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37

Fernández-Baca, Cristina P., Adam R. Rivers, Jude E. Maul, Woojae Kim, Ravin Poudel, Anna M. McClung, Daniel P. Roberts, Vangimalla R. Reddy et Jinyoung Y. Barnaby. « Rice Plant–Soil Microbiome Interactions Driven by Root and Shoot Biomass ». Diversity 13, no 3 (15 mars 2021) : 125. http://dx.doi.org/10.3390/d13030125.

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Plant–soil microbe interactions are complex and affected by many factors including soil type, edaphic conditions, plant genotype and phenotype, and developmental stage. The rice rhizosphere microbial community composition of nine recombinant inbred lines (RILs) and their parents, Francis and Rondo, segregating for root and shoot biomass, was determined using metagenomic sequencing as a means to examine how biomass phenotype influences the rhizosphere community. Two plant developmental stages were studied, heading and physiological maturity, based on root and shoot biomass growth patterns across the selected genotypes. We used partial least squares (PLS) regression analysis to examine plant trait-driven microbial populations and identify microbial species, functions, and genes corresponding to root and shoot biomass as well as developmental stage patterns. Species identified correlated with increases in either root or shoot biomass were widely present in soil and included species involved in nitrogen cycling (Anaeromyxobacter spp.) and methane production (Methanocellaavoryzae), as well as known endophytes (Bradyrhizobium spp.). Additionally, PLS analysis allowed us to explore the relationship of developmental stage with species, microbial functions, and genes. Many of the community functions and genes observed during the heading stage were representative of cell growth (e.g., carbohydrate and nitrogen metabolism), while functions correlated with physiological maturity were indicative of cell decay. These results are consistent with the hypothesis that microbial communities exist whose metabolic and gene functions correspond to plant biomass traits.
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38

Araújo, Adelson Paulo, Aurélio Magno Fernandes, Flavio Yuudi Kubota, Felipe Costa Brasil et Marcelo Grandi Teixeira. « Sample size for measurement of root traits on common bean by image analysis ». Pesquisa Agropecuária Brasileira 39, no 4 (avril 2004) : 313–18. http://dx.doi.org/10.1590/s0100-204x2004000400003.

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Evaluation of root traits may be facilitated if they are assessed on samples of the root system. The objective of this work was to determine the sample size of the root system in order to estimate root traits of common bean (Phaseolus vulgaris L.) cultivars by digital image analysis. One plant was grown per pot and harvested at pod setting, with 64 and 16 pots corresponding to two and four cultivars in the first and second experiments, respectively. Root samples were scanned up to the completeness of the root system and the root area and length were estimated. Scanning a root sample demanded 21 minutes, and scanning the entire root system demanded 4 hours and 53 minutes. In the first experiment, root area and length estimated with two samples showed, respectively, a correlation of 0.977 and 0.860, with these traits measured in the entire root. In the second experiment, the correlation was 0.889 and 0.915. The increase in the correlation with more than two samples was negligible. The two samples corresponded to 13.4% and 16.9% of total root mass (excluding taproot and nodules) in the first and second experiments. Taproot stands for a high proportion of root mass and must be deducted on root trait estimations. Samples with nearly 15% of total root mass produce reliable root trait estimates.
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39

Moore, Virginia, Brian Davis, Megan Poskaitis, Jude E. Maul, Lisa Kissing Kucek et Steven Mirsky. « Phenotypic and Nodule Microbial Diversity among Crimson Clover (Trifolium incarnatum L.) Accessions ». Agronomy 10, no 9 (21 septembre 2020) : 1434. http://dx.doi.org/10.3390/agronomy10091434.

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Crimson clover (Trifolium incarnatum L.) is the most common legume cover crop in the United States. Previous research found limited genetic variation for crimson clover within the National Plant Germplasm System (NPGS) collection. The aim of this study was to assess the phenotypic and nodule microbial diversity within the NPGS crimson clover collection, focusing on traits important for cover crop performance. Experiments were conducted at the Beltsville Agricultural Research Center (Maryland, USA) across three growing seasons (2012–2013, 2013–2014, 2014–2015) to evaluate 37 crimson clover accessions for six phenotypic traits: fall emergence, winter survival, flowering time, biomass per plant, nitrogen (N) content in aboveground biomass, and proportion of plant N from biological nitrogen fixation (BNF). Accession effect was significant across all six traits. Fall emergence of plant introductions (PIs) ranged from 16.0% to 70.5%, winter survival ranged from 52.8% to 82.0%, and growing degree days (GDD) to 25% maturity ranged from 1470 GDD to 1910 GDD. Biomass per plant ranged from 1.52 to 6.51 g, N content ranged from 1.87% to 2.24%, and proportion of plant N from BNF ranged from 50.2% to 85.6%. Accessions showed particularly clear differences for fall emergence and flowering time, indicating greater diversity and potential for selection in cover crop breeding programs. Fall emergence and winter survival were positively correlated, and both were negatively correlated with biomass per plant and plant N from BNF. A few promising lines performed well across multiple key traits, and are of particular interest as parents in future breeding efforts, including PIs 369045, 418900, 561943, 561944, and 655006. In 2014–2015, accessions were also assessed for nodule microbiome diversity, and 11 genera were identified across the sampled nodules. There was large variation among accessions in terms of species diversity, but this diversity was not associated with observed plant traits, and the functional implications of nodule microbiome diversity remain unclear.
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40

Yaseen, Muhammad, Wenxing Long, Farhan Khalid, Saraj Bahadur et Hamza Armghan Noushahi. « Shifts in Community Vegetative Organs and Their Dissimilar Trade-Off Patterns in a Tropical Coastal Secondary Forest, Hainan Island, Southern China ». Diversity 14, no 10 (30 septembre 2022) : 823. http://dx.doi.org/10.3390/d14100823.

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The ecology of functional features highlights the importance of the leaf economic spectrum (LES) in understanding plant trade-offs between conservative and commercial resource use. However, it is still unclear whether changes in the plant attributes of various vegetative organs can be altered and whether the plant economic spectrum (PES) is categorized by multiple vegetative organs. We investigated a total of 12 functional features of 174 woody tree species, with leaf and stem attributes, on Hainan Island. We used principal component analysis (PCA) to analyze the changes in attributes and connections to understand how the plant trade-offs differ. We detected that stem organic matter (SOM) and stem organic carbon (SOC) contributed most to the first principal component, followed by leaf organic matter (LOM) and leaf organic carbon (LOC). Using Spearman correlation analysis, we determined that leaf total nitrogen (LTN) and specific leaf area (SLA), LTN and leaf total phosphorus (LTP), and finally stem total nitrogen (STN) and stem total phosphorus (STP) were positively significantly correlated. These significant variations in the traits of nutrients are regulated, while the morphological traits of aboveground vegetative organs are diverse. The coexistence of species and community assembly can increase our knowledge on the tropical coastal secondary forests. Furthermore, our outcomes can help us to better understand the restoration of habitats and green infrastructure design, suggesting that selecting different species across multiple trait axes can help ensure functionality at the maximum level.
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41

Hoffman, D. D., B. W. Diers, G. L. Hartman, C. D. Nickell, R. L. Nelson, W. L. Pedersen, E. R. Cober et al. « Selected Soybean Plant Introductions with Partial Resistance to Sclerotinia sclerotiorum ». Plant Disease 86, no 9 (septembre 2002) : 971–80. http://dx.doi.org/10.1094/pdis.2002.86.9.971.

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Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, is a major soybean (Glycine max) disease in north-central regions of the United States and throughout the world. Current sources of resistance to Sclerotinia stem rot express partial resistance, and are limited in number within soybean germ plasm. A total of 6,520 maturity group (MG) 0 to IV plant introductions (PIs) were evaluated for Sclerotinia stem rot resistance in the United States and Canada in small plots or in the greenhouse from 1995 to 1997. Selected PIs with the most resistance were evaluated for resistance in the United States and Canada in replicated large plots from 1998 to 2000. The PIs in the MG I to III tests in Urbana, IL were evaluated for agronomic traits from 1998 to 2000. The selected PIs also were evaluated with an excised leaf inoculation and petiole inoculation technique. After the 1995 to 1997 evaluations, all but 68 PIs were eliminated because of their susceptibility to Sclerotinia stem rot. In field tests in Urbana, higher disease severity in selected MG I to III PIs was significantly (P< 0.05) associated with taller plant heights and greater canopy closure. All other agronomic traits evaluated were not associated or were inconsistently associated with disease severity. MG I to III PIs 153.282, 189.931, 196.157, 398.637, 417.201, 423.818, and 561.331 had high levels of resistance and had canopies similar to the resistant checks. The resistance ratings from the petiole inoculation technique had a high and significant (P< 0.01) correlation with disease severity in the MG I and II field tests. The partially resistant PIs identified in this study can be valuable in incorporating Sclerotinia stem rot resistance into elite germ plasm.
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42

Solomon, Juan K. Q. « Characterization of Adult Functional Traits of Local Populations and Cultivars of Sandberg Bluegrass and Bottlebrush Squirreltail Perennial Bunchgrasses ». Plants 8, no 6 (11 juin 2019) : 166. http://dx.doi.org/10.3390/plants8060166.

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Plant functional traits offer an understanding of the plant’s ability to cope with varying environmental impositions. The objective of this study was to evaluate the above and belowground adult morphological and chemical composition traits of local populations of Sandberg bluegrass (Poa secunda J. Presl) and Bottlebrush squirreltail (Elymus elymoides (Raf.) Swezey) collected in Nevada and their cultivated varieties. A total of six replications (one seedling each) from each population and cultivar of the two native perennial bunchgrasses were used in a randomized complete block design experiment. Each of the six seedlings from each sourced population was transplanted into individual tree pots (28 cm diameter × 61 cm height) containing 20.4 kg of air-dried Orr gravelly sandy loam soil in mid-November, 2015 and remained in the pots for the duration of the study (23 June, 2016). Traits evaluated were, plant height, leaf length, inflorescence length, shoot biomass, forage nutritive value, root morphological traits, and root carbon and nitrogen content. Traits means were considered different at P < 0.05. For Sandberg bluegrass, the cultivar ‘Mountain Home’ and the population from Panther Valley tended to have greater biomass than the population from Button Point but overall, the average of the two cultivars (10.8 g/plant) did not differ in shoot biomass relative to the local populations (7.6 g/plant). For squirreltail, plant height for the George St. Sonoma and Grass Valley populations (71.3 cm) was greater than the cultivars ‘Toe Jam Creek’ and ‘Vale’ (40.5 cm) but cultivars had greater biomass (12.6 g/plant) than the local populations (5.8 g/plant). Total root length and root diameter were not different among the Sanberg bluegrass and squirreltail populations. The results from traits expounded on in this study indicate the closeness of these populations for both species at their adult stage and provide insights for building a unified framework approach among the different agencies and restoration practitioners to aid in plant assemblages for restoration success in the Great Basin and beyond.
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43

Ohsowski, Brian M., Kari E. Dunfield, John N. Klironomos et Miranda M. Hart. « Improving plant biomass estimation in the field using partial least squares regression and ridge regression ». Botany 94, no 7 (juillet 2016) : 501–8. http://dx.doi.org/10.1139/cjb-2016-0009.

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Estimating primary productivity over time is challenging for plant ecologists. The most accurate biomass measurements require destructive sampling and weighing. This is often not possible for manipulative studies that involve repeated measures over time, or for studies in protected areas. Estimates of aboveground plant biomass using allometric equations or linear regression on single plant traits have been used, but tend to have poor predictability both within and across systems, or are limited to specific plant taxa. Here we estimate aboveground plant biomass using multiple collinear plant traits to generate a standard curve specific to the site of interest. Partial least squares regression (PLS) and ridge regression (RR), addressing predictor collinearity, are robust, highly accurate statistical methods to estimate plant biomass across gross differences in plant morphology and growth habit.
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44

Dambreville, Anaëlle, Mélanie Griolet, Gaëlle Rolland, Myriam Dauzat, Alexis Bédiée, Crispulo Balsera, Bertrand Muller, Denis Vile et Christine Granier. « Phenotyping oilseed rape growth-related traits and their responses to water deficit : the disturbing pot size effect ». Functional Plant Biology 44, no 1 (2017) : 35. http://dx.doi.org/10.1071/fp16036.

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Following the recent development of high-throughput phenotyping platforms for plant research, the number of individual plants grown together in a same experiment has raised, sometimes at the expense of pot size. However, root restriction in excessively small pots affects plant growth and carbon partitioning, and may interact with other stresses targeted in these experiments. In work reported here, we investigated the interactive effects of pot size and soil water deficit on multiple growth-related traits from the cellular to the whole-plant scale in oilseed rape (Brassica napus L.). The effects of pot size on responses to water deficit and allometric relationships revealed strong, multilevel interactions between pot size and watering regime. Notably, water deficit increased the root : shoot ratio in large pots, but not in small pots. At the cellular scale, water deficit decreased epidermal leaf cell area in large pots, but not in small pots. These results were consistent with changes in the level of endoreduplication factor in leaf cells. Our study illustrates the disturbing interaction of pot size with water deficit and raises the need to carefully consider this factor in the frame of the current development of high-throughput phenotyping experiments.
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45

Pandini, Fábio, Natal Antonio Vello et Ângela Celis de Almeida Lopes. « Heterosis in soybeans for seed yield components and associated traits ». Brazilian Archives of Biology and Technology 45, no 4 (décembre 2002) : 401–12. http://dx.doi.org/10.1590/s1516-89132002000600001.

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The objective of this research was to quantify heterosis of agronomic traits and evaluate direct and indirect correlations among seed yield and other traits. A diallel involving six parents was grown in two localities. Seed yield (PG), one-hundred seed weight (PCS), number of pods per plant (NV), weight of aerial part of the plant (PPA), harvest index (IC) and number of seeds per pod (NGV) were evaluated. Positive values of heterosis were detected for all traits. Estimates of heterosis components were significative for most traits, showing effects of aditivity and dominance. The specific heterosis was more important than the variety heterosis, mainly in the locality Anhembi. MTBR-95-123800 presented the best potential per se and as parent in crosses, but it was excelled by some of the hybrids in the two localities. Number of pods per plant demonstrated to be suitable for indirect selection for PG.
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46

Hackl, Harald, Bodo Mistele, Yuncai Hu et Urs Schmidhalter. « Spectral assessments of wheat plants grown in pots and containers under saline conditions ». Functional Plant Biology 40, no 4 (2013) : 409. http://dx.doi.org/10.1071/fp12208.

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Spectral measurements allow fast nondestructive assessment of plant traits under controlled greenhouse and close-to-field conditions. Field crop stands differ from pot-grown plants, which may affect the ability to assess stress-related traits by nondestructive high-throughput measurements. This study analysed the potential to detect salt stress-related traits of spring wheat (Triticum aestivum L.) cultivars grown in pots or in a close-to-field container platform. In two experiments, selected spectral indices assessed by active and passive spectral sensing were related to the fresh weight of the aboveground biomass, the water content of the aboveground biomass, the leaf water potential and the relative leaf water content of two cultivars with different salt tolerance. The traits were better ascertained by spectral sensing of container-grown plants compared with pot-grown plants. This may be due to a decreased match between the sensors’ footprint and the plant area of the pot-grown plants, which was further characterised by enhanced senescence of lower leaves. The reflectance ratio R760 : R670, the normalised difference vegetation index and the reflectance ratio R780 : R550 spectral indices were the best indices and were significantly related to the fresh weight, the water content of the aboveground biomass and the water potential of the youngest fully developed leaf. Passive sensors delivered similar relationships to active sensors. Across all treatments, both cultivars were successfully differentiated using either destructively or nondestructively assessed parameters. Although spectral sensors provide fast and qualitatively good assessments of the traits of salt-stressed plants, further research is required to describe the potential and limitations of spectral sensing.
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47

ROSTAMI, L., H. SADEGHI et S. HOSSEINI. « Response of Caper Plant to Drought and Different Ratios of Calcium and Sodium Chloride1 ». Planta Daninha 34, no 2 (juin 2016) : 259–66. http://dx.doi.org/10.1590/s0100-83582016340200007.

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ABSTRACT Caper (Capparis spinosa) is used as multipurpose and adaptable plant which provides a valuable opportunity to enhance greenery in harsh climatic areas. This plant like the others is affected by drought and sodium chloride stresses as the most common abiotic stresses worldwide. This study was carried out to determine the interaction between drought and different ratios of sodium and calcium chloride on caper. Droughts stress were two levels of 100 and 75% of field capacity and were applied based on the daily weighting method of pots. Salt treatments were four different ratios of calcium chloride: sodium chloride (1:0, 1:1, 1:3, 1:5]. Treatments started when the plants were sown in the pots. Results indicated that higher ratios of calcium chloride than sodium chloride which caused salinity stress have destructive effect on water relationships and contents of the caper. This stress affected growth, morphological, and physiological function related traits in a negative way. Growth and other traits decreased under water deficit conditions. It seems that interaction between salinity and drought had the most destructive effect on this plant and decreasing its quality and quantity of its traits.
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48

Jain, Santosh. « Autokinesis and Personality ». Perceptual and Motor Skills 60, no 3 (juin 1985) : 963–70. http://dx.doi.org/10.2466/pms.1985.60.3.963.

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The relationships of autokinesis to personality traits for 40 undergraduate students of Delhi University is described. Eight response measures were taken from the subjects on an apparatus that permitted recording of the apparent motion of the autokinetic stimulus in the same plane as the light source. Personality traits of suggestibility, perseveration, oscillation, and personality dimensions were respectively assessed by body-sway test, Necker's Cube, perseveration test, and the MMPI. Analysis indicates no significant relationships between autokinetic phenomena and the various personality traits.
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49

Vu, Hang T. T., A. T. James, R. J. Lawn, L. M. Bielig et A. Kilian. « Use of DArT molecular markers for QTL analysis of drought-stress responses in soybean. I. Phenotypic evaluation of traits ». Crop and Pasture Science 66, no 8 (2015) : 802. http://dx.doi.org/10.1071/cp14303.

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Physiological drought stress responses were assessed in recombinant inbred lines (RILs) from three soybean (Glycine max (L.) Merr.) crosses, in preparation for quantitative trait locus (QTL) analyses using Diversity Arrays Technology (DArT) markers. The three RIL populations were derived from pairwise crosses between three genotypes, cv. Valder, CPI 26671 and G2120, which in previous studies had differed in drought-stress response. Of particular interest was the landrace variety G2120, which in the previous reports had recovered better after severe drought. To assess drought-stress response, the plants were grown in deep cylindrical pots in the glasshouse and exposed to severe water deficit followed by re-watering. Two plants to be genotyped were grown in each pot, together with one plant of G2120, which served as a reference plant against which the responses of the two other plants were assessed. Traits recorded included measures of relative water content (RWC), epidermal conductance (ge) and recovery in growth following re-watering. The responses in the reference and parental plants and the RIL populations were broadly consistent with previous studies. As plant-available water in the soil declined, both RWC and ge declined, although the relation between RWC and ge was exponential, rather than linear as in previous studies. Analysis of variance revealed large environmental effects on most of the traits, which resulted in high coefficients of variation and low estimates of broad-sense heritability. However, there were significant differences at both the population and genotype levels for all key traits, confirming the presence of genetic variation for drought-stress response. Some opportunities for enhancing the observed genetic differences and reducing the environmental noise in future studies are canvassed. Application of the observed phenotypic data reported in this paper in subsequent QTL analyses based on DArT markers is reported in the companion paper.
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Khan, Mueen Alam, Hafiz Muhammad Faisal Umer, Muhammad Iqbal, Abdul Rehman et Waqas Shafqat Chattha. « Evaluation of high-yielding wheat (Triticum aestivum L.) varieties under water limitation ». Plant Genetic Resources : Characterization and Utilization 19, no 3 (27 avril 2021) : 245–51. http://dx.doi.org/10.1017/s1479262121000290.

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AbstractDrought tolerance is a highly complex trait and one of the important components of yield stability in wheat. An experiment was therefore conducted to study the drought tolerance status of 14 high-yielding wheat varieties based on morphological characteristics under a randomized complete block design following factorial arrangement with three replications. Variety × Treatment × Year interactions of wheat genotypes were studied for various morphological traits under normal and drought stress conditions for 2 years in plants grown in pots. Significant differences were observed among the 14 varieties of wheat. Sutlej-86 was found to be highly affected by drought, with maximum reductions in plant height, spike length and number of spikelets/spike. The variety with the maximum tolerance to drought was Bahawalpur-97; this variety also had the lowest reductions in the number of fertile tillers/plant, the number of spikelets/spike, spike weight, the number of grains/spike, 1000-grain weight, grain yield/spike, total biomass and stress susceptibility and tolerance indices. Stronger correlations among the studied attributes under drought stress over normal conditions further highlighted drought stress adversities. The studied traits are thus recognized as drought tolerance indicators for varietal selection, and varieties showing less reduction under drought could be used as a standard check in breeding programmes to identify lineages with drought tolerance and could be recommended for drought-stressed areas.
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