Dynamic Simulation of the Leaf Mass per Area (LMA) in Multilayer Crowns of Young Larix principis-rupprechtii.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model.

Intraspecific variation in fine-root traits is larger than in aboveground traits in European herbaceous species regardless of drought.

Differences within species (Intraspecific trait variation - ITV) contribute substantially to overall trait variability and environmental harshness can reduce among-species variation. While aboveground traits have received considerable attention, knowledge about ITV in fine-root traits and how it differs from ITV in aboveground traits remains limited. This study examined the partitioning of trait variation aboveground and fine-root traits in 52 European herbaceous species and how such proportions change in response to drought, offering valuable insights for accurate functional species characterization and inter-species comparisons. We studied seven morphological aboveground and fine-root traits under drought and well-watered conditions in a greenhouse experiment. Linear mixed effect models and permutational multivariate analysis of variance (PERMANOVA) were employed to decompose trait variation, ensuring the robustness of our results. We also calculated variance partitioning for the combination of aboveground traits and the combination of fine-root traits, as well as pairs of analogous leaf and fine-root traits (i.e., traits that fulfill similar functions) for each treatment (control and drought). Among-species trait differences explained a greater proportion of overall variance than within-species variation, except for root dry matter content (RDMC). Height and leaf area stood out, with species' identity accounting for 87-90% of total trait variation. Drought had no significant effect on the proportions of variation in any of the traits. However, the combination of fine-root traits exhibited higher intraspecific variability (44-44%) than aboveground traits (19-21%) under both drought and control. Analogous root traits also showed higher ITV (51-50%) than analogous leaf traits (27-31%). Our findings highlight substantial within-species variation and the nuanced responses of fine-root traits, particularly RDMC, suggesting root traits' flexibility to soil heterogeneity that fosters less differentiation among species. Among-species trait differences, especially aboveground, may underscore distinct strategies and competitive abilities for resource acquisition and utilization. This study contributes to elucidate the mechanisms underlying the multifunctionality of the above- and belowground plants compartments.

Rootstock vigor dictates the canopy light environment that regulates metabolite profile and internal fruit quality development in peach.

Five rootstock cultivars of differing vigor: vigorous ('Atlas™' and 'Bright's Hybrid® 5'), standard ('Krymsk® 86' and 'Lovell') and dwarfing ('Krymsk® 1') grafted with 'Redhaven' as the scion were studied for their impact on productivity, mid-canopy photosynthetic active radiation transmission (i.e., light availability) and internal fruit quality. Αverage yield (kg per tree) and fruit count increased significantly with increasing vigor (trunk cross sectional area, TCSA). Α detailed peach fruit quality analysis on fruit of equal maturity (based on the index of absorbance difference, IAD) coming from trees with equal crop load (no. of fruit cm-2 of TCSA) characterized the direct impact of rootstock vigor on peach internal quality [dry matter content (DMC) and soluble solids concentration (SSC)]. DMC and SSC increased significantly with decreasing vigor and increasing light availability, potentially due to reduced intra-tree shading and better light distribution within the canopy. Physiologically characterized peach fruit mesocarp was further analyzed by non-targeted metabolite profiling using gas chromatography mass spectrometry (GC-MS). Metabolite distribution was associated with rootstock vigor class, mid-canopy light availability and fruit quality characteristics. Fructose, glucose, sorbose, neochlorogenic and quinic acids, catechin and sorbitol were associated with high light environments and enhanced quality traits, while sucrose, butanoic and malic acids related to low light conditions and inferior fruit quality. These outcomes show that while rootstock genotype and vigor are influencing peach tree productivity and yield, their effect on manipulating the light environment within the canopy also plays a significant role in fruit quality development.

Genome-wide association study for stalk lodging resistance related traits in maize (Zea mays L.).

BACKGROUND: The stalk traits stalk diameter, stalk length, rind penetrometer resistance and dry matter content are important indicators for measuring lodging resistance. RESULTS: In this study, 377 inbred lines were used as the basic materials, and four stalk-related traits including stalk diameter, stalk length, rind penetrometer resistance and dry matter content of the third segment of maize, were investigated at the tasseling, grain filling, and maturity stages. 461,053 high-quality SNPs which were obtained by whole genome resequencing were used for genome-wide association study. As a result of mixed linear model analysis (P < 9.77 × 10-6), 29 significant SNPs related to traits were detected, accounting for 7.19% -15.03% of phenotypic variation, among which 4, 1, 4 and 20 SNPs were found related to rind penetrometer resistance, stalk diameter, stalk length, and dry matter content respectively. Most candidate genes are related to plant element structure, signal transduction mechanisms, inorganic ion transport and metabolism, nucleotide transport and metabolism, and transporter enzyme families. Comparing mixed linear model with generalized linear model, a total of 12 candidate genes were detected repeatedly, during which the candidate gene Zm00001d014449 were detected 5 times, with a phenotypic variation interpretation rate of 9.95% -10.84%. This gene is mainly expressed in cells with active cell division and tissue differentiation, and is involved in the formation of stalk vascular bundles and the synthesis of cell walls. Another candidate gene, Zm00001d005300, encodes the transcription factor MYB44, which regulates the dependence of salt stress signal phosphorylation, can effectively inhibit the accumulation of destructive reactive oxygen species, and has a certain resistance to non-biotic stress. In addition, this study also found that 10 unknown functional genes can be further Functional verification. CONCLUSIONS: This study helps to deepen the understanding of the genetic basis of traits related to maize stalk lodging resistance, and provides theoretical guidance for future maize lodging resistance breeding.

The comparison of dispersal rate between invasive and native species varied by plant life form and functional traits.

A long dispersal distance is widely used to indicate high invasiveness, but it ignores the temporal dimensions of plant invasion. Faster dispersal rates (= distance/time) of invasive species than native ones have been widely used in modeling species invasion and planning control management. However, the comparison of dispersal rate between invasive and native plants, particularly for dispersal on a local or landscape scale, has not been tested with a comprehensive dataset. Moreover, both the effects of plant functional traits on the dispersal rate and variation in the functional-trait effects between invasive and native plants remain elusive. Compiling studies from 30 countries globally, we compared seed dispersal rates (km/year) on a local or landscape scale between 64 observations of invasive and 78 observations of native plants given effects of plant life forms, disturbance levels, and measurement methods. Furthermore, we compared the effects of functional traits on dispersal rate between invasive and native species. We found that: (1) Trait values were similar between the invasive and native plants except for the greater height of woody native plants than woody invasive ones; (2) Compared within the same plant life form, the faster dispersal rates of invasive species were found in herbaceous plants, not in woody plants, and disturbance level and measurement methods did not affect the rate comparison; (3) Plant height and seed length had significant effects on dispersal rates of both invasive and native plants, but the effect of leaf dry matter content (LDMC) was only significant on herbaceous invasive plants. The comparison of dispersal rate between invasive and native plants varied by plant life form. The convergent values but divergent dispersal effects of plant traits between invasive and native species suggest that the trait effects on invasiveness could be better understood by trait association with key factors in invasiveness, e.g., dispersal rate, than the direct trait comparison between invasive and native plants.

Leaf functional diversity and environmental filtering in a tropical dry forest: Comparison between two geological substrates.

The role of geological substrate in shaping plant community functional diversity remains poorly understood. Considering the involvement of leaves in the energy, water, and nutrient economics of plants, we hypothesized that leaves experience geology-related filtering, which in turn shapes their functional attributes and community leaf functional diversity on different substrates. We studied tropical dry forest communities on limestone and siliciclastic phyllite-derived soils, comparing their functional diversity and soil physico-chemical properties. We predicted the most benign habitat (less severe filter) to be associated with higher leaf functional diversity and an acquisitive strategy prevalence, while the more stressful habitat should show conservative leaf traits and lower leaf functional diversity. We measured six traits in 31 common tree species (representing ~80% of community crown cover): leaf area, specific leaf area, leaf thickness, leaf dry matter content, petiole length, and leaf blade narrowness. Leaf functional diversity was assessed through the functional trait dispersion metric. Intraspecific functional variation was examined in 25 species shared between substrates. The limestone substrate was more fertile (higher phosphorous) with higher water retention, while phyllite had higher nitrogen and lower humidity. Principal component analysis segregated plots by substrate, with limestone plots being more clustered. Community leaf functional diversity was higher in the limestone forest. Most species examined showed inter-substrate trait differences in at least one leaf functional trait. The two substrates constituted distinct growth environments, with the more benign substrate associated with higher community leaf functional diversity. The intraspecific analysis revealed the prevalence of acquisitive traits in the more benign and more conservative traits in the more stressful habitat. This study advances our understanding of the role of geological substrate as an environmental filter in tropical dry forests, influencing leaf functional responses and emphasizing the importance of intraspecific functional variation.

Development and validation of near-infrared spectroscopy procedures for prediction of cassava root dry matter and amylose contents in Ugandan cassava germplasm.

BACKGROUND: Cassava utilization for food and/or industrial products depends on inherent properties of root dry matter content (DMC) and the starch fraction of amylose content (AC). Accordingly, in the present study, near-infrared reflectance spectroscopy (NIRS) models were developed to aid breeding and selection of DMC and AC as critical industrial traits taking care of root sample preparation and cassava germplasm diversity available in Uganda. RESULTS: Upon undertaking calibrations and cross-validations, best models were adopted for validation. DMC in calibration samples ranged from 20 to 45 g 100g-1 , whereas, for amylose content, it ranged from 14 to 33 g 100g-1 . In the validation set, average DMC was 29.5 g 100g-1 , whereas, for amylose content, it was 24.64 g 100g-1 . For DMC, a modified partial least square regression model had regression coefficients (R2 ) of 0.98 and 0.96, respectively, in the calibration and validation set. These were also associated with low bias (-0.018) and ratio of performance deviation that ranged from 4.7 to 5.0. In addition, standard error of prediction values ranged from 0.9 g 100g-1 to 1.06 g 100g-1 . For AC, the regression coefficient was 0.91 for the calibration set and 0.94 for the validation set. A bias equivalent to -0.03 and a ratio of performance deviation of 4.23 were observed. CONCLUSION: These findings confirm the robustness of NIRS in the estimation of dry matter content and amylose content in cassava roots and thus justify its use in routine cassava breeding operations. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The Interplay of Physiological and Biochemical Response to Short-Term Drought Exposure in Garlic (Allium sativum L.).

The impacts of global climate change and a rapid increase in population have emerged as major concerns threatening global food security. Environmental abiotic stress, such as drought, severely impairs plants' morphology, physiology, growth, and yield more than many other environmental factors. Plants use a complex set of physiological, biochemical, and molecular mechanisms to combat the negative effects caused by drought-induced stress. The aim of this study was to investigate morphological, spectral, physiological, and biochemical changes occurring in 30 garlic accessions exposed to short-term drought stress in a greenhouse setting and to identify potential early drought-induced stress markers. The results showed that, on average, garlic plants exposed to drought conditions exhibited a decrease in assimilation, transpiration, and stomatal conductance of 39%, 52%, and 50%, respectively, and an average increase in dry matter and proline content of 10.13% and 14.29%, respectively. Nevertheless, a significant interaction between the treatment and accessions was observed in the investigated photosynthetic and biochemical parameters. The plants' early response to drought ranged from mild to strong depending on garlic accession. Multivariate analysis showed that accessions with a mild early drought response were characterized by higher values of assimilation, transpiration, and stomatal conductance compared to plants with moderate or strong early drought response. Additionally, accessions with strong early drought response were characterized by higher proline content, lipid peroxidation, and antioxidant capacity as measured by FRAP compared to accessions with mild-to-moderate early drought response.

Determinants of interspecific variation in season length of perennial herbs.

BACKGROUND AND AIMS: Perennial plants in seasonal climates need to optimize their carbon balance by adjusting their active season length to avoid risks of tissue loss under adverse conditions. As season length is determined by two processes, namely spring growth and senescence, it is likely to vary in response to several potentially contrasting selective forces. Here we aim to disentangle the cascade of ecological determinants of interspecific differences in season length. METHODS: We measured size trajectories in 231 species in a botanical garden. We examined correlations between their spring and autumn size changes and determined how they make up season length. We used structural equation models (SEMs) to determine how niche parameters and species traits combine in their effect on species-specific season length. KEY RESULTS: Interspecific differences in season length were mainly controlled by senescence, while spring growth was highly synchronized across species. SEMs showed that niche parameters (light and moisture) had stronger, and often trait-independent, effects compared to species traits. Several niche (light) and trait variables (plant height, clonal spreading) had opposing effects on spring growth and senescence. CONCLUSIONS: The findings indicate different drivers and potential risks in growth and senescence. The strong role of niche-based predictors implies that shifts in season length due to global change are likely to differ among habitats and will not be uniform across the whole flora.

Quantitative trait loci and candidate genes for physico-chemical traits related to tuber quality in greater yam (Dioscorea alata L.).

BACKGROUND: Starch, dry matter content (DMC), proteins, and sugars are among the major influences on yam tuber quality. Genetic improvement programs need simple, rapid, and low-cost tools to screen large populations. The objectives of this work were, using a quantitative trait loci mapping approach (QTL) on two diploid full-sib segregating populations, (i) to acquire knowledge about the genetic control of these traits; (ii) to identify markers linked to the genomic regions controlling each trait, which are useful for marker-assisted selection (MAS); (iii) to validate the QTLs on a diversity panel; and (iv) to identify candidate genes from the validated QTLs. RESULTS: Heritability for all traits was moderately high to high. Significant correlations were observed between traits. A total of 25 QTLs were identified, including six for DMC, six for sugars, six for proteins, and seven for starch. The phenotypic variance explained by individual QTLs ranged from 14.3% to 28.6%. The majority of QTLs were validated on a diversity panel, showing that they are not specific to the genetic background of the progenitors. The approximate physical location of validated QTLs allowed the identification of candidate genes for all studied traits. Those detected for starch content were mainly enzymes involved in starch and sucrose metabolism, whereas those detected for sugars were mainly involved in respiration and glycolysis. CONCLUSION: The validated QTLs will be useful for breeding programs using MAS to improve the quality of yam tubers. The putative genes should be useful in providing a better understanding of the physiological and molecular basis of these important tuber quality traits. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Comparing Machine Learning and PLSDA Algorithms for Durian Pulp Classification Using Inline NIR Spectra.

The aim of this study was to evaluate and compare the performance of multivariate classification algorithms, specifically Partial Least Squares Discriminant Analysis (PLS-DA) and machine learning algorithms, in the classification of Monthong durian pulp based on its dry matter content (DMC) and soluble solid content (SSC), using the inline acquisition of near-infrared (NIR) spectra. A total of 415 durian pulp samples were collected and analyzed. Raw spectra were preprocessed using five different combinations of spectral preprocessing techniques: Moving Average with Standard Normal Variate (MA+SNV), Savitzky-Golay Smoothing with Standard Normal Variate (SG+SNV), Mean Normalization (SG+MN), Baseline Correction (SG+BC), and Multiplicative Scatter Correction (SG+MSC). The results revealed that the SG+SNV preprocessing technique produced the best performance with both the PLS-DA and machine learning algorithms. The optimized wide neural network algorithm of machine learning achieved the highest overall classification accuracy of 85.3%, outperforming the PLS-DA model, with overall classification accuracy of 81.4%. Additionally, evaluation metrics such as recall, precision, specificity, F1-score, AUC ROC, and kappa were calculated and compared between the two models. The findings of this study demonstrate the potential of machine learning algorithms to provide similar or better performance compared to PLS-DA in classifying Monthong durian pulp based on DMC and SSC using NIR spectroscopy, and they can be applied in the quality control and management of durian pulp production and storage.

Plant water use related to leaf traits and CSR strategies of 10 common European green roof species.

The vegetation layer contributes to multiple functions of green roofs including their hydrological function as plants remove water from substrates between rainfall events through evapotranspiration, restoring the green roofs storage capacity for rainfall retention. While individual traits have been related to water use strategies of green roof plants, these traits are inconsistent, suggesting the importance of trait combinations which may be reflected in CSR (competitor, stress tolerator, ruderal) strategies. Therefore, relating plant water use to leaf traits and CSR strategies could help facilitate green roof plant selection into new geographical regions where green roof technology is developing. For example, in high latitude northern European regions with long daylight during the growing season. Growth (shoot biomass, relative growth rate and leaf area), leaf traits (leaf dry matter content, specific leaf area and succulence) and CSR strategies were determined of 10 common European green roof plants and related to their water use under well-watered (WW) and water-deficit (WD) conditions. All three succulent species included in the experiment showed mostly stress tolerant traits and their water loss was less than the bare unplanted substrate, likely due to mulching of the substrate surface. Plants with greater water use under WW conditions had more ruderal and competitive strategies, and greater leaf area and shoot biomass, than species with lower WW water use. However, the four species with the highest water use under WW conditions were able to downregulate their water use under WD, indicating that they could both retain rainfall and survive periods of water limitations. This study indicates that, for optimal stormwater retention, green roof plant selection in high latitude regions like northern Europe, should focus on selecting non-succulent plants with predominantly competitive or ruderal strategies to make the most of the long daylight during the short growing season.

Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava.

BACKGROUND: The purpose of this study was to investigate the potential of hyperspectral imaging for the characterization of cooking quality parameters, dry matter content (DMC), water absorption (WAB), and texture in cassava genotypes contrasting for their cooking quality. RESULTS: Hyperspectral images were acquired on cooked and fresh intact longitudinal and transversal slices from 31 cassava genotypes harvested in March 2022 in Colombia. Different chemometric methods were tested for the quantification of DMC, WAB, and texture parameters. Data analysis was conducted through partial least squares regression, K nearest neighbors regression, support vector machine regression and CovSel multiple linear regression (CovSel_MLR). Efficient performances were obtained for DMC using CovSel_MLR with, coefficient of multiple determination R p 2 = 0.94 $$ {R}_p^2=0.94 $$ , root-mean-square error of prediction RMSEP = 0.96 g/100 g, and ratio of the standard deviation values RPD = 3.60. High heterogeneity was observed between contrasting genotypes. The predicted distribution of DMC within the root can be homogeneous or heterogeneous depending on the genotype. Weak predictions were obtained for WAB and texture parameters. CONCLUSIONS: This study showed that hyperspectral imaging could be used as a high-throughput phenotyping tool for the visualization of DMC in contrasting cooking quality genotypes. Further improvement of protocols and larger datasets are required for WAB and texture quality traits. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Carbon sufficiency boosts phenylpropanoid biosynthesis early in peach fruit development priming superior fruit quality.

Manipulating the crop load in peach trees determines carbon supply and optimum balance between fruit yield and quality potentials. The impact of carbon supply on peach fruit quality was assessed in three development stages (S2, S3, S4) on fruit of equal maturity from trees that were carbon (C) starved (unthinned) and sufficient (thinned). Previous studies determined that primary metabolites of peach fruit mesocarp are mainly linked with developmental processes, thus, the secondary metabolite profile was assessed using non-targeted liquid chromatography mass-spectrometry (LC-MS). Carbon sufficient (C-sufficient) fruit demonstrated superior quality attributes as compared to C-starved fruit. Early metabolic shifts in the secondary metabolome appear to prime quality at harvest. Enhanced C-availability facilitated the increased and consistent synthesis of flavonoids, like catechin, epicatechin and eriodyctiol, via the phenylpropanoid pathway, providing a link between the metabolome and fruit quality, and serving as signatures of C-sufficiency during peach fruit development.

On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies.

Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772-0.942, 0.774-0.970, 0754-0.960, and 0.800-0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index.

Internal Quality Attributes and Sensory Characteristics of 'Ambrosia' Apples with Different Dry Matter Content after a Two-Week and a Ten-Week Air Storage at 1 °C.

This research was conducted to determine the compositional and textural characteristics and sensory profile of 'Ambrosia' apples with different dry matter content (DMC) as estimated using a Felix-750 Produce Quality Meter (Felix Instruments Inc., Camas, WA, USA). Fruits were harvested from a commercial orchard in Cawston and an experimental field in Summerland Research and Development Centre (SuRDC) in British Columbia, Canada, when the average absorbance difference index/coefficient of fruit skin δAbsorbance (δA) dropped under 0.45 ± 0.10. DMC levels were estimated after harvest at the blush/background transition zone for fruit categorization on 300 fruits from each location. Fruits were coded with an individual number and grouped in different DMC categories. The distribution of the estimated DMC levels obtained from two locations was different. The results indicate that DMC levels were strongly and positively correlated with the soluble solids content (SSC) of the fruit (r = 0.81). Sensory evaluations also demonstrated that apples in the lowest DMC category (12.5% ± 0.5 from Cawston) were considered the least sweet apples with the least overall flavour quality by panellists compared to the apples from the other DMC categories included in the sensory evaluations from the two locations. Panellists also perceived less-than-expected "fresh apple" and "tropical" flavours but more-than-expected "no flavour" and "bland" off flavour from the lowest-DMC-category apples. The non-destructive DMC measurements show a potential to be used to sort apples for SSC, sweetness and flavour; nevertheless, they were not related to firmness or textural attributes.

Validation of KASP-SNP markers in cassava germplasm for marker-assisted selection of increased carotenoid content and dry matter content.

Provitamin A biofortification and increased dry matter content are important breeding targets in cassava improvement programs worldwide. Biofortified varieties contribute to the alleviation of provitamin A deficiency, a leading cause of preventable blindness common among pre-school children and pregnant women in developing countries particularly Africa. Dry matter content is a major component of dry yield and thus underlies overall variety performance and acceptability by growers, processors, and consumers. Single nucleotide polymorphism (SNP) markers linked to these traits have recently been discovered through several genome-wide association studies but have not been deployed for routine marker-assisted selection (MAS). This is due to the lack of useful information on markers' performances in diverse genetic backgrounds. To overcome this bottleneck, technical and biological validation of the loci associated with increased carotenoid content and dry matter content were carried out using populations independent of the marker discovery population. In the present study, seven previously identified markers for these traits were converted to a robust set of uniplex allele-specific polymerase chain reaction (PCR) assays and validated in two independent pre-breeding and breeding populations. These assays were efficient in discriminating marker genotypic classes and had an average call rate greater than 98%. A high correlation was observed between the predicted and observed carotenoid content as inferred by root yellowness intensity in the breeding (r = 0.92) and pre-breeding (r = 0.95) populations. On the other hand, dry matter content-markers had moderately low predictive accuracy in both populations (r< 0.40) due to the more quantitative nature of the trait. This work confirmed the markers' effectiveness in multiple backgrounds, therefore, further strengthening their value in cassava biofortification to ensure nutritional security as well as dry matter content productivity. Our study provides a framework to guide future marker validation, thus leading to the more routine use of markers in MAS in cassava improvement programs.

SlMBP3 Knockout/down in Tomato: Normal-Sized Fruit with Increased Dry Matter Content through Non-Liquefied Locular Tissue by Altered Cell Wall Formation.

The phenotypic effect of the knockdown/out of AGAMOUS clade MADS-box gene SlMBP3 in tomato was evaluated using a transferred DNA (T-DNA)-tagged mutant of SlMBP3 and SlMBP3-RNA interference lines. SlMBP3 was preferentially expressed in the locular tissue of fruit and the seed coat combined with the endoderm. Consistent with where SlMBP3 is expressed, the SlMBP3-knockout/down lines showed non-liquefied locular tissues and increased number of seed hairs than the wild type (WT). The early cell degradation of the locular tissue was not observed in the fruits of the SlMBP3-knockout/down lines, and the cells were elongated like placental cells resulting in non-liquefied locular tissues. As the result, the fruits of the SlMBP3-knockout/down lines exhibited higher dry matter contents and titratable acidity than those of the WT. During locular tissue cell development under the SlMBP3 knockout/down, the expression of cell-enlargement-related genes (beta-expansin gene SlEXPB1 and endo-beta-1,4-D-glucanase gene Cel8) and pectinase-inhibitor-related genes (pectin esterase inhibitor gene PE inhibitor and polygalacturonase inhibitor gene PG inhibitor) was upregulated and that of pectinase-encoding genes (polygalacturonase gene QRT3-like and pectin lyase gene PL2) was downregulated. In the seed coat of the SlMBP3-knockout/down lines, tomato trichome-formation-related genes such as MYB genes containing R2 and R3 repeats (R2R3-MYB) transcription factor SlMYB75, B-type cyclin SlCycB2 and Homeodomain Leucine Zipper (HD-Zip) IV transcription factor Woolly were downregulated. Our results demonstrate that SlMBP3 is involved in the liquefaction of the locular tissue through the modification of cell development and degradation processes and seed hair formation in tomato fruits, and the SlMBP3 knockout/down results in normal-sized fruit with increased dry matter content.

Functional traits and their plasticity shift from tolerant to avoidant under extreme drought.

Under climate change, extreme droughts will limit water availability for plants. However, the species-specific responses make it difficult to draw general conclusions. We hypothesized that changes in species' abundance in response to extreme drought can be best explained by a set of water economic traits under ambient conditions in combination with the ability to adjust these traits towards higher drought resistance. We conducted a 4-year field experiment in temperate grasslands using rainout shelters with 30% and 50% rainfall reduction. We quantified the response as the change in species abundance between ambient conditions and the rainfall reduction. Abundance response to extreme drought was best explained by a combination of traits in ambient conditions and their functional adjustment, most likely reflecting plasticity. Smaller leaved species decreased less in abundance under drought. With increasing drought intensity, we observed a shift from drought tolerance, i.e., an increase in leaf dry matter content, to avoidance, i.e., a less negative turgor loss point (TLP) in ambient conditions and a constancy in TLP under drought. We stress the importance of using a multidimensional approach of variation in multiple traits and the importance of considering a range of drought intensities to improve predictions of species' response to climate change.

New data of plant leaf traits from Central Europe.

Trait-based ecology is gaining ground nowadays on species-based ecology: the number of research and publication focusing on the ecological role of taxa instead of the species themselves increased significantly in the last two decades. One great advantage of this approach is that communities with different species composition due to great geographical distances (e.g., different continents) or different environmental conditions (e.g., loess, sand, and alkaline grasslands) become comparable. Obtaining trait values is, however, labour and time consuming even in the case of so-called soft traits. It is therefore reasonable and desirable for scientists to share their data as widely as possible. Demand for such data induced the publication of data papers and the establishment of databases, which support both theoretical ecological research and practical restoration ecological projects. Although several international databases (e.g., TRY, LEDA, CLO-PLA, BiolFLOR) are available nowadays, Central and Eastern European species are either missing or underrepresented in them. Consequently, measurement and publication of the traits of species typical in the above region is necessary. This paper presents leaf trait (leaf fresh and dry weight, leaf area, specific leaf area and leaf dry matter content) data for more than 1100 species of the Central European flora.