Search Results (23)

The screening of poplar varieties that demonstrate tolerance to low nitrogen (N) represents a promising strategy for improving nitrogen-use efficiency in trees. Such an approach could reduce reliance on N fertilizers while mitigating environmental pollution associated with their cultivation. In this study, a total of 87 poplar varieties were evaluated in a controlled greenhouse pot experiment. Under both low-nitrogen (LN) and normal-nitrogen (NN) conditions, 18 traits spanning four categories—growth performance, leaf morphology, chlorophyll fluorescence, and N isotope parameters were measured. For 13 of these traits (growth, leaf morphology, chlorophyll fluorescence), genetic variation and parameters, including genotypic values, were analyzed using best linear unbiased prediction (BLUP) within a linear mixed model (LMM). LN tolerance of tested poplar varieties was comprehensively assessed with three MGIDI strategies by integrating means, BLUPs, and low-nitrogen tolerance coefficient (LNindex) to rank poplar varieties. The results exhibited highly significant differences across all traits between LN and NN experiments, as well as among varieties. LN stress markedly inhibited growth, altered leaf morphology, and reduced chlorophyll fluorescence parameters in young poplar plants. Among the selection strategies, the MGIDI_LNindex approach demonstrated the highest selection differential percent (SD% = 10.5–35.23%). Using a selection intensity (SI) of 20%, we systematically identified 17 superior genotypes across all three strategies. In a thorough, comprehensive MGIDI-based evaluation, these varieties exhibited exceptional adaptability and stability under LN stress. The selected genotypes represent valuable genetic resources for developing improved poplar cultivars with enhanced low-nitrogen tolerance. Full article

This research assessed 42 lentil genotypes developed by ICARDA along with a local variety over three growing seasons (2019–2022) in Southeastern Türkiye. Phenological, morphological, and yield attributes were determined to observe earliness, yield stability, and adaptation properties. Genotype G3771 showed outstanding performance in grain yield (2579 kg ha⁻¹), 1000-seed weight (54.9 g), and harvest index (37.3%), although it had lower stability under more severe drought conditions. Early-maturing genotypes like G3744, G3715, and G3716 consistently flowered and matured sooner, making them better suited for escaping terminal drought stress areas. The highest yields were recorded during the 2019–2020 season, which experienced favorable rainfall and soil nutrient levels, while the lowest yields occurred due to changing climatic conditions in the 2020–2021 season, highlighting the crop’s sensitivity to climate. Principal component analysis, hierarchical clustering, the Modified Multi-Trait Stability Index (MTSI), and the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) aided in effective genotype classification. Although G3771 was the most productive, genotypes G3687, G3715, and G3689 proved to be the most stable and early maturing based on MGIDI scores. Strong relationships between grain yield, biological yield, and seed size identified these as key selection criteria. This study underscores the value of multi-trait selection tools like MGIDI and MTSI in consistently pinpointing lentil genotypes that balance earliness, productivity, and adaptability, laying a strong foundation for developing climate-resilient varieties suited to semi-arid climates. Full article

Nitrogen fertilization plays a critical role in promoting plant growth, improving physiological and biochemical traits, and enhancing wheat productivity. This study aimed to evaluate the effects of seven nitrogen (N) doses—0, 45, 90, 135, 180, 225, and 270 kg N ha⁻¹—on wheat performance under semi-arid subtropical conditions over three consecutive growing seasons (2015–2018). A randomized complete block design (RCBD) was used to assess a comprehensive set of agronomic, physiological, biochemical, and nutritional parameters. Key factors examined included grain yield, above-ground biomass, nitrogen harvest index, total nitrogen content in grains and straw, and physiological traits such as photosynthetic rate, stomatal conductance, transpiration rate, and the accumulation of soluble proteins, sugars, and amino acids. The study also incorporated multivariate statistical techniques, such as multi-trait genotype–ideotype distance index (MGIDI), principal component analysis (PCA), and descriptive statistics to identify the most effective nitrogen dose. Results indicated that 180 kg N ha⁻¹ (T₄) was the most effective treatment for improving wheat growth, physiological efficiency, and grain yield, with 135 kg N ha⁻¹ (T₃) also showing favorable outcomes. In contrast, higher doses (225 and 270 kg N ha⁻¹) led to diminished performance, suggesting a threshold beyond which nitrogen becomes counterproductive. These findings support 180 kg N ha⁻¹ as the optimal dose for maximizing yield and biochemical quality while contributing to more sustainable and profitable wheat production. Full article

Douglas fir (Pseudotsuga menziesii [Mirb.] Franco) is a valuable timber species native to western North America that was introduced to Europe in the 19th century. The objective of this study was to select the most valuable and stable Douglas fir provenances in Romania by combining growth and quality traits, using two indices recently used in forest tree species: the multi-trait genotype–ideotype distance index (MGIDI) and the multi-trait stability index (MTSI). The study was conducted across three common garden experiments in Romania, established in 1977, evaluating 61 provenances from the United States, Canada, Germany, France, and Romania. The analyzed traits were diameter at breast height (DBH), total height (TH), and pruned height (PH). Significant genotype–environment interactions were observed, with the Douglas fir showing superior growth performance in one of the testing sites in western Romania (Aleșd). The MGIDI and MTSI identified high-performing provenances from diverse geographic origins, including the Pacific Northwest, Europe, and Canada. Selection differentials ranged from 2.8% to 10.9% for individual traits, highlighting the potential for genetic improvement. The selected provenances represent valuable genetic resources of Douglas fir that are adapted to environmental conditions in the Carpathian region, contributing to the development of climate-adaptive breeding strategies and sustainable forest management. Full article

Rice is a vital staple in many countries, and as the demand for food diversity rises, the focus has shifted towards improving rice quality rather than just yield. This shift in breeders’ goals has led to the development of breeding populations aimed at comprehensively assessing rice grain appearance quality. In this regard, we developed an F₁₁ rice recombinant inbred line population derived from a cross between the IR28 and Shahpasand (SH) varieties and assessed the grain appearance characteristics of 151 lines and seven varieties using a computer vision system and a new generation of phenotyping tools for rapidly and accurately evaluating all grain quality-related traits. In this method, characteristics such as area, perimeter, length, width, aspect ratio, roundness, whole kernel, chalkiness, red stain, mill rate, and brown kernel were measured very quickly and precisely. To select the best lines, considering multiple traits simultaneously, we used the multi-trait genotype ideotype distance index (MGIDI) as a successful selection index. Based on the MGIDI and a 13% selection intensity, we identified 17 lines and three varieties as superior genotypes for their grain appearance quality traits. Line 59 was considered the best due to its lowest MGIDI value (0.70). Lines 19, 31, 32, 45, 50, 59, 60, 62, 73, 107, 114, 122, 125, 135, 139, 144, and 152 exhibited superior grain quality traits compared to the parents, making them high-quality candidates and indicating transgressive segregation within the current RIL population. In conclusion, the image processing technique used in this study was found to be a fast and precise tool for phenotyping in large populations, helpful in the selection process in plant breeding. Additionally, the MGIDI, by considering multiple traits simultaneously, can help breeders select high-quality genotypes that better match consumer preferences. Full article

Drought stress substantially restricts cotton growth, decreasing cotton production potential worldwide. This study evaluated cotton genotypes at the flowering stage to identify drought-resilient genotypes under moderate and severe drought conditions using physio-morphic and biochemical markers. Five genotypes were examined in a completely randomized design with three replicates across three treatments. Growth and biochemical traits were measured after 14 days of drought stress. The Multi-trait Genotype–Ideotype Distance Index (MGIDI) identified the most drought-tolerant genotypes. Severe drought had a pronounced negative effect on growth and biochemical traits, followed by moderate drought. Among the genotypes, FH-912 exhibited the strongest resilience, with significant increases in proline, peroxidase, catalase, and total chlorophyll. In contrast, chlorophyll a and transpiration rates were largely unaffected. Genotypes VH-351, VH-281, and GH-99 showed moderate drought tolerance, while FH-556 was highly sensitive to water stress. Statistical analyses, including ANOVA, PCA, and heatmaps, confirmed FH-912’s superior performance under drought stress. The drought-resilient genotype, FH-912, holds promise for breeding drought-tolerant cotton varieties to sustain cotton productivity in water-limited environments, especially in drought-prone regions. Full article

Drought is a detrimental abiotic stress that severely limits wheat growth and productivity worldwide by altering several physiological processes. Thus, understanding the mechanisms of drought tolerance is essential for the selection of drought-resilient features and drought-tolerant cultivars for wheat breeding programs. This exploratory study evaluated 14 wheat genotypes (13 relatively tolerant, one susceptible) for drought endurance based on flag leaf physiological and biochemical traits during the critical grain-filling stage in the field conditions. Measurements included six physiological, seven gas exchange, six photosystem II, six stomatal, three reactive species, seven metabolomic solutes, and two biomass traits. All parameters were significantly influenced by drought, with varying genotypic responses. Hierarchical cluster analysis (HCA) categorized genotypes into three drought tolerance groups based on trait performance. Seven genotypes in Cluster 2 (BARI Gom 26, BARI Gom 33, BD-631, BD-600, BD-9910, BD-9889, BD-637) exhibited superior drought tolerance, characterized by minimal changes in physiological traits and biomass accumulation, reduced oxidative stress markers, and increased accumulation of osmoprotectants. The innovative multi-trait genotype-ideotype distance index (MGIDI) further ranked wheat genotypes in regard to drought tolerance, identifying BARI Gom 33, BARI Gom 26, BD-9889, and BD-600 as top performers. Notably, all these top-ranking genotypes belonged to Cluster 2, previously identified as the highest-performing group in the HCA. The identified genotypes with superior drought tolerance offer valuable genetic resources for enhancing wheat productivity in water-limiting environments. Traits related to photosynthetic activity, biomass gain, leaf conductance, water stress, and osmoprotection showed high selection differentials and heritability in MGIDI analysis, indicating their potential as selection targets for drought-tolerant wheat. Overall, the strategic approaches have yielded novel insights into genotype screening that can be directly applied to deepen our understanding of drought tolerance mechanisms in wheat. Full article

Drought stress constricts crop production around the world. Employing high-yielding cultivars with drought tolerance might be the ideal professional approach to coping with its detrimental outcomes. As a result, the current study was performed to investigate the sensitivity and tolerance of nine wheat genotypes to drought stress. In a randomized block design experiment, nine wheat genotypes were subjected to four water treatments: 100%, 85%, 70%, and 55% of the available water (AW). Four water regimes in two growing seasons were counted as eight environmental zones. The leaf’s water relations and photosynthetic pigment were estimated, as well as growth and yield parameters. Univariate and multivariate statistical approaches, including the new method of multi-trait genotype–ideotype distance (MGIDI), were used for evaluation. The analysis of variance revealed that genotype, environment, and their interactions had a highly significant effect on all traits. The same trend was shown by the additive main effects and multiplicative interaction (AMMI) analysis of variance for grain yield across the environments. The AMMI biplot study indicated that the G8 genotype is the most stable in terms of water stress. The G7 genotype can withstand droughts up to 55% of the available water, while the G8 and G3 genotypes can withstand droughts up to 70% of the available water. Based on all examined traits, this index was used to identify the stable genotypes G7, G8, and G3, which can therefore be suggested for cultivation during drought conditions. Furthermore, we found a positive correlation between the MGIDI, ANOVA, and tolerance index results, indicating that the same desirable genotypes of G7 and G8 were identified by these procedures as being highly tolerant and stable across a range of soil moisture conditions. Based on MGIDI analysis, we can recommend that the G7 genotype exhibits higher grain yield and yield-related traits with the best drought-tolerant indices. Full article

Water yam (Dioscorea alata L.) is the most widely cultivated yam species with good agronomic attributes. However, several biotic and abiotic constraints and its lower food quality such as poor pound ability limit its production and use. Therefore, the identification of superior genotypes with suitable characteristics is needed for water yam improvement. This study aims to assess a panel of half-sib (progenies with one parent in common) and full-sib (progenies with the same male and female parents) progenies as well as their parents for selection of desirable ideotypes based on their agronomic and quality characteristics. A total of 280 progenies from bi-parental populations as well as five parents were evaluated, and a significant variation was observed (p < 0.01) in their performances for the eight traits used in the study. A moderate to high broad-sense heritability (30% < H2–H2 ≥ 60%) was observed for all traits except for tuber pound ability (H2 < 30%). Positive correlations were displayed between the traits, while the hierarchical clustering grouped genotypes into three clusters indicating the potential for selection of diverse genotypes for multiple traits from the four families under study. Plant vigor and number of tubers per plant contributed (p < 0.01) positively to the yield per plant in the path coefficient analysis. Using the multi-trait genotype–ideotype distance index (MGIDI), a total of 39 most promising genotypes were identified. These promising genotypes could be further used as progenitors in D. alata improvement programs targeting good agronomic and quality traits targeted for farmers and end users. Full article

Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a significant threat to rice cultivation. One effective way to deal with this disease is to identify and introduce resistant varieties using different breeding methods. This study utilized a population of 153 recombinant inbred lines (RILs) derived from the crossing of the Shahpasand (SH) and IR28 varieties, characterized by susceptibility and resistance to leaf blast, respectively. In combination with 12 control varieties, these genotypes were subjected to an extensive evaluation of disease severity (5 stages), the area under the disease progress curve (AUDPC), type, and the infection rate in 2021 and 2022. Analysis of variance revealed significant genetic variation, highlighting the potential of the RIL population for identifying and selecting resistant lines. Employing cluster analysis and the multi-trait genotype-ideotype distance index (MGIDI), 17 lines were identified as the most resistant over a two-year evaluation period. The average AUDPC for these resistant lines was estimated at 2.435 ± 0.114, and lines 17 and 111 had the lowest AUDPC (1.526 and 1.630, respectively) and showed the least infection in two years. Conversely, lines 42 and 43 showed the highest AUDPC values (255.312 and 248.209) along with heightened sensitivity. The use of MGIDI yielded a substantial selection differential (SD) of −59.12% for traits related to leaf blast disease resistance, demonstrating the effectiveness of this method. Furthermore, new recombinant populations are expected to be developed in future plant breeding projects by crossing the most susceptible and resistant lines, which will be new sources of resistance to this disease. Full article

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

Growing potatoes (Solanum tuberosum) using the idle rice fields in Southern China and the Indo-Gangetic Plains of India in the winter season through the rice–potato rotation (RC) system could support future food security. However, the modulation capacity of the RC system on soilborne fungal pathogens is still unclear. In the current study, a pot experiment was designed and conducted to monitor the dynamics of soil fungal community composition between the potato monoculture (CC) system and the RC system, where the two systems were set with the same soil conditions: autoclaving with fertilization; autoclaving without fertilization; autoclave-free with fertilization; and autoclave-free without fertilization. Then, the uncultivated soil (CK) and root-zone soil samples of conditions under the two systems were collected, and then soil physiochemical properties and enzymatic activities were determined. Next, the high-variable region (V5–V7) of fungal 18S rRNA genes of the samples were amplified and sequenced through the PCR technique and the Illumina Miseq platform, respectively. Finally, the fungal species diversity and composition, as well as the relative abundance of fungal pathogens annotated against the Fungiuld database in soil samples, were also investigated. The results showed that the RC could significantly (p < 0.05) increase soil fungal species diversity and decrease the relative abundance of soil fungal pathogens, where the RC could suppress 23 soil fungal pathogens through cultivating the rice during the summer season and 93.75% of the remaining pathogens through winter-season cultivation. Seven-eighths of the conditions under RC have lower pathogenic MGIDI indices (6.38 to 7.82) than those of the CC (7.62 to 9.63). Notably, both rice cultivation and winter planting reduced the abundance of the pathogenic strain ASV24 under the Colletotrichum genus. The bipartite fungal network between the pathogens and the non-pathogens showed that the pathogenic members could be restricted through co-occurring with the non-pathogenic species and planting crops in the winter season. Finally, the redundancy analysis (RDA) indicated that soil pH, electronic conductivity, available phosphorus content, and various enzyme activities (cellulase, urease, sucrase, acid phosphatase, catalase, polyphenol oxidase) could be the indicators of soil fungal pathogens. This experiment demonstrated that the rice–potato rotation system outperformed the potato monoculture on suppressing soilborne fungal pathogenic community. Full article

Transitioning to conservation agriculture is proving to be a better alternative and could become the norm in the future. Morocco, geographically located in a hot spot, is much more vulnerable to the hazards of climate change and the advantages of conservation agriculture remain a good compromise to ensure sustainable agricultural production. However, the lack of sufficient knowledge about this agricultural technology could be a hindrance and thus create mistrust among farmers. Therefore, the objective of our study is to evaluate the performance of a collection of chickpeas in each tillage system to identify genotypes that can be integrated into breeding programs for adaptation to conservation agriculture. Our study shows no significant effect of tillage on grain yield. Chlorophyll content and pod number made the strongest direct and positive contributions to yield for conventional and no-till, respectively. Nine genotypes including two checks (C1 and C2) were selected in both systems through MGIDI (multi-trait genotype–ideotype distance index) analysis. These genotypes would be potential candidates for breeding programs for adaptation to no-till because of their plasticity to reproduce acceptable yields in both till systems. Full article

Climate change has affected the food supply chain and raised serious food concerns for humans and animals worldwide. The present investigation aimed to assess the effect of environmental factors along with three different levels of cutting (i.e., cutting 1, 2, and 3 at the vegetative, budding, and flowering stages, respectively) and spacing (i.e., 21, 23, and 26 cm) on quinoa biomass and quality to select the most suitable accessions. This experiment was repeated for two years using a split–split plot experimental design. The cutting × genotype × year and cutting × space × genotype interactions were significant for most quinoa morphological traits (except for leaf area and intermodal distance), where the maximum growth in number of leaves/plant (NoL), plant height (PH), fresh weight (FW), number of branches/plant (Br), and dry weight (DW) were observed during the second growing season. Cutting and spacing levels also showed significant effects on morphological and quality traits of quinoa. Among the different levels of cutting and spacing, cutting level 3 and spacing level 2 were more effective across both years at gaining maximum biomass and quality traits such as crude fat (CF) and crude protein (CP). According to the MGIDI, only two accessions (R3 and R9) fared better in both growing seasons, and selected accessions had positive morphological and quality traits. There were moderately significant negative correlations between PH, NoL, LA, FW, and DW and anti-quality traits such as neutral detergent fiber (NDF) and acid detergent fiber (ADF), indicating that an increase in biomass decreased the concentrations of ADF and NDF in both stem and leaves. A comparison with oat accessions (G3 and G7) revealed that quinoa has higher CP and CF and lower NDF than oats in both stems and leaves (except for ADF). In conclusion, the combination of cutting level 3 and spacing level 2 (23 cm) is more suitable to obtain high-quality quinoa forage with maximum biomass production. Furthermore, the MGIDI is a useful tool for breeders to select genotypes based on their mean performance, stability, and desired traits. Full article

Dioscorea praehensilis Benth. is a semi-wild yam species and a valuable source of resistance trait genes. To access the agronomic and tuber quality performance, eleven quantitative phenotypic traits were used to discriminate and identify promising accessions among 162 accessions of D. praehensilis collected in Ghana. Significant and high genetic variability (p < 0.001) for all eleven quantitative traits was found among the evaluated accessions. Moderate broad-sense heritability (H²) (30–60%) was observed for all the evaluated quantitative traits except the response to YMV and tuber hardness. The accessions were clustered into three groups; each cluster displayed genotypes with good potentiality for the different traits evaluated. Path coefficient analysis revealed positive contributions (p < 0.01) of the number of tubers per plant, tuber length, tuber width, stem internode length, number of internodes, and tuber flesh hardness to the total tuber weight per plant. Through the multi-trait genotype–ideotype distance index (MGIDI), 24 accessions were identified from the 162 evaluated accessions as top-ranking and could be used as progenitors for trait introgression. The results of this study provide insight for future yam breeding and improvement programs in West Africa. Full article