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In recent years, the exploration of the therapeutic potential of Salvia has gained considerable attention, leading to a growing number of scientific studies emphasizing its pharmacological properties. Despite this, therapeutic applications of Salvia remain underexploited, requiring further investigation. Iran is a major center for sage diversity in Asia, boasting 60 Salvia species, 17 of which are unique to the area. This study aimed to comprehensively explore and compare the extracts of 102 Salvia samples belonging to 20 distinct Salvia species from Iran, providing a deeper understanding of their specific polyphenol content and, consequently, their antioxidant capabilities and potential therapeutic uses. All samples were analyzed to determine the contents of total phenolics, total flavonoids, total tannin, photosynthetic pigments, and ascorbic acid, along with their antioxidant activity. These data were then combined with the forty distinct chemical fingerprints identified by ultrafast high-pressure liquid chromatography coupled with high-resolution mass spectrometry. Multivariate data analysis was employed to find correlations and differences among the huge number of data obtained and to identify Salvia species with similar phytochemical and/or antioxidant properties. The results show that each Salvia species is characterized by a distinct class of polyphenols recognized for their antidiabetic, anti-inflammatory, cardioprotective and neuroprotective properties. Overall, our findings reveal the potential of some Salvia species for targeted therapeutic applications and provide a rational basis for the development of Salvia-derived nutraceuticals, ultimately improving the prospects for the use of Salvia in medicine. [ABSTRACT FROM AUTHOR]

In any country, genetic resources are valuable assets for sustainable development. Having an accurate knowledge of genetic behavior and identification of genomic loci associated with important economic traits can help breeders run their breeding programs efficiently. Fourteen important pomological traits were measured in 45 table grape cultivars during three successive years (2016, 2017, and 2018). The molecular profile of the studied cultivars was prepared with 39 (simple sequence repeat) SSR primer pairs. Based on the SSR markers, genetic structure analysis revealed two subpopulations (K= 2) in the association panel. In association analysis, while using the mixed linear model, seven loci were found to be significantly associated with the studied traits (p=0.05). Breeding values were also estimated for the pomological traits using the best linear unbiased prediction (BLUP). 'Saghal Solian', 'At Ouzum', 'Garmian', 'Rishbaba Qermez', 'Taifi', 'Shahroudi', 'Sahebi Qermez', 'Lal Qermez', 'Alhaghi', 'Sarghola', 'Chava Ga', 'Qzl Ouzum' and 'Agh Shani' table grape cultivars showed high and positive breeding values for cluster length, width, and weight. 'Garmian', 'Rishbaba Qermez', 'Fakhri', 'Agh Shani', 'Lal Sefid', and 'Shirazi' had positive and high breeding values for pollen germination, fruit set in open pollination, and fruit set under controlled pollination. Finally, 'Sarghola' and 'Qzl Ouzum' showed positive, highest breeding values for berry weight, flesh weight, cluster length, cluster width, and cluster weight. Cultivars with high and positive breeding values can be used as good parents for the breeding of traits in hybridization programs because they can better transfer the desirable characteristics to progeny in each case. [ABSTRACT FROM AUTHOR]

Introduction Bread heat is the first grain and the most important annual crop in the world. Like other crops, wheat faces many environmental constraints such as a lack of trace elements during its growth period. Zinc deficiency is a common micronutrient disorder in wheat-growing areas of the world. The growing degree-days (GDD) index is reliable compared to the time calendar due to its stability. These indices are important for comparing genotypes whose physiological developmental stages do not match. Temperature is an important meteorological variable in the study of plant growth and development processes and therefore its study on short time scales leads to a more accurate estimate of thermal need due to the relatively wide range of temperature changes in different phenological stages, setting the planting date. Studying the effect of temperature on wheat genotypes should be based on sufficient time and temperature to complete the phenological stages in which grain yield components are formed. Materials and Methods To study the phenological stages, cumulative growing degree-days, and grain yield and its components in 64 spring wheat cultivars under optimal and zinc deficiency conditions, a study was conducted in the 2019-2020 cropping season based on a simple lattice design in the research field of Urmia University, Iran. Phenological stages include the number of days to germination, the number of days to booting, the number of days to pollination, the number of days to physiological maturity, and the grain filling period with their GDDs during the growing season in each pot based on 50% of the samples were determined to have reached the relevant vegetative stage. In addition to phenological stages along with the number of grains per spike, thousand-grain weight, and grain yield were examined. Results and Discussion Analysis of variance revealed that there is a statistically significant difference among all cultivars in terms of all studied traits except the number of days to pollination under optimal and zinc deficiency conditions. According to the results of descriptive statistics, grain yield, the number of grains per spike, and thousandgrain weight decreased and phenological traits increased under zinc deficiency conditions compared to optimal conditions. Among phenological traits, not only the number of days to spike showed relatively high variability but also had a significant relationship with grain yield under zinc deficiency based on the results of correlation and regression analyses. The factor analysis showed that under optimal conditions, the first four components explained 87.81 percent of the total variation, so that the contribution of the first to fourth components were 38.38, 21.52, 15.88, and 12.3 percent. Under zinc deficiency stress conditions, the first five components explained 95.68 percent of the total variation, so that the first to fifth components explained 34.62,18.48,17.51, 14.66, and 10.40 percent, respectively. Cluster analysis classified all spring wheat cultivars into three and four clusters under optimal and zinc deficiency stress conditions. Conclusion Based on the results of cluster analysis under optimal and zinc deficiency stress conditions, Neishabour, Golestan, and Gahar cultivars were identified as desirable and tolerant cultivars that can be used in future breeding programs. The results of cluster analysis were confirmed by results of canonical discriminant function results. [ABSTRACT FROM AUTHOR]

Context: Morphometric digital analysis of plant seeds enables taxonomic discrimination of species based on morpho-colorimetric traits, and may be used to classify genotypes of wheat (Triticum aestivum L.). Aims: This study was focused on the isolation and classification of cultivars and landraces of Iranian wheat based on morpho-colorimetric traits, and the prediction of yield and seedling vigour based on these traits. Methods: In total, 133 wheat genotypes (91 native landraces and 42 cultivars) were evaluated by alpha lattice design in two crop years (2018–19 and 2019–20) under rainfed and conditions. After seed harvesting, 40 morpho-colorimetric traits of wheat seeds were measured by imaging. Seed colour, morphometric seed, seed vigour and yield were also assessed. Key results: Using linear discriminant analysis based on morpho-colorimetric traits, wheat cultivars and landraces were separated with high validation percentage (90% in well-watered and 98.6% in rainfed conditions). Morpho-colorimetric traits L , Whiteness index, Chroma, a , Feret and Rectang were found to be the most discriminant variables in the rainfed field. In analysis based on seed colour according to descriptors of the International Union for the Protection of New Varieties of Plants and International Board for Plant Genetic Resources, wheat genotypes were classified into four groups with high accuracy by using linear discriminant analysis. Specifically, 97.3% could be identified as yellow and 99.7% as medium-red wheat groups. Conclusions: Our observations suggest that seed digital analysis is an affordable and valuable approach for evaluating phenotypic variety among a large number of wheat genotypes. Morphometric analysis of cultivars and native populations can provide an effective step in classifying genotypes and predicting yield and seedling vigour. Implications: Morphometric databases will help plant breeders when selecting genotypes in breeding programs. Image processing systems ensure high-resolution, high-throughput and precise analysis of seeds, which can be used to discover diversity and compare developmental phases, and distinguish genotypes. We classified cultivars and landraces of Iranian wheat based on morpho-colorimetric traits under rainfed and well-watered conditions. Our findings permit the formation of a morpho-colorimetric seed database of Iranian wheat landraces and cultivars for conservation, characterisation, and prediction of yield in wheat germplasm under both environmental conditions. [ABSTRACT FROM AUTHOR]