Safflower (Carthamus tinctorius L.) crop adaptation to residual moisture stress: conserved water use and canopy temperature modulation are better adaptive mechanisms.

Oilseeds with high productivity and tolerance to various environmental stresses are in high demand in the food and industrial sectors. Safflower, grown under residual moisture in the semi-arid tropics, is adapted to moisture stress at certain levels. However, a substantial reduction in soil moisture has a significant impact on its productivity. Therefore, assessing genetic variation for water use efficiency traits like transpiration efficiency (TE), water uptake, and canopy temperature depression (CTD) is essential for enhancing crop adaptation to drought. The response of safflower genotypes (n = 12) to progressive soil moisture depletion was studied in terms of water uptake, TE, and CTD under a series of pot and field experiments. The normalised transpiration rate (NTR) in relation to the fraction of transpirable soil water (FTSW) varied significantly among genotypes. The genotypes A-1, Bhima, GMU-2347, and CO-1 had higher NTR-FTSW threshold values of 0.79 (R2 = 0.92), 0.74 (R2 = 0.96), 0.71 (R2 = 0.96), and 0.71 (R2 = 0.91), respectively, whereas GMU-2644 had the lowest 0.38 (R2 = 0.93). TE was high in genotype GMU-2347, indicating that it could produce maximum biomass per unit of water transpired. At both the vegetative and reproductive stages, significant positive relationships between TE, SPAD chlorophyll metre reading (SCMR) (p < 0.01) and CTD (p < 0.01) were observed under field conditions by linear regression. The genotypes with high FTSW-NTR thresholds, high SCMR, and low CTD may be useful clues in identifying a genotype's ability to adapt to moisture stress. The findings showed that the safflower genotypes A-1, Bhima, GMU-2347, and CO-1 exhibited an early decline and regulated water uptake by conserving it for later growth stages under progressive soil water depletion.

Analysing the SPAD dynamics of water-stressed vs. well-watered sesame (Sesamum indicum L.) accessions and establishing their relationship with seed yield.

Background: The chlorophyll content is susceptible to deficit moisture stress and may affect the plant yield. Leaf chlorophyll content is directly related to tolerance and higher productivity under deficit moisture stress (WS). The SPAD meter is an excellent tool for rapid analysis of crop chlorophyll content. Therefore, establishing a relationship between leaf chlorophyll content and seed yield is crucial in sesame, particularly under deficit moisture stress. Methods: Seeds of 37 sesame genotypes with checks were used in this study. These genotypes were mostly landraces, adapted to different agro-ecological zones in India. The selected genotypes were evaluated under well water (WW) and deficit moisture stress (WS) conditions. The SPAD readings were recorded ten (10) times each at every seven days intervals from the juvenile/first bud (30-35 days after sowing) to ripening/ physiological maturity (95-100 days after sowing) stage. This study aimed to identify the association between leaf SPAD readings (recorded at 7-days interval) and seed yield of sesame genotypes. Results: The analysis of variance revealed the presence of significant variation in SPAD readings due to treatment (WW and WS), genotypes, and their interaction effects. The SPAD readings at all stages were positively correlated with seed yield in both WW and WS. High values of correlation coefficients were observed at 52 (r: 0.672) and 59 (r: 0.655) DAS under WS; whereas at 59 (r: 0.960), 66 (r: 0.972) and 73 (r: 0.974) DAS under WW at one percent significance level (p < 0.01), which coincided with the mid-bloom stage of the sesame crop. The best-fit multiple regression model revealed that the dependence of sesame seed yield is significantly influenced by SPAD reading at 52 DAS under WS and 59 to 73 DAS under WW. Both these models provide a good fit with the chi-squared test, which compares the predicted and observed yield.

Identifying Traits Associated With Terminal Drought Tolerance in Sesame (Sesamum indicum L.) Genotypes.

Sesame is predominantly cultivated in rainfed and low fertile lands and is frequently exposed to terminal drought. Sesamum species inhabiting dryland ecosystems adaptively diverge from those inhabiting rainfed habitats, and drought-specific traits have a genetic basis. In sesame, traits associated with drought conditions have not been explored to date, yet studies of these traits are needed given that drought is predicted to become more frequent and severe in many parts of the world because of climate change. Here, 76 accessions from the available Indian core set were used to quantify variation in several traits under irrigated (WW) and terminal drought stress (WS) conditions as well as their association with seed yield over two consecutive years. The range of trait variation among the studied genotypes under WW and WS was significant. Furthermore, the traits associated with seed yield under WW and WS differed. The per se performance of the accessions indicated that the expression of most traits was reduced under WS. The correlation analysis revealed that the number of branches, leaf area (LA), leaves dry weight (LDW), number of capsules plant-1, and harvest index (HI) were positively correlated with seed yield under WW and WS, and total dry matter (TDM), plant stem weight, and canopy temperature (CT) were negatively correlated with seed yield under WW and WS, indicating that smaller and cooler canopy genotypes had higher yields. The genotypes IC-131936, IC-204045, IC-204861, IC-205363, IC-205311, and IC-73576 with the highest seed yields were characterized by low canopy temperature, high relative water content, and high harvest index under WS. Phenotypic and molecular diversity analysis was conducted on genotypes along with checks. Phenotypic diversity was assessed using multivariate analysis, whereas molecular diversity was estimated using simple sequence repeat (SSR) loci to facilitate the use of sesame in breeding and genetic mapping. SSRs showed low allelic variation, as indicated by a low average number of alleles (2.31) per locus, gene diversity (0.25), and polymorphism information content (0.22). Cluster analysis (CA) [neighbor-joining (NJ) tree] revealed three major genotypic groups and structure analysis showed 4 populations. The diverse genotypes identified with promising morpho-physiological traits can be used in breeding programs to develop new varieties.

Plant phenomics: High-throughput technology for accelerating genomics.

Plant phenomics is a high-throughput path-breaking area that meets all the requirements for the collection of accurate, rapid and multi-faceted phenotypic data. Plant phenomics is an approach to envisage complex traits that are appropriate for selection, and provides relevant information as to why particular genotype can stand out in particular environmental conditions. The technique of plant phenotyping can be operated in various dimensions, from the gene to the whole-plant level under a specific environment, and management practices. Through this review, we discuss the recent advances in plant phenomics, highlighting different field and confined high-throughput technologies for utilization in forward and reverse genetics. These plant phenomics technique are very relevant in stress identification, study physiological processes, rapid and efficient screening, dissection and confirmation for understanding the genetic basis of different traits, genes and aspects. Highthroughput phenomics technologies are essential to avoid human error and to reduce time consumption while phenotyping large germplasm populations, or for confirmation of gene or trait functional analysis.