Phenotyping of traits imparting drought tolerance in lentil

Abstract

Lentil is one of most important pulse crops in South Asia, and invariably encounters terminal moisture stress, leading to forced maturity and lower yield. A long and prolific root system is known to enhance capacity of the plant to extract water from the lower soil strata and thus help avoid the water stress. We assessed genetic variation for 12 traits among 43 lentil genotypes comprising improved varieties and promising breeding lines. The average root length at the 65-day plant stage ranged from 42 to 83 cm. Two genotypes (EC 208362 and VKS 16/11) with shorter root length and poor dry root weight (DRW) and three genotypes (DPL 53, JL 1, and IPL 98/193) with longer root length and high DRW were identified with stable performance over the years. Relationship of root traits with seed yield under rainfed conditions was non-significant in our study. The SPAD value (chlorophyll content) showed significantly positive correlation with DRW (r = 0.45**) and root length (r = 0.44**) and thus can be used as selection criterion for phenotyping root traits which are otherwise difficult to measure in the field. In drought-prone environments, early flowering and maturity, seedling vigour, and high SPAD value, biological yield, and harvest index were identified as key traits for higher seed yield in lentil. Our results revealed significant genetic variability for these traits in lentil germplasm. Indian genotypes adapted to rainfed conditions were shown to have longer roots and higher DRW. The three genotypes (DPL 53, JL 1, and IPL 98/193) identified with superior root traits either originated from or have in their ancestries at least one parent adapted to rainfed conditions. These genotypes can be utilised for the development of mapping populations to identify QTLs associated with these traits for marker-assisted breeding of drought-tolerant, high-yielding varieties of lentil.

Genetic diversity analysis of Moroccan lentil (Lens culinaris Medik.) landraces using Simple Sequence Repeat and Amplified Fragment Length Polymorphisms reveals functional adaptation towards agro‐environmental origins

“… Early vegetative vigour: 1 = very poor, 2 = poor, 3 = average, 4 = good, 5 = very good (Kumar et al. ). …”

“…Using SPSS Statistics 22, discriminant analysis was performed based on combined data sets of genetic data (SSRs and AFLP) and the agronomic data (agro-environment, early vegetative vigour, flowering and maturity time and seed type) in order to sort landraces according to most discriminating agronomic factors that may correspond to functional grouping of Early vegetative vigour: 1 = very poor, 2 = poor, 3 = average, 4 = good, 5 = very good (Kumar et al 2012).…”

Opportunities to improve the seasonal dynamics of water use in lentil (Lens culinaris Medik.) to enhance yield increase in water-limited environments

“…High genetic variation has been reported for root traits such as taproot length, lateral root number, total root length, and total root weight for lentil germplasm from different origins [13,14,25,26,31,42]. The high heritability estimates that were reported by these authors indicate the feasibility of making use of this genetic variability for the development of drought-adapted cultivars.…”

“…In such cases, what is usually called "drought tolerance" could be, in part, the consequence of plant constitutive traits that affect how soil water is used earlier in the growing season when water is non-limiting to plant transpiration [66]. The present yield of lentil in India is reported to be low [25] due to terminal drought and high temperatures, particularly during flowering and seed growth [32]. Climate change is expected to increase temperatures and an increase in extremes of rainfall as well as an increased risk of drought in many areas where lentil is grown [5].…”

“…Kumar et al [25] assessed genetic variability for 12 attributes including root and shoot traits among lentil genotypes originating from rainfed areas adapted to short-season environments. They found correlations between the individual traits and achieving a higher yield under drought conditions.…”