Abstract
Deep understanding of genetic architecture of water-stress tolerance is critical for efficient and optimal development of water-stress tolerant cultivars, which is the most economical and environmentally sound approach to maintain lettuce production with limited irrigation. Lettuce (Lactuca sativa L.) production in areas with limited precipitation relies heavily on the use of ground water for irrigation. Lettuce plants are highly susceptible to water-stress, which also affects their nutrient uptake efficiency. Water stressed plants show reduced growth, lower biomass, and early bolting and flowering resulting in bitter flavors. Traditional phenotyping methods to evaluate water-stress are labor intensive, time-consuming and prone to errors. High throughput phenotyping platforms using kinetic chlorophyll fluorescence and hyperspectral imaging can effectively attain physiological traits related to photosynthesis and secondary metabolites that can enhance breeding efficiency for water-stress tolerance. Kinetic chlorophyll fluorescence and hyperspectral imaging along with traditional horticultural traits identified genomic loci affected by water-stress. Supervised machine learning models were evaluated for their accuracy to distinguish water-stressed plants and to identify the most important water-stress related parameters in lettuce. Random Forest (RF) had classification accuracy of 89.7% using kinetic chlorophyll fluorescence parameters and Neural Network (NN) had classification accuracy of 89.8% using hyperspectral imaging derived vegetation indices. The top ten chlorophyll fluorescence parameters and vegetation indices selected by sequential forward selection by RF and NN were genetically mapped using a L. sativa × L. serriola interspecific recombinant inbred line (RIL) population. A total of 25 quantitative trait loci (QTL) segregating for water-stress related horticultural traits, 26 QTL for the chlorophyll fluorescence traits and 34 QTL for spectral vegetation indices (VI) were identified. The percent phenotypic variation (PV) explained by the horticultural QTL ranged from 6.41 to 19.5%, PV explained by chlorophyll fluorescence QTL ranged from 6.93 to 13.26% while the PV explained by the VI QTL ranged from 7.2 to 17.19%. Eight QTL clusters harboring co-localized QTL for horticultural traits, chlorophyll fluorescence parameters and VI were identified on six lettuce chromosomes. Molecular markers linked to the mapped QTL clusters can be targeted for marker-assisted selection to develop water-stress tolerant lettuce.
Highlights
Drought is a major challenge for crop production around the globe adversely affecting crop growth and productivity
In the third experiment conducted in fall of 2019, all recombinant inbred line (RIL) lines were grown in a growth chamber (CMP6050, Conviron, Winnipeg, MB, Canada) at 20◦C under continuous white light (200 μmol m−2 s−1) and relative humidity between 50 and 70% throughout the experiment and the water-stress was administered by withholding water supply to plants 2 weeks after transplanting
In this study we found that the Normalized Difference Vegetation Index (NDVI) was correlated with horticultural traits including fresh weight and water content and chlorophyll fluorescence parameters such as Fm, Fv and QY_max
Summary
Drought (water-stress) is a major challenge for crop production around the globe adversely affecting crop growth and productivity. Water stress decreases plants growth by affecting various physiological and biochemical processes such as photosynthesis, chlorophyll synthesis, nutrient metabolism, ion uptake and translocation, respiration, and carbohydrates metabolism (Jaleel et al, 2008; Farooq et al, 2009). Stressed plants display reduced water potential and turgor pressure, stomatal closure and decreased cell enlargement (Farooq et al, 2009) leading to accelerated leaf senescence. Leaf senescence triggered prematurely under water-stress leads to earlier transition to plant reproductive state (Lim et al, 2007; Behmann et al, 2014) and is characterized by reallocation of nutrients, degradation of leaf pigments and reduction in leaf chlorophyll content. Degradation of leaf chlorophyll leads to diminished photosynthetic efficiency of photosystem II (PSII) and alters the ratio between reflected, absorbed, and transmitted radiation (Blackburn, 2007)
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