Search bioRxiv⌕ Search

Biology subjects

Kholova, J.

Publications and source records attributed to Kholova, J..

5 recordsLinked to original sources

Transpiration efficiency variations in the pearl millet reference collection PMiGAP

Transpiration efficiency (TE), the biomass produced per unit of water transpired, is a key trait for crop performance under limited water. As water becomes scarce, increasing TE would contribute to increase crop drought tolerance. This study is a first step to explore pearl millet genotypic variability for TE on a large and representative diversity panel. We analyzed TE on 538 pearl millet genotypes, including inbred lines, test-cross hybrids, and hybrids bred for different agroecological zones. Three lysimeter trials were conducted in 2012, 2013 and 2015, to assess TE both under well-watered and terminal-water stress conditions. We recorded grain yield to assess its relationship with TE. Up to two-fold variation for TE was observed over the accessions used. Mean TE varied between inbred and testcross hybrids, across years and was slightly higher under water stress. TE also differed among hybrids developed for three agroecological zones, being higher in hybrids bred for the wetter zone, underlining the importance of selecting germplasm according to the target area. Environmental conditions triggered large genotype-by-environment interactions, although TE showed some moderately high heritability. Transpiration efficiency was the second contributor to grain yield after harvest index, hence its relevance in pearl millet breeding programs. Future research on TE in pearl millet should focus (i) on investigating the causes of its plasticity i.e. the GxE interaction (ii) on studying its genetic basis and its association with other important physiological traits.

plant biology↗

Characterization of adaptation mechanisms in sorghum using a multi-reference back-cross nested association mapping design and envirotyping

The identification of haplotypes influencing traits of agronomic interest, with well-defined effects across environments, is of key importance to develop varieties adapted to their context of use. It requires advanced crossing schemes, multi-environment characterization and relevant statistical tools. Here we present a sorghum multi-reference back-cross nested association mapping (BCNAM) population composed of 3901 lines produced by crossing 24 diverse parents to three elite parents from West and Central Africa (WCA-BCNAM). The population was characterized in environments contrasting for photoperiod, rainfall, temperature, and soil fertility. To analyse this multi-parental and multi-environment design, we developed a new methodology for QTL detection and parental effect estimation. In addition, envirotyping data were mobilized to determine the influence of specific environmental covariables on the genetic effects, which allowed spatial projections of the QTL effects. We mobilized this strategy to analyse the genetic architecture of flowering time and plant height, which represent key adaptation mechanisms in environments like West Africa. Our results allowed a better characterisation of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod sensitive and candidate gene Elf3 being insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the WCA-BCNAM constitutes a key genetic resource to feed breeding programs in relevant elite parental lines and develop climate-smart varieties.

genetics↗

Characterization of the pearl millet cultivation environments in India: status and perspectives enabled by expanded data analytics and digital tools

The cultivation of pearl millet in India is experiencing important transformations due to changes in weather, socio-economic trends, and technological progress. In this scope, we propose a new characterization of the pearl millet production environment in India using the latest available data and methodology. For that, we constructed a database incorporating data on various aspects of pearl millet cultivation at the district level from 1998 to 2017. We complemented this analysis using extensive pearl millet agri-system simulations to evaluate crop models abilities to reconstruct and analyse the system at an unprecedented scale. We also proposed a new method to infer system parameters from crop model data. Our results show important differences compared to the characterization currently used. The East part of the pearl millet tract (East Rajasthan, Haryana, Uttar Pradesh, and Madhya Pradesh) emerges as the only region where pearl millet cultivation has grown with potential surplus that is likely exported. Important reductions of pearl millet cultivated area in Gujarat, Maharashtra and Karnataka are potentially due to economy-driven transition to other more pro table crops like cotton, maize, or castor bean. The data used also point toward a constant increase of the rain during the growing season which could have major consequences on the future of this crop, with potential positive effects like extra yield but also negative like extra pressure due to more intense and erratic rainfall or transition to more pro table crops requiring more water. Despite difficulties to predict pearl millet yield in rapidly changing environments, the tested crop models reflected reasonably well the pearl millet production system, thus, setting the base for effective system design in future climatic scenarios. Our data and results have been gathered in an open-source interactive online application.

plant biology↗

New algorithm for pearl millet modelling in APSIM allowing a mechanistic simulation of tillers

We present a new algorithm for pearl millet simulation in APSIM. Compared to the actual released model, this new model increases the ability to simulate dynamic tillers by integrating recent progresses about biological understanding of the tillering mechanism. The new algorithm also offers the possibility to have an increased genetic control over key functions like canopy development and tillering through additional genotype related parameters. Next to model description, we also present the parametrization of 9444 and HHB 67-2, two genotypes broadly used in India. Overall, we could show that the new algorithm is able to reconstruct the main plant function like biomass accumulation and tillering. Some margin of improvement remains concerning the simulation of tiller cessation.

plant biology↗

Transpiration and water use efficiency of sorghum canopies have a large genetic variability and are positively related under naturally high evaporative demand.

Indoor experiments with individual plants often show that transpiration rate is restricted under high vapor pressure deficit (VPD), resulting in a plateau of transpiration that increases water use efficiency (WUE) of some genotypes. We tested this hypothesis outdoors during dry or rainy seasons of India and Senegal, based on the response of the transpiration of canopy-grown sorghum plants to the reference evapotranspiration that takes both light and VPD into account. This response showed no plateau at high evaporative demand in 47 genotypes, but a large genetic variability was observed for the slope of the relationship over the whole range of evaporative demand. Unexpectedly, this slope was genetically correlated with WUE in two experiments with high evaporative demand: genotypes that most transpired had the highest WUE. Conversely, a negative correlation was observed under low evaporative demand. Genotypes with high WUE and response to evaporative demand were also those allowing maximum light penetration into the canopy. We suggest that this caused the observed high WUE of these genotypes because leaves within the canopy had sufficient light for photosynthesis whereas we observed a lower VPD in the canopy than in open air when leaf area index reached 2.5-3, thereby decreasing transpiration. HighlightsThe transpiration response to evaporative demand was genetically variable and correlated to WUE: genotypes that most transpired had highest light penetration towards leaves subjected to lower VPD than in air.

physiology↗