| Literature DB >> 32777163 |
John N Ferguson1,2, Lorna McAusland1, Kellie E Smith1, Adam H Price3, Zoe A Wilson1, Erik H Murchie1.
Abstract
A key target for the improvement of Oryza sativa (rice) is the development of heat-tolerant varieties. This necessitates the development of high-throughput methodologies for the screening of heat tolerance. Progress has been made to this end via visual scoring and chlorophyll fluorescence; however, these approaches demand large infrastructural investments to expose large populations of adult plants to heat stress. To address this bottleneck, we investigated the response of the maximum quantum efficiency of photosystem II (PSII) to rapidly increasing temperatures in excised leaf segments of juvenile rice plants. Segmented models explained the majority of the observed variation in response. Coefficients from these models, i.e. critical temperature (Tcrit ) and the initial response (m1 ), were evaluated for their usability for forecasting adult heat tolerance, measured as the vegetative heat tolerance of adult rice plants through visual (stay-green) and chlorophyll fluorescence (ɸPSII) approaches. We detected substantial variation in heat tolerance of a randomly selected set of indica rice varieties. Both Tcrit and m1 were associated with measured heat tolerance in adult plants, highlighting their usability as high-throughput proxies. Variation in heat tolerance was associated with daytime respiration but not with photosynthetic capacity, highlighting a role for the non-photorespiratory release of CO2 in heat tolerance. To date, this represents the first published instance of genetic variation in these key gas-exchange traits being quantified in response to heat stress in a diverse set of rice accessions. These results outline an efficient strategy for screening heat tolerance and accentuate the need to focus on reduced rates of respiration to improve heat tolerance in rice.Entities:
Keywords: zzm321990Oryza sativazzm321990; chlorophyll fluorescence; heat stress; high-throughput phenotyping; photosynthesis; stay-green; technical advance
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Year: 2020 PMID: 32777163 DOI: 10.1111/tpj.14956
Source DB: PubMed Journal: Plant J ISSN: 0960-7412 Impact factor: 6.417