Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/13

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Genetic variation for cold tolerance in two nested association mapping populations
(2023) Revilla, Pedro; Butrón, Ana; Rodriguez, Víctor Manuel; Rincent, Renaud; Charcosset, Alain; Giauffret, Catherine; Melchinger, Albrecht E.; Schön, Chris-Carolin; Bauer, Eva; Altmann, Thomas; Brunel, Dominique; Moreno-González, Jesús; Campo, Laura; Ouzunova, Milena; Álvarez, Ángel; Ruíz de Galarreta, José Ignacio; Laborde, Jacques; Malvar, Rosa Ana
Cold reduces maize (Zea mays L.) production and delays sowings. Cold tolerance in maize is very limited, and breeding maize for cold tolerance is still a major challenge. Our objective was to detect QTL for cold tolerance at germination and seedling stages. We evaluated, under cold and control conditions, 919 Dent and 1009 Flint inbred lines from two nested association mapping designs consisting in 24 double-haploid populations, genotyped with 56,110 SNPs. We found a large diversity of maize cold tolerance within these NAM populations. We detected one QTL for plant weight and four for fluorescence under cold conditions, as well as one for plant weight and two for chlorophyll content under control conditions in the Dent-NAM. There were fewer significant QTL under control conditions than under cold conditions, and half of the QTL were for quantum efficiency of photosystem II. Our results supported the large genetic discrepancy between optimal and low temperatures, as the quantity and the position of the QTL were very variable between control and cold conditions. Furthermore, as we have not found alleles with significant effects on these NAM designs, further studies are needed with other experimental designs to find favorable alleles with important effects for improving cold tolerance in maize.
Remote sensing of maize plant height at different growth stages using UAV-based digital surface models (DSM)
(2022) Oehme, Leon Hinrich; Reineke, Alice-Jacqueline; Weiß, Thea Mi; Würschum, Tobias; He, Xiongkui; Müller, Joachim
Plant height of maize is related to lodging resistance and yield and is highly heritable but also polygenic, and thus is an important trait in maize breeding. Various manual methods exist to determine the plant height of maize, yet they are labor-intensive and time consuming. Therefore, we established digital surface models (DSM) based on RGB-images captured by an unmanned aerial vehicle (UAV) at five different dates throughout the growth period to rapidly estimate plant height of 400 maize genotypes. The UAV-based estimation of plant height (PHUAV) was compared to the manual measurement from the ground to the highest leaf (PHL), to the tip of the manually straightened highest leaf (PHS) and, on the final date, to the top of the tassel (PHT). The best results were obtained for estimating both PHL (0.44 ≤ R2 ≤ 0.51) and PHS (0.50 ≤ R2 ≤ 0.61) from 39 to 68 days after sowing (DAS). After calibration the mean absolute percentage error (MAPE) between PHUAV and PHS was in a range from 12.07% to 19.62%. It is recommended to apply UAV-based maize height estimation from 0.2 m average plant height to maturity before the plants start to senesce and change the leaf color.

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