Breeding maize hybrids for drought tolerance would significantly reduce yield loss due to drought in southern Africa. Mode of gene action controlling yield and secondary traits was investigated by mating 27 inbred lines, in sets according to a North Carolina design II scheme. The resultant 72 experimental and eight commercial hybrids were evaluated in 8 · 10 a-lattice design with two replications, in four drought and two non-drought environments. Under drought conditions, only general combining ability (GCA) variance was significant for yield, indicating predominance of additive effects. In non-drought environments, both GCA and specific combining ability variances were significant for yield, indicating importance of additive and non-additive effects, respectively. Contributions of male (GCA m ) and female GCA (GCA f ) effects to hybrids varied depending on the trait and conditions. Superior GCA f to GCA m effects for yield under drought conditions, and for ASI, prolificacy and ear aspect under both drought and non-drought conditions, suggested that maternal effects might have modified these traits. Larger GCA m than GCA f for ASI and silking dates under normal conditions indicated that paternal genotypes played a greater role in determining these traits. Similar GCA m and GCA f for yield under normal conditions, silking and anthesis dates under drought indicated that both parents made similar contribution to hybrids. Possibly, complications due to modification of traits by cytoplasmic effects and cross-over G · E for yield might partly explain why only a few drought tolerant hybrids have been developed. Practical implications of these findings in breeding drought tolerance in maize are discussed.

BackgroundGray leaf spot (GLS) is a globally important foliar disease of maize. Cercospora zeina, one of the two fungal species that cause the disease, is prevalent in southern Africa, China, Brazil and the eastern corn belt of the USA. Identification of QTL for GLS resistance in subtropical germplasm is important to support breeding programmes in developing countries where C. zeina limits production of this staple food crop.ResultsA maize RIL population (F7:S6) from a cross between CML444 and SC Malawi was field-tested under GLS disease pressure at five field sites over three seasons in KwaZulu-Natal, South Africa. Thirty QTL identified from eleven field trials (environments) were consolidated to seven QTL for GLS resistance based on their expression in at least two environments and location in the same core maize bins. Four GLS resistance alleles were derived from the more resistant parent CML444 (bin 1.10, 4.08, 9.04/9.05, 10.06/10.07), whereas the remainder were from SC Malawi (bin 6.06/6.07, 7.02/7.03, 9.06). QTLs in bin 4.08 and bin 6.06/6.07 were also detected as joint QTLs, each explained more than 11% of the phenotypic variation, and were identified in four and seven environments, respectively. Common markers were used to allocate GLS QTL from eleven previous studies to bins on the IBM2005 map, and GLS QTL “hotspots” were noted. Bin 4.08 and 7.02/7.03 GLS QTL from this study overlapped with hotspots, whereas the bin 6.06/6.07 and bin 9.06 QTLs appeared to be unique. QTL for flowering time (bin 1.07, 4.09) in this population did not correspond to QTL for GLS resistance.ConclusionsQTL mapping of a RIL population from the subtropical maize parents CML444 and SC Malawi identified seven QTL for resistance to gray leaf spot disease caused by C. zeina. These QTL together with QTL from eleven studies were allocated to bins on the IBM2005 map to provide a basis for comparison. Hotspots of GLS QTL were identified on chromosomes one, two, four, five and seven, with QTL in the current study overlapping with two of these. Two QTL from this study did not overlap with previously reported QTL.

Key message Historical data from breeding programs can be efficiently used to improve genomic selection accuracy, especially when the training set is optimized to subset individuals most informative of the target testing set. Abstract The current strategy for large-scale implementation of genomic selection (GS) at the International Maize and Wheat Improvement Center (CIMMYT) global maize breeding program has been to train models using information from full-sibs in a “test-half-predict-half approach.” Although effective, this approach has limitations, as it requires large full-sib populations and limits the ability to shorten variety testing and breeding cycle times. The primary objective of this study was to identify optimal experimental and training set designs to maximize prediction accuracy of GS in CIMMYT’s maize breeding programs. Training set (TS) design strategies were evaluated to determine the most efficient use of phenotypic data collected on relatives for genomic prediction (GP) using datasets containing 849 (DS1) and 1389 (DS2) DH-lines evaluated as testcrosses in 2017 and 2018, respectively. Our results show there is merit in the use of multiple bi-parental populations as TS when selected using algorithms to maximize relatedness between the training and prediction sets. In a breeding program where relevant past breeding information is not readily available, the phenotyping expenditure can be spread across connected bi-parental populations by phenotyping only a small number of lines from each population. This significantly improves prediction accuracy compared to within-population prediction, especially when the TS for within full-sib prediction is small. Finally, we demonstrate that prediction accuracy in either sparse testing or “test-half-predict-half” can further be improved by optimizing which lines are planted for phenotyping and which lines are to be only genotyped for advancement based on GP.

Rice is an important staple food and cash crop. Although many varieties of rice have been developed to date, few are adopted possibly because researchers did not take into account farmers’ preferences and perceptions on varieties during the development process. Because farmers increasingly rely on low‐yielding landraces, production fails to meet demand. To provide an understanding of farmers’ preferences for rice cultivars and perceptions on drought stress and management practices as inputs to rice breeding research, this study was conducted in the Sikasso region of Mali in September 2005 using participatory rural appraisal approach. A total number of 125 farmers were randomly selected from 10 villages in three ecologies and interviewed individually and in groups. Results showed that farmers’ preferences, crop management practices and ranking of production constraints differed significantly across ecologies. Whereas farmers in the irrigated ecologies preferred high‐yielding, long duration rice varieties, those in the upland and lowland ecologies preferred tall plants of short duration. While upland and lowland farmers preferred red and white long grains, respectively, irrigated ecologies were indifferent about grain colour. Farmers appeared willing to trade‐off yield for grain quality and plant height, inconsistent with traditional breeders’ selection criteria. The high preference for tall varieties among farmers in the upland and lowland ecologies also contrasted sharply with the model of dwarf rice varieties responsible for the green revolution in Asia. The implication of these findings for rice breeders is that different plant idiotypes complemented by effective drought management practices should target different ecologies to increase impact.

Gray leaf spot disease (GLS; caused by Cercospora zeae‐maydis Tehon and Daniels) is among the major maize (Zea mays L.) production constraints in southern Africa. Maize is predominantly grown by small‐scale farmers without fungicides; hence, there is need to develop GLS resistant hybrids. There is limited information about the mode of inheritance for GLS resistance in regionally adapted germplasm. This study was initiated to determine gene action controlling GLS resistance. Seventy‐two hybrids were generated by mating 27 inbred lines in a North Carolina design II scheme. Experimental and check hybrids were evaluated in an 8 by 12 α‐lattice design with two replications at three locations, during the 2004–2005 season. There was significant variation among the hybrids for GLS resistance and yield. Inbreds L13, L15, L18, L19, and L24, from A, N3, B, K, and SC heterotic groups, respectively, contributed high levels of resistance to hybrids. Both general combining ability (GCA) and specific combining ability (SCA) effects were highly significant (P < 0.01), but the predominance of GCA for GLS (86%) and yield (74%) indicated that additive effects were more important than nonadditive gene action in controlling both traits. Hybrids ranked similarly for GLS across environments, suggesting that few significant crossover genotype by environment interactions, which would cause problems in hybrid selection, were observed. Overall, results indicated that it would be readily possible to develop inbred lines with high GLS resistance from this germplasm.