Genotype-by-environment interaction analysis is vital for cultivar release, and to identify suitable crop production sites. The current study aimed to determine sorghum grain yield stability and adaptability and to identify the most informative and representative environments for sorghum grain yield performance in Uganda. Sorghum grain yield data of eight (08) genotypes; ICSR 160, IS8193, IESV92043DL, IESV92172DL, GE17/1/2013A, GE35/1/2013A, SESO1, and SESO3 tested across eight (08) major sorghum production area in Uganda for two consecutive seasons of 2017 using randomised complete block design with 2 replications were analysed via Additive Main effects and Multiplicative Interaction (AMMI) and Genotype Main Effect and Genotype by Environment interaction effects (GGE) using PB tools. Genotype IESV92043DL was the ideal genotype in the entire test environments with mean grain yield of 2783 kg ha-1 however genotype ICSR 160 had the highest grain yield of 2823 kg ha-1 across all the test environment. On the other hand, GE17/1/2013A was the most stable and adapted genotype across all the test environment. Of the eight (08) environments tested, biplot analysis precisely grouped the test environments into two presumed mega-environments with the best genotype being IS8193 and ICSR 160. Out of eight (08) trial sites, two (02) environments; Abi and Mayuge were the most representative and informative environment for sorghum grain yield performance in Uganda.

Pearl millet (Pennisetum glaucum) is an important food and cash crop for many people living in the semi arid areas of Uganda. But information about the common diseases and their effect on yield is lacking yet it is important in designing a realistic and focused pearl millet breeding programme aimed at increasing yield. A disease survey was done in 2012 in the farmers' fields in the predominantly pearl millet growing districts of Kumi and Katakwi in eastern and Kitgum and Lamwo in northern Uganda to identify the major diseases of pearl millet and establish their incidence, severity correlation and effect on grain yield. The aim of the study therefore was to identify the major pearl millet diseases that affect production in Uganda. In terms of incidence, rust (Puccinia substriata) (73.58%) was the most frequent disease followed by ergot (Claviceps fusiformis) (62.98%), then leaf blast (Pyricularia grisea) (61.25%) and smut (Moesziomyces penicillariae) (26.76%). However, in terms of severity, leaf blast (62.20%) was the most severe followed by rust (43.33%), ergot (29.46%) and smut (14.18%). Using SPSSv20, backward model reduction regression of disease parameters against grain yield, results show disease severities of rust, ergot, leaf blast and incidences of smut and rust were the most important in affecting grain yield. The correlation of disease severity with grain yield further indicated that ergot and rust severities were causes of the significant effect on yield.

Pearl millet is grown by inhabitants of the semi-arid zones. Due to the unpredictable climatic conditions the genotype-by-environment interaction (GEI) makes it hard to select genotypes adapted to such conditions. The study objectives therefore were to analyse the patterns of GEI and to identify superior genotypes for grain yield and rust resistance. Seventy six genotypes were planted in four environments in 4×19 alpha design with two replications. The ANOVA results showed that main effects of environments were significant (p ≤ 0.05) for grain yield and highly significant (p ≤ 0.001) for rust resistance while the main effects of the genotypes and their interactions with environments were also important for grain yield and rust severity at 50% physiological maturity. The GGE biplot analysis revealed that environments associated with more rains received during vegetative phase performed better than those receiving more rains during post-anthesis phase. The winner in the best environment for grain yield was ICMV3771×SDMV96053 while Shibe×CIVT9206 and Shibe×GGB8735 were the best for rust resistance.

Sorghum is a C4 grass native in the semi-arid environments of the African sub-Saharan and consequently chilling stress can affect the performance of the crop, especially at the reproductive stages. Moreover, a significant delay of flowering and maturity was observed when sorghum grows under low temperatures regions, and consequently farmers in highland areas of Uganda face yield penalties. Forty genotypes were evaluated in 2017B and 2018A seasons under non-stress (Kabanyolo) and cold stress (Kachwekano and Zombo) field conditions. Data were recorded on: Days to 50% flowering, days to physiological maturity, culm height, panicle length, panicle weight, kernel weight per panicle, and thousand grain weight. Mean comparison of most agronomic traits recorded indicated high significant differences for season-by-genotype, location-by-genotypes, and the three-way interaction (GxLxS). This indicates that cold stress significantly affects yield components. Significant positive correlation was obtained between days to 50% flowering, days to maturity, and culm height, which suggested that simultaneous improvement of these traits is possible. Some genotypes (IESV 91003LT, IESV 91105LT and IS 29376) were best ranked in normal environment but poorly performed in cold environments, which indicates lack of adaptation in highland. BM6, Cytanobe, IESV 91018, IESV 91609, IS 25563 showed generally good performance and stability in all locations. Therefore, these genotypes can be used as parental lines for further breeding process.

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