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Location-specific weather and climate information together with related advisory services are one of the crucial drivers of development in the 21st century particularly in Sub-Saharan Africa. However, there still exist significant gaps in provision of weather and climate information at scales that effectively address the needs of local people for instance; local farmers and pastoralists. This therefore force local people to rely on indigenous knowledge (IK), to observe and forecast weather conditions. This situation does not exclude Uganda, and thus the current study assessed the efficacy of integrating indigenous knowledge systems into modern weather observational instruments in order to boost and act as a backup mechanism for modern weather observational instruments to increase accuracy and wide coverage of weather observations within Uganda. Results indicated that, respondents across the two pilot sites use a combination of plants, animals, insects, and human behaviours, meteorological and astrological indicators to observe and predict local prevailing weather conditions. Majority of the respondents particularly in Masaka district, believed that the use of indigenous knowledge to observe weather and climatic events is very reliable compared to their counterparts in Entebbe Municipality. Therefore, the integration of indigenous knowledge system in scientific weather observations is very vital.

Background: Xanthomonas oryzae pv. Oryzae (Xoo), the causal agent of rice bacterial blight disease has been extensively characterized and loci against different races identified. Many rice cultivars have been developed and utilized to combat the disease, however due to rapid evolution of Xoo, a number of resistances have broken-down. The continuous challenge of ever evolving Xoo and breakdown of resistance in cultivated rice varieties makes it even more important to discover new loci to enable sustainable durable deployment of broad-spectrum resistance genes in elite breeding lines. African germplasm can be exploited as reservoirs of useful genetic variation for bacterial blight (BB) resistance. This study was conducted to identify loci associated to BB resistance and new genetic donors for breeding program. Results: To identify candidate sources of resistance for advancing breeding, we used highly four virulent strains of Xoo (PXO99, MAI1, BAI3 and Xoo3-1) to screen 78 East African accessions by genome-wide association studies. The core genetic base of the diverse accessions exhibited high degree of resistance to the Xoo strains. 50.63% of the accessions were highly resistant to the Philippines strain PX099, while 20.25% were highly susceptible to the virulent West African strain MAI1. Two novel resistant loci significantly associated hotspots were identified using 1901 SNPs. The two hits were located on chromosome 12 (Xa25) and Chr. 6 (Xa7, Xa27, Xa33). Conclusions: Our finding have identified novel loci that gives a useful basis for more investigation and a wide core genetic pool of high resistance for broad-spectrum resistance genetic improvement.

Sorghum is the third most important staple cereal crop in Uganda after maize and millet. Downy mildew disease is one of the most devastating fungal diseases which limits the production and productivity of the crop. The disease is caused by an obligate fungus, Peronosclerospora sorghi (Weston & Uppal) with varying symptoms. Information on the genetic diversity and population structure of P.sorghi in sorghum is imperative for the screening and selection for resistant genotypes and further monitoring possible mutant(s) of the pathogen. Isolates of P. sorghi infecting sorghum are difficult to discriminate when morphological descriptors are used. The use of molecular markers is efficient, and reliably precised for characterizing P. sorghi isolates. This study was undertaken to assess the level of genetic diversity and population structure that exist in P. sorghi isolates in Uganda. A total of 195 P. sorghi isolates, sampled from 13 different geographic populations from 10 different regions (agro-ecological zones) was used. Eleven (11) molecular markers, comprising of four Random amplified microsatellite (RAM) and seven (7) Inter-Simple Sequence Repeat (ISSR) markers were used in this study. The analysis of molecular variation (AMOVA) based on 11 microsatellite markers showed significant (P < 0.001) intra-population (88.9 %, PhiPT = 0.111) and inter-population (8.4 %, PhiPR = 0.083) genetic variation, while the genetic variation among regions (2.7 %, PhiRT = 0.022) was not significant. The highest genetic similarity value (0.987 = 98.7 %) was recorded between Pader and Lira populations and the lowest genetic similarity (0.913 = 91.3 %) was observed between Namutumba and Arua populations. The mean Nei's genetic diversity index (H) and Shannon Information Index (I) were 0.308 and 0.471 respectively. Seven distinct cluster groups were formed from the 195 P. sorghi isolates based on their genetic similarity. Mantel test revealed no association between genetic differentiation and geographical distance (R2 = 0.0026, p = 0.02) within the 13 geographic populations.

In sweet potato, an anti-virus defense mechanism termed reversion has been postulated to lead to virus freedom from once infected plants. The objectives of this study were to identify anti-virus defense genes and evaluate their segregation in progenies. Reference genes from different plant species were used to assemble transcript sequences of each sweet potato defense gene in silico. Sequences were used for evaluate phylogenetic relationships with similar genes from different plant species, mining respective defense genes and thereafter developing simple sequence repeats (SSRs) for segregation analysis. Eight potential defense genes were identified: RNA dependent RNA polymerases 1, 2, 5, and 6; Argonaute 1, and Dicer-like 1, 2, and 4. Identified genes were differentially related to those of other plants and were observed on different chromosomes. The defense genes contained mono-, di-, tri-, tetra, penta-, and hexa-nucleotide repeat motifs. The SSR markers within progenies were segregated in disomic, co-segregation, nullisomic, monosomic, and trisomic modes. These findings indicate the possibility of deriving and utilizing SSRs using published genomic information. Furthermore, and given that the SSR markers were derived from known genes on defined chromosomes, this work will contribute to future molecular breeding and development of resistance gene analogs in this economically important crop.