RESPONSE OF LOCALLY ADAPTED PEARL MILLET POPULATIONS TO S1 PROGENY RECURRENT SELECTION FOR GRAIN YIELD AND RESISTANCE TO RUST

In the semi-arid zones of Uganda, pearl millet ( Pennisetum glaucum (L.) R. Br.) is mainly grown for food and income; but rust (Puccinia substriata var indica (L.) R. Br.) is the main foliar constraint lowering yield. The objective of the study was to genetically improve grain yield and rust resistance of two locally adapted populations (Lam and Omoda), through two cycles of modified phenotypic S1 progeny recurrent selection. Treatments included three cycles of two locally adapted pearl millet populations, evaluated at three locations. Significant net genetic gain for grain yield (72 and 36%) were achieved in Lam and Omoda populations, respectively. This led to grain yield of 1,047 from 611 kg ha-1 in Lam population and 943 from 693 kg ha-1 in Omoda population. Significant improvement in rust resistance was achieved in the two populations, with a net genetic gain of -55 and -71% in Lam and Omoda populations, respectively. Rust severity reduced from 30 to 14% in Lam population and from 57 to 17% in Omoda population. Net positive genetic gains of 68 and 8% were also achieved for 1000-grain weight in Lam and Omoda, respectively. Traits with a net negative genetic gain in both populations were days to 50% flowering, days to 50% anthesis, days to 50% physiological maturity, flower-anthesis interval, plant height and leaf area.

GGE biplot analysis of multi-environment yield trials of rice produced in a temperate climate

Low temperature is one of the main environmental constraints for rice ( Oryza sativa L.) grain production yield. It is known that multi-environment studies play a critical role in the sustainability of rice production across diverse environments. However, there are few studies based on multi-environment studies of rice in temperate climates. The aim was to study the performance of rice plants in cold environments. Four experimental lines and six cultivars were evaluated at three locations during three seasons. The grain yield data were analyzed with ANOVA, mixed models based on the best linear unbiased predictors (BLUPs), and genotype plus Genotype × Environment interaction (GGE) biplot. High genotype contribution (> 25%) was observed in grain yield and the interaction between genotype and locations was not very important. Results also showed that ‘Quila 241319’ was the best experimental line with the highest grain yield (11.3 t ha-1) and grain yield stability across the environments; commercial cultivars were classified as medium grain yield genotypes.

Biopsy case mix and diagnostic yield at a Malawian central hospital

Cancer is a major disease burden worldwide resulting in high morbidity and mortality. It is the leading cause of mortality in developed countries and is one of the three leading causes of death for adults in developing countries. Pathological examination of tissue biopsies with histological confirmation of a correct cancer diagnosis is central to cancer care. Without an accurate and specific pathologic diagnosis, effective treatment cannot be planned or delivered. In addition, there are marked geographical variations in incidence of cancer overall, and of the specific cancers seen. Much of the published literature on cancer incidence in developing countries reflects gross estimates and may not reflect reality. Performing baseline studies to understand these distributions lays the groundwork for further research in this area of cancer epidemiology. Our current study surveys and ranks cancer diagnoses by individual anatomical site at Queen Elizabeth Central Hospital (QECH) which is the largest teaching and referral hospital in Malawi. A retrospective study was conducted reviewing available pathology reports over a period of one full year from January 2010 to December 2010 for biopsies from patients suspected clinically of having cancer. There were 544 biopsies of suspected cancer, taken from 96 anatomical sites. The oesophagus was the most common biopsied site followed by breast, bladder, bone, prostate, bowel, and cervical lymph node. Malignancies were found in biopsies of the oesophagus biopsies (squamous cell carcinoma, 65.1%; adenocarcinoma, 11.6%), breast (57.5%), bladder (squamous cell carcinoma, 53.1%) and stomach (37.6%). Our study demonstrates that the yield of biopsy for clinically suspected malignancy was greater than 50% for the 11 most common sites and provides a current survey of cancer types by site present in the population reporting to our hospital.

Effect of foliar application of Cu, Zn, and Mn on yield and quality indicators of winter wheat grain

Micronutrients are part of many crucial physiological plant processes. The combined application of N and micronutrients helps in obtaining grain yield with beneficial technological and consumer properties. The main micronutrients needed by cereals include Cu, Mn, and Zn. The subject of this study was to determine yield, quality indicators (protein content and composition, gluten content, grain bulk density, Zeleny sedimentation index, and grain hardness), as well as mineral content (Cu, Zn, Mn, Fe) in winter wheat grain ( Triticum aestivum L.) fertilized by foliar micronutrient application. A field experiment was carried out at the Educational and Experimental Station in Tomaszkowo, Poland. The application of mineral fertilizers (NPK) supplemented with Cu increased Cu content (13.0%) and ω, α/β, and γ (18.7%, 4.9%, and 3.4%, respectively) gliadins in wheat grain. Foliar Zn fertilization combined with NPK increased Cu content (14.9%) as well as high (HMW) and low molecular weight (LMW) glutenins (38.8% and 6.7%, respectively). Zinc fertilization significantly reduced monomeric gliadin content and increased polymeric glutenin content in grain, which contributed in reducing the gliadin:glutenin ratio (0.77). Mineral fertilizers supplemented with Mn increased Fe content in wheat grain (14.3%). It also significantly increased protein (3.8%) and gluten (4.4%) content, Zeleny sedimentation index (12.4%), and grain hardness (18.5%). Foliar Mn fertilization increased the content of ω, α/β, and γ gliadin fractions (19.9%, 9.5%, and 2.1%, respectively), as well as HMW and LMW glutenins (18.9% and 4.5%, respectively). Mineral NPK fertilization, combined with micronutrients (Cu + Zn + Mn), increased Cu and Zn content in grain (22.6% and 17.7%, respectively). The content of ω, α/β, and γ gliadins increased (20.3%, 10.5%, and 12.1%, respectively) as well as HMW glutenins (7.9%).

Diversity and path coefficient analysis of Southern African maize hybrids

Detailed knowledge on genetic diversity among germplasm is important for hybrid maize ( Zea mays L.) breeding. The objective of the study was to determine genetic diversity in widely grown hybrids in Southern Africa, and compare effectiveness of phenotypic analysis models for determining genetic distances between hybrids. Fifty hybrids were evaluated at one site with two replicates. The experiment was a randomized complete block design. Phenotypic and genotypic data were analyzed using SAS and Power Marker respectively. There was significant (p < 0.01) variation and diversity among hybrid brands but small within brand clusters. Polymorphic Information Content (PIC) ranged from 0.07 to 0.38 with an average of 0.34 and genetic distance ranged from 0.08 to 0.50 with an average of 0.43. SAH23 and SAH21 (0.48) and SAH33 and SAH3 (0.47) were the most distantly related hybrids. Both single nucleotide polymorphism (SNP) markers and phenotypic data models were effective for discriminating genotypes according to genetic distance. SNP markers revealed nine clusters of hybrids. The 12-trait phenotypic analysis model, revealed eight clusters at 85%, while the five-trait model revealed six clusters. Path analysis revealed significant direct and indirect effects of secondary traits on yield. Plant height and ear height were negatively correlated with grain yield meaning shorter hybrids gave high yield. Ear weight, days to anthesis, and number of ears had highest positive direct effects on yield. These traits can provide good selection index for high yielding maize hybrids. Results confirmed that diversity of hybrids is small within brands and also confirm that phenotypic trait models are effective for discriminating hybrids.