Common bean is a queen of legumes and a major source of protein and iron for many people in Lesotho. It is speculated that bean production, area planted and yield of common beans have been erratic throughout the period of 58 years from 1961-2017. This has not been verified statistically and documented, hence this study has been conducted to dispel or dispute the speculation. The object of the study was therefore to (a) estimate the trend in the production, area and yield of common bean over a period of six decades, (b) identify the key factors influencing bean production. Data on trend of common beans were obtained from Bureau of Statistics (2017), while data for factors affecting production were obtained from Lesotho Meteorological Service (2017). Excel spread sheet was employed to determine the trend of bean over the period of 58 years and ANOVA was to establish the significance of the factors contributing towards bean production. The results showed an average increase of 44% in the production, 42% increase in area planted and 2% decrease in yield. There were droughts and peaks during this time-period differing greatly. The factors of production did not significantly influence the bean production.
A large collection of maize germplasm is introduced annually to Lesotho from CYMMIT in Zimbabwe for evaluation of adaptability and yield performance. This collection is not characterized for degree of similarities and dissimilarities using morphological and other markers. The study was conducted with the objectives of (a) estimating genetic distance among maize cultivars using cluster analysis and (b) identifying morphological characters with high discriminatory power to segregate maize cultivars. The study was conducted at National University of Lesotho, Experimental farm. Randomized Complete Block Design was applied with ten treatments and three replications. Data collected using Descriptor compiled by International Board of Plant Genetic Resource Unit included number of leaves per plant, tassel colour, number of cobs, silk colour, stem colour, plant height, number of ears, ear length, cob diameter, number of kernels, kernel arrangement, kernel colour, shape of upper surface, kernel type, leaf length and tassel length. Data were subjected to GENSTAT software package to generate cluster analysis and perform principal component analysis. The results of cluster analysis revealed two big groups, of which one consisted of six cultivars and another consisted of four cultivars. Besides, there was one outlier. Two big groups were further divided into sub-groups, Three principal component analyses were used to analyze the results, which constituted 65.37% of the total variation. The first one showed variation of 26.93%, the second one showed 20.65% while the third one had 17.79%. The first principal component was constituted by ear length, tillering, maize height, total number of kernels, cross-section of cob and stem colour. The characters comprising second principal component were kernel type, kernel row arrangement, silk colour, number of ear and number of kernel row. Lastly, the character influencing separations along third principal component were number of kernel row, silk colour and number of leaves. The study was able to distinguish the cultivars.
Characterisation of Wheat (Triticum Aestivum L.) Cultivars Grown In Lesotho by Morphological Markers (Published)
Wheat is one of the major cereal crops grown in Lesotho, ranking third after maize and sorghum. Cultivars of wheat are imported from South Africa without characterization. The study was therefore conducted with the following objectives; (1) to distinguish wheat cultivars grown by farmers, (2) to estimate genetic distance among wheat cultivars and (3) to identify the characters that have high discriminatory power. Complete Randomized Block Design with ten treatments and three replications were applied. Data were collected using Descriptor and analysed using GENSTAT software to perform cluster and principal component analysis. The first three principal components constituted 84.572% of the total variation. First principal component variation accounted for 55.738%, while second principal component contributed 15.737% and third principal component constituted 12.858%. Characters responsible for variation in the first component were spikelets, spike height and tillers. Separation among second component was brought about by plant height, reproductive tillers and seeds per spike. Variation in component three was due to glume hairiness, seed size and plant height. Cluster analysis formed two groups, A and B, and one outlier. Group A comprised of Gariep, Koonap, Elands and Senqu while Group B consisted SST374, SST356, PAN3195, PAN3379 and TugelaDN. Group C was an outlier containing Matlabas. The findings showed that the cultivars were different from each other and as such genetic variation exists that broaden the spectrum of germplasm, from which farmers can make a wider choice.
Genetic diversity of common bean (Phaseolus vulgaris L.) introduced for adaptation in Lesotho (Published)
Common beans are introduced in Lesotho from CIAT-Malawi annually to evaluate them for adaptation and other characters of economic importance. They are not being characterized for identity, therefore the study was conducted at National University of Lesotho located in the Maseru District of Lesotho with specific objectives of (1) estimating genetic distances among the common bean genotypes using morphological features and (2) identifying morphological characteristics that contributed to discrimination of these cultivars. Randomized Complete Block Design was applied with four replications. Twenty cultivars of common beans from CIAT-Malawi were used as treatments. Data were collected using descriptor of common beans compiled by International Board of Genetic Resources Unit. Data generated were subjected to cluster analysis and principal component analysis using Genstat recover (2015). Results of cluster analysis revealed four groups, of which two consisted of five cultivars, another had four and the last one only two cultivars. Besides, there were three outliers. The results of principal component analysis showed the total variation accounted for by both principal component 1 and 2 was 35.95% with each constituting 18.62 and 17.33 %, respectively. The characters responsible for variation from the first principal component analysis were seed shape, colour of flowers, colour of wings, seed-coat pattern and pod beak orientation. The characters influencing separation along the second principal component were number of locules per pod, number of seeds per pod, leaflet length, days to flowering and pod colour. It can be deduced that the cultivars broad in to Lesotho is diverse broadening the genetic base of the existing common bean genotypes
Variability in Yield and Yield Components among Common Bean (Phaseolus Vulgaris L.) Genotypes (Published)
Common bean is an important leguminous crop grown by farmers for home consumption and local market in Lesotho. Its low productivity has been a great concern necessitating introduction of new improved cultivars that are tested for adaptation and yield potential. The study was conducted at National University of Lesotho located in the Maseru District of Lesotho with specific objectives of (1) determining the difference in yield and yield components of common bean genotypes obtained from CIAT and also (2) determining correlation coefficient among the yield components of the genotypes. Randomized Complete Block Design was applied with four replications to lay-out an experiment. Twenty cultivars of common beans obtained from CIAT were used as treatments. Parameters measured were plant height, number of pods per plant, number of seeds per pod and weight of 100 seeds (g). Data generated were subjected to analysis of variance using Genstat recovery version (2015). The results revealed significant differences in number of pods per plant, yield and plant height among twenty cultivars. No significant difference was obtained among different bean cultivars for weight of 100 seeds per pod and number of pods per plant. Number of pod per plant showed a positive correlation between number of seed per pod, plant height and seed weight per pod but had negative correlation with weight per 100 seeds. Seed weight had negative correlation with all components of beans.
Wheat being the third most important cereal crop in Lesotho, after Maize and Sorghum, has been decreasing in production, area planted and yield. This decline has not been determined using statistical analysis. The objectives of the study were to (1) determine trend in wheat production, area planted and yield, (2) estimate regression coefficients of factors affecting wheat and (3) establish correlation coefficient of these factors. Time series data from 1961 to 2013 on total production of wheat, area planted, yield, rainfall and temperature were captured from FAOSTAT (2013). GENSTAT software was perform statistical analysis. The results revealed a dramatic decline in production, area planted and yield of 77%, 82% and 33.16%, respectively. Regression analysis revealed significant difference (p>0.01) among the regrsessors and each regressor had elasticity coefficient influencing wheat production. Correlation analysis showed that yield was highly correlated (r =0.6678) with area and moderately correlated with temperature (r =0.363) and rainfall (r = 0.2011).
Aims of paper were: to compare area planted and harvested sorghum; determine production trend over the time-period of 53 years; estimate productivity trend and growth rate; and compare National Cereals supply–demand balance. Time series data collected from FAOSTAT and Bureau of Statistics spanning 1960 to 2013 were subjected to GENSTAT for statistical analysis. Results showed persistent decline in area planted and harvested. Area under sorghum cultivation, production and yield fluctuated erratically throughout study period. Production decreased from 84 000 tonnes in 1975 to 22 000 tonnes in 2010, with only 18% of the period recording yield above 1 tonne ha-1. Increase production area did not always translate into higher yield. Despite low yield, sorghum utilization was 16 000 tonnes compared to 11 000 tonnes produced, thus necessitating an import of 5 000 tonnes, thus there was higher sorghum self-sufficiency level. Promotion of sorghum production and its use should be revisited to address food security and export value.
Trend Analysis of Maize Production in Lesotho and Its Distribution among the Ecological Zones (Published)
Maize is the major staple crop in Lesotho as evidenced by production and consumption levels. Speculation showed that maize production and area planted is declining dramatically and no appropriate analytical tools have been employed to verify this. The objectives of this study were; (1) to determine the trend of maize production, area planted and yield using time-series data (2) to determine distribution of maize by production and area among ecological zones. Time series data from 1961 to 2013 on maize production, area and yield were collected from FAOSTAT (2015). Data on ecological zones were obtained from Bureau of Statistics in Lesotho (2014). Genstat software was employed for trend analysis using time series function and ANOVA was to establish differences in maize production among ecological zones of Lesotho. The results revealed that trendline for maize production had declined from 107,000 in 1961 to 94,000 tons in 2013. Production and area curves appeared cyclical. Trendline for area planted maize for 54 years was constant from 1961 to 2013. Yield trendline was constant at 860 kg ha-1. Maize production in the lowland was the highest, followed by Foothills, Mountain and Orange river zone. There is a potential for Lesotho to increase maize production by mainly increasing yield.