Mango fruits contain substantial vitamins and dietary fibre. Vitamins vary among and within fruits depending on cultivar type and ripening stage. Conventional techniques of vitamins analysis are based on High Pressure Liquid Chromatography, which are costly and laborious. This study evaluated the potential of Fourier transform infrared-diffuse reflectance spectroscopy (FTIR-DRIFTS) technique in predicting β-carotene, α-tocopherol and l-ascorbic acid in pulps of four mango cultivar types (‘Apple’, ‘Kent’, ‘Ngowe’, and ‘Tommy Atkins’). Combination of ran dom forest (RF) and first derivative spectra developed the predictive models. Factorial ANOVA examined the interaction effect of cultivar type, site (‘Thika’, ‘Embu’ and ‘Machakos), and fruit canopy position (sun exposed/within crown) on β-carotene, α-tocopherol and l-ascorbic acid contents. RF Models gave R² = 0.97, RMSE = 2.27, RPD = 0.72 for β-carotene; R² = 0.98, RMSE = 0.26, RPD = 0.30 for α-tocopherol and R² = 0.96, RMSE = 0.51, RPD = 1.96 for l-ascorbic acid. Generally cultivar type affected vitamin C, F (3, 282) = 7.812, p < 0.05. Apple and Tommy Atkins had higher mean vitamins than Ngowe and Kent. In Machakos, within canopy fruits had higher β-carotene than sun-exposed fruits, F (5, 257) = 2.328, p = 0.043. However, interactions between fruit position, site and cultivar did not affect α-tocopherol and vitamin C. In Thika, Tommy Atkins at fully ripe stage had higher vitamin C than at intermediate maturity stage, F (2, 143) = 7.328, p = 0.01. These results show that FTIR-DRIFTS spectroscopy is a high-throughput method that can be used to predict mango fruit vitamins of in a large data set.

The present study assessed soil physical-chemical characteristics as reliable soil health indicators in six climate-smart land use types; agroforestry, community forest, cropland with soil and water conservation (SWC), crop land without SWC, grassland and control across climate-smart villages (CSVs) in Lushoto (Tanzania), Hoima (Uganda), Wote and Nyando (Kenya). Soils were sampled at three depths; 0–15 cm, 15–45 cm and 45–100 cm and then analyzed for bulk density (BD), pH, exchangeable bases (Ca, Mg, K, Na), extractable Fe, Mn, Zn, exchangeable acidity (ExAc), Electrical conductivity (EC), total carbon (TC), total nitrogen (TN) and cation exchange capacity (CEC). Land use types and sampling depths significantly affected soil properties (p < 0.05), High bulk density (BD) was measured at 45–100 cm depth in grassland (1.47 g/cm³) and crop land (1.50 g/cm³) in Kenya and Tanzania, respectively. BD in Ugandan grasslands was statistically lower (p < 0.05) than BD in other land use types at all depths. Soil pH of surface soil (0–15 cm) ranged from 6.67 ± 0.67 (agroforestry) to 6.27 ± 0.85 (grassland). Ex. bases (Ca, Mg, K and Na) and extractable Fe, Mn, Zn, ExAc, EC, TC, TN and CEC were significantly affected by land uses (p ≤ 0.05). Soil properties were significantly correlated, a positive correlation between silt % (p < 0.01) and pH, sand and Ca (p < 0.05). EC and pH, exchangeable Ca, exchangeable bases, exchangeable K and C: N ratio was observed. There was a negative correlation (p < 0.05) between pH and clay. The study has shown that improving soil properties using land use systems leads to an increase in soil nutrients.

Mangoes are fruits of nutritional importance in Kenya. The fruits vary in their sugars depending on cultivar type and ripening stage. Current methods of sugar content analysis are based on HPLC methods, which are accurate but expensive and time-consuming. We evaluated the potential of diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy as a rapid tool for quantitative prediction of fructose and glucose sugars in the pulp of Kenyan mangoes. Principal component analysis and partial least regression models were developed using the first derivative DRIFT spectra (400–4000 cm−1) to predict fructose and glucose sugars. A factorial analysis of variance compared effects of site (three locations), cultivar type (four cultivars), fruit position (inside/outside), and their interactions on fructose and glucose contents. The principal component analysis scores plot using components 1 and 2 explained 75 and 8% of the variance, respectively, with no clear grouping either by sites or cultivars. The PLS range for glucose was R 2 = 0.80, SECV = 0.55, and RPD = 11.52 and fructose R 2 = 0.70, SECV = 0.28, and RPD = 11.52. Site (F (2, 265) = 18.12, p < 0.05, η2 = 0.02), cultivar type (F (3, 256) = 4.44, p < 0.05, η2 = 0.05), and fruit position (F (1, 259) = 7.62, p < 0.05, η2 = 0.03) had a significant effect on glucose content and not on fructose content. However, interactions between these three factors were not significant, p > 0.05. In general, fruits outside the canopy had higher fructose and glucose contents than those within the canopy. DRIFTS coupled with chemometric techniques showed potential for prediction of fructose and glucose contents of mango fruits.

A novel total ensemble (TE) algorithm was developed and compared with random forest optimization (RFO), gradient boosted machines (GBM), partial least squares (PLS), Cubist and Bayesian additive regression tree (BART) algorithms to predict numerous soil health indicators in soils with diverse climate-smart land uses at different soil depths. The study investigated how land-use practices affect several soil health indicators. Good predictions using the ensemble method were obtained for total carbon (R² = 0.87; RMSE = 0.39; RPIQ = 1.36 and RPD = 1.51), total nitrogen (R² = 0.82; RMSE = 0.03; RPIQ = 2.00 and RPD = 1.60), and exchangeable bases, m3. Cu, m3. Fe, m3. B, m3. Mn, exchangeable Na, Ca (R² > 0.70). The performances of algorithms were in order of TE > Cubist > BART > PLS > GBM > RFO. Soil properties differed significantly among land uses and between soil depths. In Kenya, however, soil pH was not significant, except at depths of 45–100 cm, while the Fe levels in Tanzanian grassland were significantly high at all depths. Ugandan agroforestry had a substantially high concentration of ExCa at 0–15 cm. The total ensemble method showed better predictions as compared to other algorithms. Climate-smart land-use practices to preserve soil quality can be adopted for sustainable food production systems.

Global interest in using duckweed (Lemna minor) as a substitute for fish, livestock, and human diets has spurred research on the mass culture of the species. There is a scarcity of information on the L. minor fatty acid composition in different aquaculture settings. A comparative study was carried out to investigate the fatty acid composition of L. minor cultured in indoor plastic tanks and outdoor earthen ponds for 30 days. During the culture period, culture facilities were fertilized using livestock manure. Fatty acid characterization was done using gas chromatography method. Fifteen fatty acids: five saturated (SAFAs), five monounsaturated (MUFAS), and five polyunsaturated (PUFAs) were identified. Fatty acid compositions varied between indoor and outdoor settings. Percentage composition of L. minor PUFAs cultured outdoor (37.13) was higher than that of indoor (21.96) settings. L. minor SAFAs percentage composition was higher in the indoor culture at 41.63% while that of outdoor was 33.75%. The composition of L. minor MUFAs in indoor tanks was higher (36.32%) than in outdoor earthen ponds (29.10%). This study indicated the presence of docosahexaenoic, eicosapentaenoic, linoelaidic, and eicosanoic acids in L. minor seldom reported in past studies. Paired Students’ t‐test indicated that the means of the fatty acid composition were significantly different (p < 0.05) in both settings, with docosahexaenoic showing the highest paired mean difference.