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Nineteen tanniferous browse plants were collected from South Africa to investigate their digestibility, gas production (GP) characteristics and methane production. Fresh samples were collected, dried in forced oven, and ground and analyzed for nutrient composition. In vitro GP and in vitro organic matter digestibility (IVOMD) were determined using rumen fluid collected, strained and anaerobically prepared. A semi- automated system was used to measure GP by incubating the sample in a shaking incubator at 39°C. There was significant (p<0.05) variation in chemical composition of studied browses. Crude protein (CP) content of the species ranged from 86.9 to 305.0 g/kg dry matter (DM). The neutral detergent fiber (NDF) ranged from 292.8 to 517.5 g/kg DM while acid detergent fiber (ADF) ranged from 273.3 to 495.1 g/kg DM. The ash, ether extract, non-fibrous carbohydrate, neutral detergent insoluble nitrogen, and acid detergent insoluble nitrogen and CP were negatively correlated with methane production. Methane production was positively correlated with NDF, ADF, cellulose and hemi-cellulose. Tannin decreased GP, IVOMD, total volatile fatty acid and methane production. The observed low methanogenic potential and substantial ammonia generation of some of the browses might be potentially useful as rumen manipulating agents. However, a systematic evaluation is needed to determine optimum levels of supplementation in a mixed diet in order to attain a maximal depressing effect on enteric CH4 production with a minimal detrimental effect on rumen fermentation of poor quality roughage based diet.

Some medicinal plants have the tendency to manipulate the rumen microbial ecosystem, which in turn might reduce methane (CH4) emissions. The anti-methanogenic activities of leaf fraction of Piper betle, Aloe vera, Carica papaya, Azadirachta indica, Moringa oleifera, Tithonia diversifolia, Jatropha curcas and Moringa oleifera pods were studied at different doses. The plant materials were extracted with pure methanol and subsequently reconstituted at the rate of 25, 50, 75 and 100 mg in 1000 mL distilled water. Four mL of each plant extracts preparation was anaerobically incubated with 400 mg Eragrostis curvula hay in four replicates and the experiment was repeated five times. Plant extracts of P. betle and A. vera significantly increased total gas produced whereas other extracts recorded lesser or similar values to the control group. Leaf extracts of A. indica, C. papaya, J. curcas, M. oleifera, T. diversifolia and M. oleifera pods all significantly reduced CH4 volume at dosages of 25 and 50 mg/L due to the activities of their phytochemicals. Total volatile fatty acids and in vitro organic matter digestibility values recorded for all extracts were generally superior when compared with the control. Methane yield per unit of total gas were significantly lower in extracts of T. diversifolia, M. oleifera, A. indica, M. oleifera pods whereas it is higher in P. betle and A. vera. It can be concluded from the study that methanolic extracts of A. indica, C. papaya, J. curcas, M. oleifera, M. oleifera pods and T. diversifolia resulted in reduced CH4 production, and thus can be used potentially to manipulate rumen condition, improve feed digestibility and reduce enteric CH4 emission from ruminants. However, the in vitro results needs to be verified using in vivo studies by administering concentrated crude extracts at a rate of 25 mg or 50 mg per kg of roughage feed for small ruminants.

The use of crop modeling as a decision tool by farmers and other decision-makers in the agricultural sector to improve production efficiency has been on the increase. In this study, artificial neural network (ANN) models were used for predicting maize in the major maize producing provinces of South Africa. The maize production prediction and projection analysis were carried out using the following climate variables: precipitation (PRE), maximum temperature (TMX), minimum temperature (TMN), potential evapotranspiration (PET), soil moisture (SM) and land cultivated (Land) for maize. The analyzed datasets spanned from 1990 to 2017 and were divided into two segments with 80% used for model training and the remaining 20% for testing. The results indicated that PET, PRE, TMN, TMX, Land, and SM with two hidden neurons of vector (5,8) were the best combination to predict maize production in the Free State province, whereas the TMN, TMX, PET, PRE, SM and Land with vector (7,8) were the best combination for predicting maize in KwaZulu-Natal province. In addition, the TMN, SM and Land and TMN, TMX, SM and Land with vector (3,4) were the best combination for maize predicting in the North West and Mpumalanga provinces, respectively. The comparison between the actual and predicted maize production using the testing data indicated performance accuracy adjusted R2 of 0.75 for Free State, 0.67 for North West, 0.86 for Mpumalanga and 0.82 for KwaZulu-Natal. Furthermore, a decline in the projected maize production was observed across all the selected provinces (except the Free State province) from 2018 to 2019. Thus, the developed model can help to enhance the decision making process of the farmers and policymakers.

This paper summarizes effects of forage-legume intercropping on grain and fodder yield, land equivalent ratio, residual soil fertility, disease and insect pest reduction in mixed crop-livestock systems in Africa. In particular, it discusses the potential benefit of forage-legume intercropping in improving productivity, resource use efficiency and resilience of the system under climate change, which enhances adaptation to climate change and possibly provides the co-benefit of reducing greenhouse gases in sub-Saharan Africa. Research undertaken in Africa demonstrates that intercropping forage legumes with cereals improves overall yield and soil fertility, and reduces the risk of crop failure owing to rainfall variability, diseases, weeds and pests. When the forage from intercropped legumes is provided to animals it improves the digestibility of poor-quality feed, animal performance and efficiency of roughage feed utilization by ruminants. Additional role that legumes may play include lowering erosion and the loss of organic matter, reducing nitrogen leaching and carbon losses, and promoting carbon sequestration. Nitrogen fixed by legumes is safer than nitrogen from inorganic fertilizers. Despite the many benefits of forage legume intercropping the current adoption rate in sub-Saharan Africa is very low. Future research aimed at selection of compatible varieties, appropriate plant geometry and temporal arrangement of the various intercrops under different locations and management scenarios, as well as minimizing the confounding effects of water, soil, light, microclimate, and seeds could enhance adoption of the technology in Africa.