Climate trends, risks and coping strategies in smallholder farming systems in Uganda

Mubiru, Drake N.; Maren, Radeny; Kyazze, Florence Birungi; Zziwa, Ahamada; Lwasa, James; Kinyangi, James; Mungai, Catherine

doi:10.1016/j.crm.2018.08.004

Cited by 91 publications

(72 citation statements)

References 10 publications

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“…However, declines in the amounts of rainfall and the number of rainy days in these months were reported by Mubiru et al. (). The mean annual temperature was 25°C, with a range of 15–27°C (Kimbugwe, ), and an increasing trend of about 0.5°C per year (Mubiru et al., ).…”

Section: Methodsmentioning

confidence: 74%

“…(). The mean annual temperature was 25°C, with a range of 15–27°C (Kimbugwe, ), and an increasing trend of about 0.5°C per year (Mubiru et al., ). On the other hand, Hoima district that is located in the Albertine Rift valley, central western Uganda, receives a mean annual rainfall of 1,270 mm with a range of 800–1,400 mm, during March to May and August to November.…”

Section: Methodsmentioning

confidence: 99%

“…On the other hand, Hoima district that is located in the Albertine Rift valley, central western Uganda, receives a mean annual rainfall of 1,270 mm with a range of 800–1,400 mm, during March to May and August to November. The district experiences increasing amounts of rains in January, March and August with declining trends in certain months (Mubiru et al., ). In these two districts, the studies were conducted in two villages per subcounty except in Kyabigambire subcounty in Hoima district where the experiments were in three villages (Table ).…”

Section: Methodsmentioning

confidence: 99%

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Participatory farmers’ selection of common bean varieties (Phaseolus vulgaris L.) under different production constraints

et al. 2018

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On-farm evaluation of 15 common bean varieties was undertaken with nine farmer groups under two fertilizer applications levels in four subcounties of Hoima and Rakai districts for two seasons to select farmers' desired and undesired varieties.Farmers' votes for acceptance and rejection of varieties at podding stage were converted to a preference index, and analysis of variance was conducted to examine differences in farmers' preference indices among subcounties and combined across subcounties, seasons, management and gender. Management had no-significant influence on the way farmers selected varieties in the subcounties. Choice of varieties varied significantly (p ≤ .001) between seasons and gender in the different subcounties. Variety Masindi Yellow Long and Farmers' seed (Kaduli), and the introduced KATB1 were accepted by farmers due to their medium seed size, desired seed colour and potential of varietal adaptability to their farm conditions. Varieties NABE2, ROBA1 and RWR719 were deselected due to possession of traits less desired in the market. These results demonstrate the need for breeding programmes to involve diverse stakeholders in capturing the diverse traits preferences in varietal development process. K E Y W O R D Sfarmer evaluation, food security, grain legumes, participatory research

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Section: Methodsmentioning

confidence: 74%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Participatory farmers’ selection of common bean varieties (Phaseolus vulgaris L.) under different production constraints

et al. 2018

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“…Water supply schemes in rural areas typically have less technical, financial, and managerial capacity [65]. Therefore, in schemes that will experience the effects of rainfall variability, broad-scale adaptation strategies are needed to address a threat [76,77]. However, for this purpose, further assessments are vital which can also analyze the potential influence of other climate variables (e.g., temperature), additional variables, such as population growth, the standard of water supply infrastructure, and management practices [23].…”

Section: Discussionmentioning

confidence: 99%

Seasonal and Annual Rainfall Variability and Their Impact on Rural Water Supply Services in the Wami River Basin, Tanzania

Twisa

Buchroithner

2019

Water

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In some parts of Africa, rainfall variability has resulted in widespread droughts and floods, thus posing a substantial challenge to water availability in rural areas, especially drinking water. Therefore, due to increasing water demands, increases in the population, and economic development, water supply systems are under constant stress. One of the critical uncertainties surrounding the effects of rainfall variability in Africa is the significant impact that it imposes on rural water supply services. The present study analyzes the trends in annual and seasonal rainfall time series in the Wami River Basin to see if there have been any significant changes in the patterns during the period 1983–2017 and how they affect the access to water supply services in rural areas. The study analyzes the trends of rainfall series of three stations using simple regression, Mann–Kendal Test and Sen’s Slope Estimator. The water point mapping datasets were analyzed considering seasonal variation. The analysis showed a statistically significant positive trend in annual rainfall at Kongwa and March–April–May (MAM) seasonal rainfall at Dakawa. The maximum increase in annual rainfall occurred at Kongwa (5.3 mm year−1) and for MAM seasonal data at Dakawa (4.1 mm year−1). Water points were found to be significantly affected by seasonal changes, both in terms of availability and quality of water. There also exists a strong relationship between rural water services and seasons.

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“…The author describes low-level farmers in east Africa face a wide extent of agrarian age threats. Natural change and variability present new risks and vulnerabilities [22]. The author describes Environmental change is set to be especially problematic in poor agrarian networks.…”

Section: Literature Foundationmentioning

confidence: 99%

Novel Methods for Crop Prediction based on Influencing Parameters in Indian Regions using Data Mining

Joseph,

Manohar

2020

IJEAT

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Agriculture plays a crucial role for the production of food in Indian regions. Indian regions mainly produces crops like rice, wheat, maize and many other types of crop. There are several factors required for the productivity of any harvest, but we know that soil, climate, pesticides, Fertilizers and ground water is most influencing essential factor for the productivity of any harvest. Let us consider soil which is the key element as it provides nutrients for proper development and growth of crops. Secondly, climate is also having major role in agriculture as crop growth depends on rainfall, humidity, temperature etc. Thirdly, Pesticides is widely used to control pest and prevents the damage of crops. Fourthly, Fertilizers can improve the quality of crops. Finally, ground water which will enrich nutrients in soil. The current preparation centers around different information mining procedures utilized in various regions of India and anticipate future harvest along with reasonable information mining procedure saw during the period(1920-2019).The parameters considered for the examination were soil, atmosphere, water thickness, pesticides and composts and Crop informational collection. The Classification calculations utilized in preparation were Adaptive boosting classification, Excess tree classification, neural based classification, Multiple Process classification, Decision making classification, K-closest neighbors, Bayesian theory classification, decision Forest classification, support group machine, and Randomized Gradient Classification. By using the techniques mentioned above we can improve the harvest prediction using information mining techniques which in turn help the farmers to take better decisions in future and it can be used in other technologies like image analyzing etc. The Experimental results show predicted crop, suitable algorithm and algorithm accuracy in that particular state of India respectively.

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Climate trends, risks and coping strategies in smallholder farming systems in Uganda

Cited by 91 publications

References 10 publications

Participatory farmers’ selection of common bean varieties (Phaseolus vulgaris L.) under different production constraints

Participatory farmers’ selection of common bean varieties (Phaseolus vulgaris L.) under different production constraints

Seasonal and Annual Rainfall Variability and Their Impact on Rural Water Supply Services in the Wami River Basin, Tanzania

Novel Methods for Crop Prediction based on Influencing Parameters in Indian Regions using Data Mining

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