Browsing by Author "Tumbo, S. D."

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A decision support system for enhancing crop productivity of smallholder farmers in semi-arid agricultureA decision support system for enhancing crop productivity of smallholder farmers in semi-arid agriculture
Churi, A. J.; Mlozi, M. R. S; Tumbo, S. D.; Casmir, R.; Mahoo, M. R. S
A decision support system for enhancing crop productivity of smallholder farmers in semi-arid agricultureA decision support system for enhancing crop productivity of smallholder farmers in semi-arid agriculture
(2013) Churi, A. J.; Mlozi, M. R. S; Tumbo, S. D.; Casmir, R.; Mahoo, M. R. S
This study aimed at investigative decision support systems for assisting strategic and tactical decision making of smallholder farmers to reduce climate risks and increase crop productivity of semi-arid areas. Specifically, the study assessed farm-level decisions used by the farmers for reducing climate risks; examined information communication and knowledge sharing strategies for enhancing decision making and designed a system for assisting the farmers in selecting appropriate options for improving crop productivity. Development of DSS was governed by design science where prototyping approach was used to allow complete participation of end-users. The proposed architecture allows difference agricultural actors participate in communicating agricultural information and sharing of knowledge with smallholder farmers. The DSS was implemented and assessed by farmers as a useful tool for accessing information and advisories in agricultural systems. More research is recommended to enable simple and affordable mobile phones be used by farmers to access wealth of agricultural knowledge and policies from research centres and government resources.
A gendered analysis of perception and vulnerability to climate change among smallholder farmers: the case of Same district, Tanzania
Mnimbo, T. S.; Mbwambo, J.; Kahimba, F. C.; Tumbo, S. D.
A gendered analysis of perception and vulnerability to climate change among smallholder farmers: the case of Same district, Tanzania
(2015-02-16) Mnimbo, T. S.; Mbwambo, J.; Kahimba, F. C.; Tumbo, S. D.
Climate change affects women and men differently. However, there are few location-specific studies that can support interventions or policy development that can tackle this issue. To help build that body of knowledge, this article looks at gender-differentiated vulnerability among smallholder farmers in one sub-Saharan African country: Tanzania. Data were collected through household questionnaires, key informant interviews, and focus group discussions in Same District, northern Tanzania. Results revealed notable inequalities distributed across genders. Women bear the biggest burden from climate change impacts. For example, women shoulder 63% of productive tasks, such as ploughing and crop sowing, compared to 28% by men. On the other hand, resource ownership and expenditure are male dominated. The results highlight the need for governments and NGOs to address gender disparities in policies designed to strengthen the capacity of households to cope with vulnerability to climate change impacts.
Accuracy of Giovanni and Marksim software packages for generating daily rainfall data in selected bimodal climatic areas in Tanzania
(Tanzania Journal of Agricultural Sciences) Kahimba, F. C.; Tumbo, S. D.; Mpeta, E.; Yonah, I. B.; Timiza, W.; Mbungu, W.
Accuracy of Giovanni and Marksim software packages for generating daily rainfall data in selected bimodal climatic areas in Tanzania
(Tanzania Journal of Agricultural Sciences, 2014) Kahimba, F. C.; Tumbo, S. D.; Mpeta, E.; Yonah, I. B.; Timiza, W.; Mbungu, W.
Agricultural adaptation to climate change requires accurate, unbiased, and reliable climate data. Availability of observed climatic data is limited because of inadequate weather stations. Rainfall simulation models are important tools for generating rainfall data in areas with limited or no observed data. Various weather generators have been developed that can produce time series of climate data. Verification of the applicability of the generated data is essential in order to determine their accuracy and reliability for use in areas different from those that were used during models development. Marksim and Giovanni weather generators were compared against 10 years of observed data (1998-2007) for their performance in simulating rainfall in four stations within the northern bimodal areas of Tanzania. The observed and generated data were analyzed using climatic dialog of the INSTAT program. Results indicated that during the long rain season (masika) Giovanni predicted well the rainfall amounts, rainy days, and maximum dry spells compared to Marksim model. The Marksim model estimated seasonal lengths much better than the Giovanni model during masika. During short rain season (vuli), Giovanni was much better than Marksim. All the two software packages had better predictions during masika compared to vuli. The Giovanni model estimated probabilities of occurrence of rainfall much better (RMSE = 0.23, MAE = 0.18, and d =0.75) than Marksim (RMSE = 0.28, MAE = 0.23, and d = 0.63). The Marksim model over-predicted the probabilities of occurrence of dry spells greater than seven days (MBE = 0.17) compared to the Giovanni model (MBE = 0.01). In general the Giovanni model was more accurate than the Marksim model in most of the observed weather variables. The web based Giovanni model is better suited to the northern bimodal areas of Tanzania. The Marksim model produced more accurate climatic data when the long-term average climate data are used as input variables. This study recommends the use of rainfall data generated using Giovanni software over Marksim, for areas receiving bimodal rainfall regimes similar to the northern bimodal areas of Tanzania.
Adoption and scaling-up of conservation agriculture in Tanzania: Case of Arusha and Dodoma regions
(Scientific Research) Kahimba, F. C.; Mutabazi, K. D.; Tumbo, S. D.; Masuki, K. F.; Mbungu, W. B.
Adoption and scaling-up of conservation agriculture in Tanzania: Case of Arusha and Dodoma regions
(Scientific Research, 2014-02-21) Kahimba, F. C.; Mutabazi, K. D.; Tumbo, S. D.; Masuki, K. F.; Mbungu, W. B.
A study was conducted to assess the adoption and scaling-up of Conservation Agriculture in Arumeru district, Arusha region, northern Tanzania and Chamwino and Dodoma Urban districts in Dodoma region, Central Tanzania. The study employed structured questionnaire survey and key informant interviews as the main data collection methods. Data analysis was done descriptively to determine factors that influence the adoption. Results showed that farmers in Arusha have highly adopted terraces, minimum tillage and cover cropping whereas their counterparts in Dodoma have highly adopted large planting pits, minimum tillage, and rippers. The intensity of adoption in Arusha is higher for the wealthy compared to the poor while in Dodoma the wealth status was not a factor that influenced adoption of the Conservation Agriculture (CA) technologies. The process of technology adoption should include the use of various participatory methods including farmer field schools, experimental plots, farmer exchange visits, and training of trainers among others. Use of farmer groups, incentives, and support instruments such as Savings and Credit Co-operative Society (SACCOS) or warehouse receipts systems are also important to ensure that farmers realize some acceptable profits from their efforts. Involvement of various stakeholders is also very important including local governments and agricultural change agents at national, regional, district, ward and village levels. Hence, the intention to promote CA technologies should not only look at the economic importance, but also its socio-economic importance to the local people in the area. Their desire to adopt and out-scale a technology should be among the most important investment factors that the government and development partners should consider.
Application of self-organizing-maps technique in downscaling GCMs climate change projections for Same, Tanzania
Tumbo, S. D.; Mpeta, E.; Mbillinyi, B. P.; Kahimba, F. C.; Mahoo, H. F.; Tadross, M.
Application of self-organizing-maps technique in downscaling GCMs climate change projections for Same, Tanzania
(2010) Tumbo, S. D.; Mpeta, E.; Mbillinyi, B. P.; Kahimba, F. C.; Mahoo, H. F.; Tadross, M.
High resolution surface climate variables are required for end-users in climate change impact studies; however, information provided by Global Climate Models (GCMs) has a coarser resolution. Downscaling techniques such as that developed at the University of Cape Town, which is based on Self-Organizing Maps (SOMs) technique, can be used to downscale the coarse-scale GCM climate change projections into finer spatial resolutions; but that must be combined with verification. The SOM downscaling technique was employed to project rainfall and temperature changes for 2046-2065 and 2080-2100 periods for Same, Tanzania. This model was initially verified using downscaled NCEP reanalysis and observed climate data set between 1979 and 2004, and between NCEP reanalysis and GCM controls (1979 - 2000). After verification, the model was then used to downscale climate change projections of four GCMs for 2046-2065 (future-A) and 2080-2100 (future-B) periods. These projections were then used to compute changes in the climate variables by comparing future-A and B to the control period (1961-2000). Verification results indicated that the NCEP downscaled climate data compared well with the observed data. Also, comparison between NCEP downscaled and GCM downscaled showed that all the four GCM models (CGCM, CNRM, IPSL, and ECHAM) compared well with the NCEP downscaled temperature and rainfall data. Future projections (2046-2065) indicated 56 mm and 42 mm increase in seasonal total rainfall amounts for March-April-May (MAM) and October-November-December (OND) (23% and 26% increase), respectively; and a temperature increase of about 2°C for both seasons. Furthermore, it was found that during MAM there will be a decrease in dry spells by 2 days, and an increase in seasonal length by 8 days, while for OND, there will be also 2 days decrease in dry spells, and 40 days increase in the seasonal length. The results for future-B shows a 4°C rise in temperature, and 46.5% and 35.8% increase in rainfall for MAM and OND, respectively. The results imply a better climatic future for the area because of the increase in the amount of rainfall and decrease in dry spells. However, it is suggested that further investigations are required to see if the projected changes will have real positive effects in agricultural production and also identify better agronomic practices that will take advantage of the opportunities.
Characterization of sounds in maize produced by internally feeding insects: Investigations to develop inexpensive devices for detection of prostephanus truncatus (Coleoptera: Bostrichidae) and sitophilus zeamais (Coleoptera: Curculionidae) in small-scale storage facilities in Sub-Saharan Africa
(Florida Entomological Society) Kiobia, D. O.; Tumbo, S. D.; Cantillo, J.; Rohde, B. B.; Mallikarjunan, P. K.; Mankin, R. W.
Characterization of sounds in maize produced by internally feeding insects: Investigations to develop inexpensive devices for detection of prostephanus truncatus (Coleoptera: Bostrichidae) and sitophilus zeamais (Coleoptera: Curculionidae) in small-scale storage facilities in Sub-Saharan Africa
(Florida Entomological Society, 2015) Kiobia, D. O.; Tumbo, S. D.; Cantillo, J.; Rohde, B. B.; Mallikarjunan, P. K.; Mankin, R. W.
Infestations by Prostephanus truncatus Horn (Coleoptera: Bostrichidae) and Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae) are prevalent in small-scale Zea mays L. storage facilities in Tanzania and other regions of sub-Saharan Africa. It is especially difficult to detect these species’ larvae, which feed unseen inside the grain kernels. An electronic device that acoustically detects and reliably indicates the presence of such larvae could assist pest managers in maintaining the quality of the stored maize. A study was conducted in a sound- and vibration-controlled environment to estimate the amplitudes and spectral ranges of signals that an inexpensive electronic system would encounter while detecting insects in maize storage facilities. Larva-infested wheat kernels from a laboratory colony of Sitophilus oryzae (L.), a species similar in size and behavior to S. zeamais, were placed in a pouch and inserted near the side or the bottom of a bag of maize. An acoustic probe was inserted into the bag, and recordings were made at multiple positions, 5–35 cm from the pouch. Numerous sounds of 4 different types were detected over a range of frequencies extending to 7 kHz, well within the signal-processing capabilities of currently available low-cost microcontroller platforms. Larval sound impulses were detected frequently within 25 cm from the pouch, but not at 35 cm. However, adjustable-length probes could be used to reach within 30 cm of all maize kernels in the types of containers commonly used in regional storage facilities. Thus, there is considerable potential to develop an inexpensive sensor/ microcontroller system useful for managing stored product insect pests in sub-Saharan Africa.
Combining ability and heterosis of selected grain and forage dual purpose sorghum genotypes
(Canadian Center of Science and Education) Chikuta, Sally; Odong, Thomas; Kabi, Fred; Rubaihayo, Patrick; BomBom, A.; Okori, P.; Gibson, P.; Rubaihayo, P.; Kiryowa, M.; Ddamulira, G.; Karuma, A. N.; Mtakwa, P. W.; Amuri, N.; Gachene, C. K. K.; Gicheru, Patrick; Mhike, X.; Tesfahun, Kassie Girma; Magorokosho, C.; Chikobvu, Shamiso; Msongaleli, B.; Rwehumbiza, F. B. R.; Tumbo, S. D.; Kihupi, N.
Determinants of farm-level adoption of water systems innovations in dryland areas: The case of Makanya watershed in Pangani river basin, Tanzania
Masuki, K.F. G.; Mutabazi, K. D; Tumbo, S. D.; Rwehumbiza, F. B.; Mattee, A. Z.; Hatibu, N.
Determination of suitability levels for important factors for identification of potential sites for rainwater harvesting
Tumbo, S. D.; Mbillinyi, B. P.; Mahoo, H. F.; Mkiramwinyi, F. O.
Determination of suitability levels for important factors for identification of potential sites for rainwater harvesting
(2016) Tumbo, S. D.; Mbillinyi, B. P.; Mahoo, H. F.; Mkiramwinyi, F. O.
Indigenous and scientific knowledge for locating potential sites for water harvesting technologies do exists, however, a simple and integrated tool to assist farmers’ support agencies, is missing. A geographic information system (GIS)-based decision support system (DSS) can be a valuable tool for such a task. However, pre-requisite for such DSS are the factors and their suitability levels, which are not well developed. This paper focused on development of suitability levels for most important factors/parameters for identification of such sites, which are soil texture, soil depth, drainage, topography and land use or cover. Specific suitability levels were obtained using both the analysis of existing RWH technology at Makanya river catchment and through literature review. Results of field survey together with literature review showed that suitability levels of factors differ with different RWH technologies. For example, suitable levels/areas for water reservoirs (ndiva) are steep slopes (>30o) with clay soils whereas suitable sites for stone terraces are moderately steep slopes (18o – 30o) with sandy loam soils. It was also found that most RWH technologies are located at a distance between 0 and 125m from cropland.
Enhancing response farming for strategic and tactical management of risks of seasonal rainfall variability
Admassu, H.; Mahoo, H. F.; Rwehumbiza, F. B. R.; Tumbo, S. D.; Mogaka, H.
Evaluation of a variable rate controller for aldicarb application around buffer zones in citrus groves
Tumbo, S. D.; Miller, W. M.; Salyani, M.; Sweeb, R.; Buchanon, S.
GIS-based decision support system for identifying potential sites for rainwater harvesting
(Physics and Chemistry of the Earth) Mbilinyi, B. P.; Tumbo, S. D.; Mahoo, H. F.; Mkiramwinyi, F. O.
GIS-based decision support system for identifying potential sites for rainwater harvesting
(Physics and Chemistry of the Earth, 2007) Mbilinyi, B. P.; Tumbo, S. D.; Mahoo, H. F.; Mkiramwinyi, F. O.
Identification of potential sites for rainwater harvesting (RWH) is an important step towards maximizing water availability and land productivity in the semi-arid areas. However, selection of appropriate sites for different RWH technologies on a large scale presents a great challenge, since the necessary biophysical data and infrastructure are often lacking. This paper presents a geographic information system (GIS)-based decision support system (DSS) that uses remote sensing (RS), limited field survey to identify potential sites for RWH technologies. The input into the DSS include maps of rainfall, slope, soil texture, soil depth, drainage and land use/cover and the outputs are maps showing potential sites of water storage systems (ndiva), stone terraces, bench terraces and borders. The Model Builder in the Arc View GIS was used as a platform for the DSS. Two sites in the Makanya watershed, in Kilimanjaro Region, Tanzania, were used for testing and validation of the DSS. The results reflect specific suitability levels of parameters and weight of factors; for example, near streams (drainage) with slope ranges from moderately steep to steep (10 –30 ) are potential sites for ndiva locations whereas moderately undulating to steep slopes (5 –30 ) with unstable soils are potential sites for stone terraces. Moderately undulating slopes (5 –10 ) with clay, silt clay and sandy clay soils are potential sites for bench terrace and gently undulating slopes (2 –5 ) with clay, silt clay and sandy clay soils are potential sites for borders. The results from testing and validation of the developed DSS indicated that the tool can be used reliably to predict potential sites for RWH technologies in semi-arid areas. Most of predicted RWH technologies during testing were found within very highly and highly suitable locations (41.4% and 40%, respectively) also in validation 36.9% of RWH technologies were found within the moderately suitable followed by very highly suitable and highly suitable both with 23.6%. Despite the good results, it is recommended that more work be carried out to refine the model and to include other pertinent ancillary data like socio-economic factors to increase its usefulness.