Browsing by Author "Kihupi, N."

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Evaluation of the effectiveness of commonly used irrigation scheduling approaches on land and water productivity
(2008-06) Kihupi, N.; Tarimo, A. K. P. R.; Bjerkholt, J. T.; Mkoga, Z. J.; Mbozil, A. F
A field experiment was conducted to study the impacts of different irrigation schedules on land and water productivity of a bean (Phaseolus vulgaris L.) crop. Three irrigation scheduling methods were evaluated using a randomised complete block design., one based on historical climatic data (water balance), a second one based on neutron probe soil moisture measurements and the third one based on normal practices of farmers in the area (farmer-managed schedule). Irrigation water applications and crop water use were monitored throughout the growing season. The mean total water delivery under farmer- managed plots was 735mm which is more than adequate for a bean crop whose water requirement for maximum production varies between 300 and 500mm depending on climate. There were significant differences (P<0.05) in irrigation water productivity (IWP) and field water application efficiency (FAE) among treatments. The IWP and FAE of farmer-managed schedule were significantly lower than the other treatments, but the F AE of the control plot and climatic data plot did not differ significantly (P < 0.05). On the other hand, there was no significant difference (P<0.05) in physiological water use efficiency (PWUE) among treatments. Land productivity was significantly higher (P < 0.05) in the climatic data based schedule than the other methods. It would thus appear that the water budget technique based on average climatic data is a suitable irrigation scheduling criterion which saved irrigation water while achieving maximum yield, optimum water productivity and field application efficiency. Low field application efficiencies under farmers' management practices indicate a need for improvement in water management strategies of individual farmers. This would go a long way to improving both water and land productivities.
Impacts of climate variability and change on rainfed sorghum and maize: Implications for food security policy in Tanzania
(Canadian Center of Science and Education, 2015-04-15) Msongaleli, B. M.; Rwehumbiza, F.; Tumbo, S. D.; Kihupi, N.
Concern about food security has increased because of a changing climate, which poses a great threat to food crop productivity. Climate change projections from the Coupled Model Inter-comparison Project phase 5 (CMIP5) and crop models were used to investigate the impacts of climate change on rain-fed cereal production. Calibrated and evaluated crop models simulated maize and sorghum yields over time periods and scenarios across central zone Tanzania with and without adaptation. Simulation outputs without adaptation showed predominant decrease and increase in maize and sorghum yields, respectively. The results showed that maize yields were predicted to decline between 1% and 25% across periods, representative concentration pathways (RCPs) and global circulation models (GCMs). However, sorghum yields were on average predicted to increase between 5% and 21%. Overall when adaptation is incorporated toward mid-century, yields are projected to increase for both crops. The yield projections variation between cereal crops highlights the importance of location and crop specific climate change impact assessments. Despite the uncertainties in predicting the impacts of climate change on rainfed crops, especially on cereals (maize and sorghum) which are important staple food crops in semi-arid Tanzania, the findings of this study enable policy makers to develop plans aimed at sustainable food security. In conclusion, the results demonstrate the presumption that sorghum productivity stands a better chance than maize under prospects of negative impacts from climate change in central zone Tanzania.
Investigation of sorghum yield response to variable and changing climatic conditions in semi-arid central Tanzania: Evaluating crop simulation model applications
(2013) Msongaleli, B.; Rwehumbiza, F. B. R.; Tumbo, S. D.; Kihupi, N.
Combination of global circulation models (GCMs), local-scale climate variability and crop simulation models were used to investigate rain-fed sorghum yield response under current and future climate in central Tanzania. Decision Support System for Agrotechnology Transfer (DSSAT) v.4.5 and Agricultural Production Systems Simulator (APSIM) v 7.4 were calibrated and evaluated to simulate sorghum (Sorghum Bicolor L. Moench) var. Tegemeo in 2050s compared to baseline. Simulated median yields from both crop models for the baseline (1980-2010) agree with the trend of yield over the years realistically. The models predicted yields of sorghum in the range from 818 to 930 kg ha-1 which are close to the current national average of 1000 kg ha-1. Simulations by both models using downscaled weather data from two GCMs (CCSM4 and CSIRO-MK3) under the Fifth Coupled Model Intercomparison Project (CMIP5) and Representative Concentration Pathway (RCP 4.5) by mid-century show a general increase in median sorghum yields. Median sorghum yields will increase by 1.1% - 7.0% under CCSM4 and by 4.0% - 12.5% under CSIRO-MK3. Simulations for both current and future periods were run based on the present technology, current varieties and current agronomy packages. This examination of impacts of climate change revealed that increase in sorghum yield will occur despite further projected declines or increase in rainfall and rise in temperature. Modifying management practices through adjustment of sowing dates and the choice of cultivars between improved and local are seemingly feasible options under future climate scenarios depending on the GCM and the direction of the management practice. Our simulation results show that current improved sorghum cultivars would be resilient to projected changes in climate by 2050s, hence bolstering the evidence of heat and drought tolerance in sorghum crop, thus justifying its precedence as an adaptation crop under climate change. We conclude that despite the uncertainty in projected climate scenarios, crop simulation models are useful tools for assessing possible impacts of climate change and management practices on sorghum.
Lepus conference soils, land use and plague Lushoto, Tanzania
(Sokoine University of Agriculture, 2013-08) Hieronimo, P.; Meliyo, J.; Gulinck, H.; Kimaro, D.; Msanya, B.; Mulungu, L.; Kihupi, N.; Deckers, S.; Leirs, H.; Leirs, H.
This excursion guide leads you to the case study area of the LEPUS project. The study area is located in a 200 km2 section of the Western Usambara Mountains and within the Lushoto district (map 1 ). I t is centred over the region in which during the period 1 980 - 2004 many bubonic plague cases were registered. Within the case area, there is west-east gradient from high to low plague incidence.
Lepus conference soils, land use and plague Lushoto, Tanzania
(2013) Hieronimo, P.; Meliyo, J.; Gulinck, H.; Kimaro, D.; Msanya, B. M.; Mulungu, L.; Kihupi, N.; Deckers, S.; Leirs, H.
Validation of crop weather models for crop assessment arid yield prediction under Tanzania conditions
(2000) Kihupi, N.; Dihenga, B.O.; Ntella, P. M.
Information gatheringfor early warning and crop assessment in Tanzania is based on physical inspection of standing crop in sample jields. This process is subject to human error, inadequate and is also time consuming. Recent developments in computer simulation have paved the way for more efficient methods of analysing datafor purposes of early warning and crop assessment. Two such sch~mes based on soil water balance simulation, viz. IRSIS and CRPSM models were used in this study fo see how closeZv they could predict grain yieldsfor selected stations in Tanzania. Inputfor the models comprised of weather, crop and soil data collected from jive selected stations. Simulation results show that IRSIS model tends to over predict grain yields of maize, sorghum and wheat, a fact that could be attributed to the inadequacy of the model to accurately account for rainfall excess. On the other hand, the CRPSA1 model simulated results were not significantZv different (P>O. 05) from the actual grain yields ojmaize, sorghum,. wheat and beans. Although the agreement between actual and simulated yield data was good, it was observed that mean valuesfor predicted grain yields were consistently lower thanfor actual grain yields. This could be attributed to the use of approximate rather than location specific input parameters required by the CRPSM model. Locally calibrated input parameters in the CRPSM model could filrther improve the accuracy of the model and hence its ability to predict grain yields.