Your search found 3 records
1 Haileselassie, H.; Araya, A.; Habtu, S.; Meles, K. G.; Gebru, G.; Kisekka, I.; Girma, A.; Hadgu, K. M.; Foster, A. J. 2016. Exploring optimal farm resources management strategy for Quncho-teff (Eragrostis tef (Zucc.) Trotter) using AquaCrop model. Agricultural Water Management, 178:148-158. [doi: https://doi.org/10.1016/j.agwat.2016.09.002]
(Location: IWMI HQ Call no: e-copy only Record No: H047852)
(1.52 MB)
Teff is a major staple food crop in Ethiopia. Moisture and soil fertility are the two major factors limiting teff yield. Studies were conducted across three sites in Ethiopa [Mekelle (MK) in 2012 and 2016, Ilala (IL) in 2012 and Debrezeit (DZ) in 2009 and 2010]. The objectives of these studies were (1) to assess the response of Quncho-teff to different fertilizer and irrigation levels; 2) to quantify irrigation water productivity (IWP), and (3) to collect data to calibrate and validate AquaCrop model for simulating yield and evaluate optimal irrigation and sowing date strategy for Quncho-teff at different locations in Ethiopia. The different fertilizer levels were: 1) 64 kg N and 46 kg P/ha (N2P2); 2); 32 kg N and 23 kg P/ha (N1P1); 3) 0 kg N and 0 kg P/ha (N0P0) and 4) 52 kg N and 46 kg P/ha (N3P3). The four irrigation treatments were: zero (rainfed), two, four and full irrigation applications. Findings showed that full irrigation in combination with high fertilizer (N2P2) could give better yield. However, during abnormal rainfall, spreading the available fertilizer at a rate of 32 kg N and 23 kg P/ha may be preferable to applying 64 kg N and 46 kg P/ha. This study also indicated that the regional fertilizer recommendations for teff need to be revised taking in to account the soil characteristics, climate and irrigation water availability. The AquaCrop model was able to simulate the observed canopy cover, soil water, biomass and yield of teff satisfactorily. Canopy cover was simulated with normalized root mean square error (NRMSE), index of agreement (I) and R2 of 7%, 0.5 and 0.8, respectively. Soil moisture during the season was simulated with NRMSE of 11.4–15.7%, I of 0.99 and R2 of 0.85–0.9. Simulated final aboveground biomass values were in close agreement with the measured (NRMSE, 7.8%, I, 0.89 and R2, 0.66). There was also good agreement between simulated and measured grain yield with NRMSE, I and R2 values of 10.9%, 0.93, 0.80, respectively. Scenario analysis indicated that early sowing was the best option to maximize teff yield with the least amount of irrigation. Scenario analysis also showed that one irrigation during flowering stage could substantially improve irrigation water productivity (IWP) of teff and minimize the yield loses which could occur due to shifting of sowing date from early to normal. Two irrigation applications also substantially improved the yield and IWP of late sown teff. However, to get high yield, a late sown teff should receive at least four irrigation applications during the mid-growth stage of the crop. These results suggest that AquaCrop model can be used to identify optimal farm resource management strategies for teff production.
2 Manivanh, L.; Pierret, A.; Rattanavong, S.; Kounnavongsa, O.; Buisson, Y.; Elliott, I; Maeght, J. -L.; Xayyathip, K.; Silisouk, J.; Vongsouvath, M.; Phetsouvanh, R.; Newton, P. N.; Lacombe, Guillaume; Ribolzi, O.; Rochelle-Newall, E.; Dance, D. A. B. 2017. Burkholderia pseudomallei in a lowland rice paddy: seasonal changes and influence of soil depth and physico-chemical properties. Scientific Reports, 7:1-11. [doi: https://doi.org/10.1038/s41598-017-02946-z]
(Location: IWMI HQ Call no: e-copy only Record No: H048174)
(1.85 MB)
Melioidosis, a severe infection with the environmental bacterium Burkholderia pseudomallei, is being recognised increasingly frequently. What determines its uneven distribution within endemic areas is poorly understood. We cultured soil from a rice field in Laos for B. pseudomallei at different depths on 4 occasions over a 13-month period. We also measured physical and chemical parameters in order to identify associated characteristics. Overall, 195 of 653 samples (29.7%) yielded B. pseudomallei. A higher prevalence of B. pseudomallei was found at soil depths greater than the 30 cm currently recommended for B. pseudomallei environmental sampling. B. pseudomallei was associated with a high soil water content and low total nitrogen, carbon and organic matter content. Our results suggested that a sampling grid of 25 five metre square quadrats (i.e. 25 × 25 m) should be sufficient to detect B. pseudomallei at a given location if samples are taken at a soil depth of at least 60 cm. However, culture of B. pseudomallei in environmental samples is difficult and liable to variation. Future studies should both rely on molecular approaches and address the micro-heterogeneity of soil when investigating physico-chemical associations with the presence of B. pseudomallei.
(Location: IWMI HQ Call no: e-copy only Record No: H049690)
(1.53 MB) (1.53 MB)
Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, where each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents, at field capacity and permanent wilting points, were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam, and 35% and 17% for a clay loam, respectively. The field capacity level which occurs shortly after an irrigation event was considered the upper point of soil moisture content, and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam, and clay loam soils, respectively. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field
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