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Matin M.A.,University of South Australia | Matin M.A.,International Maize and Wheat Improvement Center Bangladesh | Fielke J.M.,University of South Australia | Desbiolles J.M.A.,University of South Australia
Biosystems Engineering | Year: 2015

Strip-tillage research in developing countries usually relies on commonly used rotary blades designed for conventional full disturbance soil tillage. With the aim of optimising the blade geometry and operational settings, this study investigated the effect of three blade geometries (conventional, half-width and straight) at four rotary speeds (125, 250, 375, and 500rpm) on torque, power and energy characteristics. A single row rotary tiller was fitted with the blades set at a cutting width of 50mm and depth of 50mm and tested in a soil bin (sandy loam soil). Analyses of high speed video images and corresponding blade motion revealed that the peak torque occurred at a higher blade penetration depth as the speed increased indicating transformation of the peak torque requirement from due to initial soil failure at a low speed to final soil cutting and throwing at a high speed. The straight blade design required the least torque, average power, peak power, specific energy and effective specific energy at 375-500rpm which targeted for a small bite length for a fine soil tilth. The straight blade saved 20-25% power when compared with the conventional and half-width blades at 500rpm. Although, the average power, peak powerand specific energy requirements increased with the rotary speed for all the blades with a steep rise over 375rpm, the effective specific energy requirement remained almost unchanged for the straight blade indicating its high effectiveness for strip-tillage operations. © 2014 IAgrE.


Gathala M.K.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,University of Melbourne | Islam M.S.,International Maize and Wheat Improvement Center Bangladesh | And 12 more authors.
Field Crops Research | Year: 2016

Responding to increasing demand from poultry and fish feed industries, maize area is rapidly expanding in South Asia. Current tillage and crop establishment (TCE) practices are however associated with high levels of input use, including direct and indirect forms of energy. In Bangladesh, policy makers emphasize the need to reduce the USD 1.4 billionyear-1 agricultural energy subsidy. Bangladeshi farmers cultivate maize during the winter rabi season, when yield potential is high. But when poorly managed, farmers' investments in TCE practices may erode farm-level profitability, while inefficiently utilizing energy. Resource-conserving TCE options may however provide an alternative for maintaining or raising yields, while increasing farmers' income and reducing energy use. We present a multi-criteria assessment of the productivity, profitability and energetics of alternative TCE options, including zero (ZT), reduced (RT), and strip tillage (ST), in addition to fresh (FBs) and permanent bed planting (PBs), contrasted with conventional tillage (CT) in Bangladesh's main maize producing agro-ecological zones (AEZs). Trials were conducted in 184 farmers' fields in Bangladesh's northwestern districts with coarse-textured soils (Rangpur and Rajshahi in AEZs 3 and 11, respectively) and in one eastern district with fine-textured soils (Comilla in AEZ 19). Trials spanned the 2009-2010 to 2012-2013 rabi seasons. Significant TCE effects on grain yield were observed in AEZs 3 and 11, but not in AEZ 19. Compared to CT, grain yields under FBs, PBs and ST were significantly higher in AEZ 3, and also under FBs and PBs in AEZ 11. Production cost was 7.8% lower, while net profit and benefit-to-cost ratios for the alternative TCE options were 13.7 and 20% greater than CT, although data were inconsistent in AEZ 19. Across AEZs, total energy inputs were significantly higher for CT (30.3.5×103 to 33.8×103MJha-1) compared to alternative options (28.3×103 to 32.7×103MJha-1). Permanent beds required the lowest diesel energy compared to CT. Similarly, energy use efficiency (EUE) was significantly higher for PBs and ST compared to CT in AEZ 3 (7.17-8.08MJMJ-1) and for PBs and FBs in AEZ 11 (8.55-10.26MJMJ-1). Among all options, PBs, FBs and ST provided greater benefits in terms of increased yield and profits, increased EUE, and reduced economic risks in AEZs 3 and 11, but less so in AEZ 19. Poor performance in the latter region was due mainly to poorly-drained low- to medium-low land types that delayed maize planting and impeded optimal establishment. Further efforts are needed to untangle the determinants of spatially variable performance to refine recommendation domains for TCE options for maize in South Asia. © 2015.


Krupnik T.J.,International Maize and Wheat Improvement Center Bangladesh | Ahmed Z.U.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,University of Melbourne | And 6 more authors.
Field Crops Research | Year: 2015

Rising wheat demand in South Asia necessitates crop intensification to meet food security needs. Increased grain output can be achieved by bridging yield gaps on currently farmed land or by expanding cultivation to new land, though the latter entails environmental trade-offs and offers limited potential as most of South Asia's arable land is already cropped. Alternatively, opportunities for boosting production may exist where farmers can transition from single to double cropping and forgo dry season fallows - which are estimated at between 240,000 and 800,000ha in southern Bangladesh - and establish a crop such as wheat following monsoon season rice. Southern Bangladesh's fallows result from prolonged post-monsoon soil saturation, soil salinity, and farmers' low risk-bearing and investment capacity. In response, we assessed the potential to sow wheat on land that is seasonally fallow with approaches that optimize yields while reducing risk and rationalizing costs. Working with 64 farmers in eight production environments, we examined yield response to three genotypes, BG25 and BG27 (with salinity- and heat-tolerant traits) and BG21 (local check), across a gradient of sowing dates, grouped as 'early' (sown before 15 December) and 'late' (after 15 December), under 0, 100 and 133 and 0, 67 and 100kgNha-1 for early- and late-sowing groups, respectively. Across environments and genotypes, yield ranged from 2.11 to 4.77tha-1 (mean: 3.9tha-1) under early-sowing, and from 0.83 to 4.27tha-1 (mean: 2.74tha-1) under late-sowing. Wheat performance varied with environment (1.68-4.77tha-1 at 100kgNha-1 across sowing groups); the lowest yields found where early sowing was delayed and soil salinity levels were elevated. Small but significant (P<0.001) yield differences (0.22tha-1) were found between 100 and 133kgNha-1 for the early-sowing group, though no difference was found between 67 and 100kgNha-1 for late-sowing. Combining early- and late-sowing groups, significant environment×N rate and sowing-group×N rate interactions (both P<0.001) for 100kgNha-1 indicated the importance of site-and time-specific N management in these stress-prone environments. Considering all cultivars and environments, ECa at sowing, flowering and grain filling negatively correlated with yield (r=-0.50, -0.59 and -0.54, all P<0.001). Correlations with ground water depth at flowering and grain filling were negative and significant, but less pronounced in the context of farmer-managed irrigation scheduling. Despite putative stress-tolerance traits in two of the three entries, no genotypic yield differences were found under early-sowing, though small differences (<0.19tha-1) were observed with late sowing. Agronomic fertilizer-N efficiency (AE-N) was consistently higher for 100 than 133 and 67 than 100kgNha-1 for early- and late-sowing. The marginal economic value of N application followed similar trends, indicating that rates of at most 100 and 67kgNha-1 are favorable for sowing before or after December 15th. Wheat can replace dry season fallows in Bangladesh's coastal delta, though site-specific management practices are needed to optimize yields while rationalizing investment costs to avoid the poverty traps that may ensue from poor management. © 2014 Elsevier B.V.


Krupnik T.J.,International Maize and Wheat Improvement Center Bangladesh | Ahmed Z.U.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,International Maize and Wheat Improvement Center Bangladesh | Timsina J.,University of Melbourne | And 5 more authors.
Agricultural Systems | Year: 2015

In South Asia, wheat is typically grown in favorable environments, although policies promoting intensification in Bangladesh's stress-prone coastal zone have resulted in expanded cultivation in this non-traditional area. Relatively little is known about how to best manage wheat in these unique environments. Research is thus needed to identify 'best-bet' entry points to optimize productivity, but classical parametric analyses offer limited applicability to elucidate the relative importance of the multiple factors and interactions that influence yield under such conditions. This problem is most evident in datasets derived from farmer-participatory research, where missing values and skewed data are common. This paper examines the predictive power of three non-parametric approaches, including linear mixed effects models (LMMs), and two binary recursive partitioning methods: classification and regression trees (CARTs) and Random Forests. We collected yield, crop management, and environmental observations from 422 wheat fields in the 2012-13 season, across six production environments spanning southern Bangladesh, where nutrient rates and genotypes were imposed, but management of other production factors varied from farmer to farmer. Fields were grouped into categories including early- and late-sowing, depending on crop establishment before or after December 15, respectively, and in combination, across both early- and late-sowing groups. For each of these groups, we investigated how each non-parametric analysis predicted the factors influencing yield. All three approaches identified nitrogen rate and environment as the most important factors, regardless of sowing category. CART also identified assemblages of high- and low-yielding environments, although those located in saline and warmer thermal zones were not necessarily the lowest yielding, indicating that farmers can optimize crop management to overcome these constraints. The number of days farmers sowed wheat before or after December 15, days to maturity, and the number of irrigations and weedings also influenced yield, though each method weighted these factors differently. LMMs also indicated a slight yield advantage when farmers used stress-tolerant genotypes, though CART and Random Forests did not. One-to-one plots for observed vs. predicted yields from LMMs and Random Forests showed better performance by the former than the latter, with smaller root mean square and mean absolute error for the combined, early- and late-sowing groups, respectively. While the LMMs were superior in this case, Random Forests may still prove useful in the classification and interpretation of farm survey data in which no treatment interventions have been administered. © 2015 Elsevier B.V.


Schulthess U.,International Maize and Wheat Improvement Center Bangladesh | Krupnik T.J.,International Maize and Wheat Improvement Center Bangladesh | Ahmed Z.U.,International Maize and Wheat Improvement Center Bangladesh | McDonald A.J.,International Maize and Wheat Improvement Center
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2015

Remote sensing data are nowadays being acquired within short intervals and made available at a low cost or for free. This opens up opportunities for new remote sensing applications, such as the characterization of entire regions to identify most suitable areas for technology targeting. Increasing population growth and changing dietary habits in South Asia call for higher cereal production to ensure future food security. In the Delta area of Bangladesh, surface water is considered to be available in quantities large enough to support intensification by adding an irrigated dry season crop. Fuel-efficient, low lift axial flow pumps have shown to be suitable to carry water to fields that are within a buffer of four hundred meters of the rivers. However, information on how and where to target surface water irrigation efforts is currently lacking. We describe the opportunities and constraints encountered in developing a procedure to identify cropland for which axial flow pumps could be successfully deployed upon in a 43'000 km2 area. First, we isolated cropland and waterways using Landsat 5 and 7 scenes using image segmentation followed by classification with the random forest algorithm. Based on Landsat 7 and 8 scenes, we extracted maximum dry season enhanced vegetation index (EVI) values, which we classified into fallow, low-, and high-intensity cropland for the last three years. Last, we investigated the potential for surface water irrigation on fallow and low-intensity land by applying a cropping risk matrix to address the twin threats of soil and water salinity. Our analysis indicates that there are at least 20, 000 ha of fallow land under the low-risk category, while more than 100, 000 ha of low-intensity cropland can be brought into intensified production. This information will aid in technology targeting for the efficient deployment of surface water irrigation as a tool for intensification.

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