The notion of adoption is central to efforts to measure technological change in African agriculture, and plays an important role in the evaluation of return on investment in agricultural research and technology development. However, the adoption concept, as it is commonly used in both the literature and development research practice, is seriously flawed and leads to inaccurate and misleading conclusions. The authors outline a design specification for a replacement concept that would provide a better basis for robust empirical research on the economic, social and environmental impacts of investment in agricultural technology development and promotion. They propose that this new concept can contribute to a better and more nuanced understanding of the impacts of technology development interventions.
There is strong advocacy for agricultural machinery appropriate for smallholder farmers in South Asia. Such ‘scale-appropriate’ machinery can increase returns to land and labour, although the still substantial capital investment required can preclude smallholder ownership. Increasing machinery demand has resulted in relatively well-developed markets for rental services for tillage, irrigation, and post-harvest operations. Many smallholders thereby access agricultural machinery that may have otherwise been cost prohibitive to purchase through fee-for-service arrangements, though opportunity for expansion remains. To more effectively facilitate the development and investment in scale-appropriate machinery, there is a need to better understand the factors associated with agricultural machinery purchases and service provision. This paper first reviews Bangladesh’s historical policy environment that facilitated the development of agricultural machinery markets. It then uses recent Bangladesh census data from 814,058 farm households to identify variables associated with the adoption of the most common smallholder agricultural machinery – irrigation pumps, threshers, and power tillers (mainly driven by two-wheel tractors). Multinomial probit model results indicate that machinery ownership is positively associated with household assets, credit availability, electrification, and road density. These findings suggest that donors and policy makers should focus not only on short-term projects to boost machinery adoption. Rather, sustained emphasis on improving physical and civil infrastructure and services, as well as assuring credit availability, is also necessary to create an enabling environment in which the adoption of scale-appropriate farm machinery is most likely.
Background: Crops such as maize, sorghum, and millet are being biofortified with provitamin A carotenoids to ensure adequate vitamin A (VA) intakes. VA assessment can be challenging because serum retinol concentrations are homeostatically controlled and more sensitive techniques are resource-intensive.
Objectives: We investigated changes in serum retinol relative differences of isotope amount ratios of 13C/12C (d13C) caused by natural 13C fractionation in C3 compared with C4 plants as a biomarker to detect provitamin A efficacy from biofortified (orange) maize and high-carotene carrots.
Methods: The design was a 2 3 2 3 2 maize (orange compared with white) by carrot (orange compared with white) by a VA fortificant (VA+ compared with VA2) in weanling male Mongolian gerbils (n = 55), which included a 14-d VA depletion period and a 62-d treatment period (1 baseline and 8 treatment groups; n = 527/group). Liver VA and serum retinol were quantified, purified by HPLC, and analyzed by GC combustion isotope ratio mass spectrometry for 13C.
Results: Treatments affected liver VA concentrations (0.048 6 0.039 to 0.79 6 0.24 mmol/g; P < 0.0001) but not overall serum retinol concentrations (1.3860.22 mmol/L). Serum retinol and liver VA d13C were significantly correlated (R2 = 0.92; P < 0.0001). Serum retinol d13C differentiated control groups that consumed white maize and white carrots (227.1 6 1.2 d13C&) from treated groups that consumed orange maize and white carrots (221.6 6 1.4 d13C&; P < 0.0001) and white maize and orange carrots (230.6 6 0.7 d13C&; P < 0.0001). A prediction model demonstrated the relative contribution of orange maize to total dietary VA for groups that consumed VA from mixed sources.
Conclusions: Provitamin A efficacy and quantitative estimation of the relative contribution to dietary VA were demonstrated with the use of serum retinol d13C. This method could be used for maize efficacy or effectiveness studies and with other C4 crops biofortified with provitamin A carotenoids (e.g., millet, sorghum). Advantages include no extrinsic tracer dose, 1 blood sample, and higher sensitivity than serum retinol concentrations alone.
Rice and wheat are the principal calorie sources for over a billion people in South Asia, although each crop is particularly sensitive to the climatic and agronomic management conditions under which they are grown. Season-long heat stress can reduce photosynthesis and accelerate senescence; if extreme heat stress is experienced during flowering, both rice and wheat may also experience decreased pollen viability and stigma deposition, leading to increased grain sterility. Where farmers are unable to implement within-season management adaptations, significant deviations from expected climatic conditions would affect crop growth, yield, and therefore have important implications for food security. The influence of climatic conditions on crop growth have been widely studied in growth chamber, greenhouse, and research station trials, although empirical evidence of the link between climatic variability and yield risk in farmers’ fields is comparatively scarce. Using data from 240 farm households, this paper responds to this gap and isolates the effects of agronomic management from climatic variability on rice and wheat yield risks in eight of Pakistan’s twelve agroecological zones. Using Just and Pope production functions, we tested for the effects of crop management practices and climatic conditions on yield and yield variability for each crop. Our results highlight important risks to farmers’ ability to obtain reliable yield levels for both crops. Despite variability in input use and crop management, we found evidence for the negative effect of both season-long and terminal heat stress, measured as the cumulative number of days during which crop growth occurred above critical thresholds, though wheat was considerably more sensitive than rice. Comparing variation in observed climatic parameters in the year of study to medium-term patterns, rice, and wheat yields were both negatively affected, indicative of production risk and of farmers’ limited capacity for within-season adaptation. Our findings suggest the importance of reviewing existing climate change adaptation policies that aim to increase cereal farmers’ resilience in Pakistan, and more broadly in South Asia. Potential agronomic and extension strategies are proposed for further investigation.
Crop management innovations are often not discrete fixed stand-alone options—and their adoption may imply various combinations and adaptations. This potentially confounds their impact assessment. This article assesses the resource saving and productivity enhancing impacts of a crop management package revolving around minimum tillage in maize-based farming systems in northwest Ethiopia. An endogenous switching regression model was applied to plot- and household-level survey data collected from 290 rural households operating 590 maize plots during the 2012 production year. Controlling for variations in plot and household characteristics, the average effect of minimum tillage package (minimum tillage package) on maize productivity is 0.44 t/ha. Compared to conventional practice (CP), adoption of the MTP decreased the average male and female labor use in maize production by 14.4 and 8.2 person-days per ha, respectively. Similarly, MTP adoption decreased draft power use for land preparation by 13.2 pair of oxen-days per ha. Compared to CP, in general, there is a considerable short-run maize productivity gain and reduction in labor and draft power use under MTP.
Climate change is expected to impact global food supply and food security by affecting growing conditions for agricultural production. Process-based dynamic growth models are important tools to estimate crop yields based on minimum inputs of climate, soil, crop management, and crop cultivar parameters. Using region-specific cultivar parameters is critical when applying crop models at a global scale because cultivars vary in response to climate conditions, soils, and crop management. In this study, parameters were developed for modern cultivars representing all 17 CIMMYT wheat Mega Environments (MEs) using field experimental data and genetic cultivar relationships for the CROPSIM-CERES model in DSSAT v 4.5 (Decision-Support System for Agrotechnology Transfer). Cultivar performance was tested with independent CIMMYT breeding trial field experiments across several locations. Then crop simulations were carried out at 0.5 × 0.5 ° pixels for global wheat-growing areas, using cultivars representing MEs, soil information, region-specific crop management, and initial soil conditions. Aggregated simulated wheat yields and production were compared to reported country yields and production from Food and Agriculture Organization (FAO) statistics, resulting in a Root Mean Square Error (RMSE) of 1.3 t/ha for yield and 2.2 M t/country for country production. Some of the simulated errors are relatively large at country level because of uncertainties in pixel information for climate, soil, and crop management input and partly because of crop model uncertainties. In addition, FAO yield statistics have uncertainties because of incomplete farm reports or poor estimates. Nevertheless, this new cultivar-specific, partially-validated global baseline simulation enables new studies on issues of food security, agricultural technology, and breeding advancement impacts combined with climate change at a global scale.
Authors: Manickavelu, A.; Joukhadar, R.; Jighly, A.; Caixia Lan; Huerta-Espino, J.; Ahmad Shah Stanikzai; Kilian, A.; Singh, R.P.; Ban, T.
Published in: Plant Science, 2016, vol.252, p.222-229
Mining of new genetic resources is of paramount importance to combat the alarming spread of stripe rustdisease and breakdown of major resistance genes in wheat. We conducted a genome wide associationstudy on 352 un-utilized Afghan wheat landraces against stripe rust resistance in eight locations. Highlevel of disease variation was observed among locations and a core-set of germplasm showed consis-tence performance. Linkage disequilibrium (LD) decayed rapidly (R2≈ 0.16 at 0 cM) due to germplasmpeerless diversity. The mixed linear model resulted in ten marker-trait associations (MTAs) across allenvironments representing five QTL. The extensively short LD blocks required us to repeat the analysiswith less diverse subset of 220 landraces in which R2decayed below 0.2 at 0.3 cM. The subset GWASresulted in 36 MTAs clustered in nine QTL. The subset analysis validated three QTL previously detectedin the full list analysis. Overall, the study revealed that stripe rust epidemics in the geographical originof this germplasm through time have permitted for selecting novel resistance loci.
Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.
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Field trials were conducted in Haryana representing the northwestern Indo-Gangetic Plains (IGP) to assess the changes brought about by management, including conservation agriculture (CA) practices, in the global warming potential (GWP) of conventional rice–wheat systems. Conservation agriculture is an approach to managing agro-ecosystems for improved and sustained productivity, by way of minimal soil disturbance, permanent soil cover with organic matter or cover crops and crop rotation. Methane (CH4) and nitrous oxide (N2O) fluxes were measured using static chambers. Experiments involved four cropping system scenarios with different CA components, and different N rates. In addition, emissions of CH4 and N2O fluxes were measured in farmers’ fields to establish baselines. The dynamics of CH4 emissions were controlled by floodwater levels, and fertilizer N had no effect. On the other hand, N application rates and timing in relation to soil water status determined the N2O emissions in rice fields. Nitrous oxide fluxes could be avoided by applying N fertilizer to wet soil or by irrigating the field not later than 1 day after N application. Applying crop residues on soil surface had no significant effect on the seasonal CH4 and N2O emissions. It was estimated that switching rice crop establishment method from conventional to CA-based practices in Haryana could reduce GWP for rice by 23% or by 1.26 Tg CO2 eq yr−1. An intensive CA-based rice–wheat and maize–wheat system reduced GWP by 16–26% or by 1.3–2.0 Tg CO2 eq yr−1 compared with the conventional rice–wheat system. However, this reduction in GWP would be from a decrease in diesel and electricity consumption and not from direct emissions of CH4 and N2O, which were higher in the maize–wheat system than in the rice–wheat system.
Authors: Glover, D.; Sumberg, J.; Andersson, J.A.
