Site-Specific Agronomic Information and Technology Adoption: A Field Experiment from Ethiopia

Author(s):  
Hailemariam Ayalew
2020 ◽  
Vol 46 (4) ◽  
pp. 345-347
Author(s):  
Erlei Melo Reis ◽  
Mateus Zanatta ◽  
Andrea Camargo Reis

ABSTRACT The evolution of the reduction in Asian soybean rust (caused by Phakopsora pachyrhizi) control by site-specific fungicides has been reported season after season. In a field experiment, the effect of prothioconazole solo and added to multisite mancozeb was evaluated for rust control. Treatments were evaluated in a factorial design of four prothioconazole doses and three mancozeb doses. In a set of treatments, three applications were performed in one soybean cycle and four applications in another one. The first applications were performed at GS V8, 11 days before rust detection, with 2.56% leaflet incidence, while the other applications were at 12 to 14-day interval. Rust severity was quantified, control was calculated in relation to the unsprayed treatment, and soybean grain yield was estimated as kg/ha. Fifty-one to 61% control was obtained with three sprayings and 68% to 70% control with four sprayings of prothioconazole alone. Over 80% control was obtained with at least 0.3 L/ha prothioconazole + 2.0 kg/ha mancozeb, corresponding to 75 g a.i./ha prothioconazole + 1500 g a.i./ha mancozeb. Reduction in P. pachyrhizi control by the use of the site-specific fungicide alone was confirmed, while the addition of mancozeb can recover the efficacy of the site-specific fungicide.


2021 ◽  
Vol 111 (6) ◽  
pp. 1918-1943
Author(s):  
Lori Beaman ◽  
Ariel BenYishay ◽  
Jeremy Magruder ◽  
Ahmed Mushfiq Mobarak

Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low. (JEL O13, O18, O33, Q12, Q16)


2019 ◽  
Vol 11 (4) ◽  
pp. 622-641
Author(s):  
Yingmei Tang ◽  
Yue Yang ◽  
Jihong Ge ◽  
Jian Chen

Purpose The purpose of this paper is to empirically investigate the impact of weather index insurance on agricultural technology adoption in rural China. Design/methodology/approach A field experiment was conducted with 344 rural households/farmers in Heilongjiang and Jiangsu Provinces, China. DID model was used to evaluate farmers’ technology adoption with and without index insurance. Findings The results show that weather index insurance has a significant effect on the technology adoption of rural households; there is a regional difference in this effect between Heilongjiang and Jiangsu. Weather index insurance promotes technology adoption of rural households in Heilongjiang, while has limited impact on those in Jiangsu. Weather, planting scale and risk preference are also important factors influencing the technology adoption of rural households. Research limitations/implications This research is subject to some limitations. First, the experimental parameters are designed according to the actual situation to simulate reality, but the willingness in the experiment does not mean it will be put into action in reality. Second, due to the diversity of China’s climate, geography and economic environment, rural households are heterogeneous in rural China. Whether the conclusion can be generalized beyond the study area is naturally questionable. A study with more diverse samples is needed to gain a fuller understanding of index insurance’s effects on farmers in China. Originality/value This research provides a rigorous empirical analysis on the impact of weather index insurance on farmers’ agricultural technology adoption through a carefully designed field experiment.


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