• Title/Summary/Keyword: Agricultural Risk Coverage

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Explaining Share of Farm Loss Systemic with County Loss in the United States?

  • Kim, Sang-Hyo;Lim, Jin-Soon;Zulauf, Carl
    • Journal of Distribution Science
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    • v.15 no.11
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    • pp.21-29
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    • 2017
  • Purpose - Relationship between farm and county losses determines whether the county program provides too little, too much, or similar amount of assistance relative to the loss on an individual farm. A review of the literature finds limited analysis of the determinants of this relationship. This paper conducts such an analysis using farm-level yield data. Research design, data, and methodology - Farm-level yield data from Illinois and Kansas farm business management associations are used for to calculate the correlation between farm and county loss and the share of farm loss systemic with county loss, and also for the regression analysis. Results - Average share of farm loss systemic with the county loss lies between 42% and 68%. The correlation between farm and county yield/revenue deviation from expected value is statistically significant in all four models. The coefficient is positive, implying the higher the correlation, the larger the share of farm loss that is systemic with the county loss. Conclusions - The findings of this study are consistent with the existing literature which argues that county variability may not be closely associated with farm variability. The findings of this study thus raise questions about the efficacy of area yield and revenue insurance products in helping farmers manage their risk.

CFD Modeling of Pesticide Flow and Drift from an Orchard Sprayer (과수원용 스프레이어의 농약 살포 및 비산 예측을 위한 전산유체해석)

  • Hong, Se-Woon;Kim, Rack-Woo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.60 no.3
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    • pp.27-36
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    • 2018
  • Effective pesticide applications are needed to assure the quality and economic competitiveness of fruit production and lower the risk of spray drift. Experimental studies have shown that better spray coverage and less driftability require an understanding of the transport of spray droplets within turbulent airflows in the orchard and the interaction between droplet dynamics and tree canopies. This study developed a computational fluid dynamics (CFD) model to predict pesticide flows in the orchard and spray drift discharged from an air-assisted orchard sprayer. The model represented the transport of spray droplets as well as droplets captured by tree canopies, which were modeled as a conical porous model and branched tree model. Validation of the CFD model was accomplished by comparing the CFD results with field measurements. Spray depositions inside tree canopies and at off-target locations were in good agreement with the measurements. The resulting data presented that 38.6%~42.3% of the sprayed droplets were delivered to the tree canopies while 13.6%~20.1% were drifted out of the orchard, part of them reached farther than 200 m from the orchard. The study demonstrates that CFD model can be used to evaluate spray application performance and spray drift potential.

Development and Use of Digital Climate Models in Northern Gyunggi Province - I. Derivation of DCMs from Historical Climate Data and Local Land Surface Features (경기북부지역 정밀 수치기후도 제작 및 활용 - I. 수치기후도 제작)

  • 김성기;박중수;이은섭;장정희;정유란;윤진일
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.6 no.1
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    • pp.49-60
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    • 2004
  • Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.

MAKING AGRICULTURAL INSURANCE IN INDIA FARMER-FRIENDLY AND CLIMATE RESILIENT

  • Kumar, K. Nirmal Ravi
    • Agribusiness and Information Management
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    • v.11 no.1
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    • pp.27-39
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    • 2019
  • Agricultural risks are exacerbated by a variety of factors ranging from climatevariability and change, frequent natural disasters, uncertainties in yields and prices, weakrural infrastructure, imperfect markets and lack of financial services including limited spanand design of risk mitigation instruments such as credit and insurance. Indian agriculture has little more than half (53%) of its area still rainfed and this makes it highly sensitive to vagaries of climate causing unstable output. Besides adverse climatic factors, there are man-made disasters such as fire, sale of spurious seeds, adulteration of pesticides and fertilizers etc., and all these severely affect farmers through loss in production and farm income, and are beyond the control of farmers. Hence, crop insurance' is considered to be the promising tool to insulate the farmers from risks faced by them and to sustain them in the agri-business. This paper critically evaluates the performance of recent crop insurance scheme viz., Pradhan Mantri Fasal Bhima Yojana (PMFBY) and its comparative performance with earlier agricultural insurance schemes implemented in the country. It is heartening that, the comparative performance of PMFBY with earlier schemes revealed that, the Government has definitely taken a leap forward in covering more number of farmers and bringing more area under crop insurance with the execution of this new scheme and on this front, it deserves the appreciation in fulfilling the objective for bringing more number of farmers under insurance cover. The use of mobile based technology, reduced number of Crop Cutting Experiments (CCEs) and smart CCEs, digitization of land record and linking them to farmers' account for faster assessment/settlement of claims are some of the steps that contributed for effective implementation of this new crop insurance scheme. However, inadequate claim payments, errors in loss/yield assessment, delayed claim payment, no direct linkage between insurance companies and farmers are the major shortcomings of this scheme. This calls for revamping the crop insurance program in India from time to time in tune with the dynamic changes in climatic factors on one hand and to provide a safety-net for farmers to mitigate losses arising from climatic shocks on the other. The future research avenues include: insuring the revenue of the farmer (Price × Yield) as in USA and more and more tenant farmers should be brought under insurance by doling out discounts for group coverage of farmers like in Philippines where 20 per cent discount in premium is given for a group of 5-10 farmers, 30 per cent for a group of 10-20 and 40 per cent for a group of >20 farmers.