• Title/Summary/Keyword: Farm selection

Search Result 174, Processing Time 0.027 seconds

The effect of the 6th industrialization in agriculture on farm and off-farm income (농업의 6차산업화가 농가 및 농업법인의 농업 및 농외소득에 미치는 영향)

  • Park, Jong Hoon;Hwang, Jae Hee;Lee, Seong Woo
    • Journal of Korean Society of Rural Planning
    • /
    • v.20 no.4
    • /
    • pp.193-208
    • /
    • 2014
  • This study aims to identify feasible policy direction of the 6th industrialization in agriculture based on the current agricultural and rural environment in Korea. To do so, this study employes a heckman selection model to correct a probable selection bias, utilizing the Korean agricultural census in 2010 and the agricultural statistics of farm enterprises in 2011. This study focuses on the differences of the farm and off-farm income determinants, according to conjoint types of the 6th industrialization such as Type 1 (primary+secondary+tertiary) vs. Type 2 (primary+secondary or primary+tertiary). The empirical results show Type 2 has much higher possibilities to earn farm and off-farm income in Korea, especially for farm enterprises. This study concludes with providing some policy implications reflecting rural and agricultural environment in Korea.

AHP Model for Selecting a Fish Farm Site (어류양식장의 입지선택을 위한 계층분석과정(AHP)모형)

  • Lee, Kang-Woo
    • The Journal of Fisheries Business Administration
    • /
    • v.38 no.1 s.73
    • /
    • pp.19-45
    • /
    • 2007
  • There have not been many studies which considered both quantitative and qualitative location factors on the issues of site selection problems for a fish farm. This study develops AHP(analytic hierarchy process) model to resolve site selection problem for a fish raising farm by using quantitative and qualitative factors. In order to evaluate the validity of the location factors found in the literature review, the study used advice from fish raising farmers and related academic experts. Four major factors have been selected as economic factors, social factors, natural environmental factors and infrastructures. An AHP structural diagram has developed by considering the factors and potential sites proposed for fish farming. Through the survey on the preference of factors and potential sites, pairwise comparison matrices have been estimated and used to calculated the relative weights of each potential site. The AHP model process shown in the study can be applied to resolve site selection problems for fish raising farmers.

  • PDF

The Impact of Computer Applications on the Improvement of Farm Household Income (정보화가 농가소들 증대에 미치는 영향)

  • Yu, Seung-Ju;Cho, Joong-Koo;Lee, Seong-Woo
    • Journal of Korean Society of Rural Planning
    • /
    • v.12 no.3 s.32
    • /
    • pp.81-95
    • /
    • 2006
  • The objective of the this study is to find a way to increase fm household income through investigating their computer applications. We utilized the 2000 Korea Agricultural Survey data and applied a Heckman Selection Model to correct a selection bias. The present study found the following results. First, determinant of income among fm households by the level of computer applications has significant statistical differences based on their choices of computer applications. Accordingly, the application of general linear regression about fm income without adjusting these choices may cause statistical fallacy. Second, it has been reported that increasing the member of household is not directly related to increasing the fm income. In case of computer-own farm household, the effect of decrease in income according to increasing in age was predicted. However, in the fm household not possessing computer, it shows negative relationship. It shows that an agricultural career of farm owner and educational attainment of all farm household members have positive relationship regardless of computer possession. The income of the farm household those main field is not agriculture is also found to be lower than that of farm household whose major earnings come from agriculture.

Solid Culture Medium Selection Criteria for Hydroponics Farm Households (양액재배 농가의 고형배지 선택 기준에 관한 연구)

  • Kim, Dong-Seok;Kim, Dae-Young;Hwang, Jae-Hyun;Yun, Hoa-Young
    • Korean Journal of Organic Agriculture
    • /
    • v.22 no.4
    • /
    • pp.841-854
    • /
    • 2014
  • This study aimed to analyze the selection criteria and priority settings for solid culture medium used in hydroponic crop production in farm households. Expert brain storming was carried out to extract solid culture medium selection criteria for hydroponic farming. As a result, 3 criteria of economy (cost), productivity, and environment, and 9 factors were extracted. A questionnaire survey of hydroponic farm households was conducted in Gyeonggi, Gangwon, and Chooncheong provinces. AHP analysis of the hydroponic solid culture medium selection criteria identified productivity as the most important criterion, chosen by 58.7% of the respondents, followed by economy (28.4%) and environment (12.9%). The 9 factors were rated by the respondents in the following decreasing order of importance: 1, crop yield (28.3%); 2, pest occurrence (18.5%); 3, maintenance/management costs (12.0%); 4, convenience of maintenance/management (13.4%); 5, initial investment cost (11.6%); 6, material energy consumption (6.5%); 7, waste recyclability (4.0%); 8, waste disposal costs (3.4%); and 9 environmental emissions (1.81%). These results imply that hydroponic farm households consider cultivation-related quality factors more important than economic factors, such as price of culture medium or installation cost.

A Study on Effects of Adopting ICT in Livestock Farm Management on Farm Sales Revenue (정보화기기 활용이 국내 축산농가 총판매금액에 미치는 영향 분석)

  • Hanna Jeong;Jimin Shim;Yerin Lim;Jongwook Lee
    • Journal of Korean Society of Rural Planning
    • /
    • v.30 no.1
    • /
    • pp.81-97
    • /
    • 2024
  • This study examines the effects of adopting Information and Communication Technology (ICT) in livestock farm management on farm sales revenue. Using the 2020 Census of Agriculture, Forestry, and Fisheries, a nationally representative data set constructed by Statistics Korea, this study focuses on a sample of 9,020 livestock farms in South Korea. We employ Propensity Score Matching (PSM) methods to address the potential selection bias between 2,076 farms that used ICT for livestock farm management and 6,944 farms that did not. The findings consistently show that the use of ICT significantly increases farm revenue, taking into account the selection bias. The utilization of ICT in livestock farms leads to a higher increase in sales revenue, particularly for farms with greater sales.

The Effect of Crop Diversification on Agricultural Income (작목다각화가 농업소득에 미치는 영향)

  • Choi, Do Hyeong;Choi, Eunji;Lee, Seong Woo
    • Journal of Korean Society of Rural Planning
    • /
    • v.27 no.4
    • /
    • pp.1-12
    • /
    • 2021
  • The purpose of this study is to analyze the effect of crop diversification on farm households' agricultural income. Abundant literature have explored the determinants and efficient strategies for crop diversification. Yet, there is a paucity of research studies that empirically test the effectiveness of crop diversification as a profitable farm management strategy. Utilizing the 2015 Agricultural Census, this study adopts a quasi-experimental research design to compare the outcomes between farm households that opted for crop diversification and farm households that did not engage in such a strategy. In doing so, this study applies the Heckman Selection Model and the decomposition technique to address the problem of selection bias and to identify the causal effect. Our empirical results show that farms that implement diversification are more likely to earn higher agricultural income than non-diversified farms, although the difference would not be much substantial. This study concludes with several policy proposals to stabilize agricultural income in conjunction with crop diversification.

Assessment of Possible Resources and Selection of Preparatory Sites for Offshore Wind Farm around Korean Peninsula (국내 해역의 해상풍력 가능자원 평가 및 예비부지 선정)

  • Kim, Ji-Young;Kang, Keum-Seok;Oh, Ki-Yong;Lee, Jun-Shin;Ryu, Moo-Sung
    • New & Renewable Energy
    • /
    • v.5 no.2
    • /
    • pp.39-48
    • /
    • 2009
  • Recently, developing the offshore wind farm in Korean peninsula is widely understood as essential to achieve the national target for the renewable energy. As part of national plan, KEPRI (Korea electric power research institute) is performing the front running project for the offshore wind farm development that is dedicated to investigate the possible resources based on the economy considering current technological status. It also includes the selection of the first sea area among candidates and optimal design of the offshore wind farm, etc. In this paper the interim results of the project are summarized that the possible capacity for the offshore wind farm can be estimated conservatively around 18 GW regarding the wind power class, sea depth and social constraint. The five western sea areas near Taean, Gunsan, Gochang, Yeonggwang, Sinan were chosen for the candidating sites. Detailed analysis for these sites will be conducted to finalize the first-going offshore wind farm in Korea.

  • PDF

Tracing the breeding farm of domesticated pig using feature selection (Sus scrofa)

  • Kwon, Taehyung;Yoon, Joon;Heo, Jaeyoung;Lee, Wonseok;Kim, Heebal
    • Asian-Australasian Journal of Animal Sciences
    • /
    • v.30 no.11
    • /
    • pp.1540-1549
    • /
    • 2017
  • Objective: Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP) markers strictly selected through least absolute shrinkage and selection operator (LASSO) feature selection. Methods: We performed farm tracing of domesticated pig (Sus scrofa) from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results: We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion: The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.