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Kafe 바로가기주관연구기관 | 국립식량과학원 National Institute of Crop Science |
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보고서유형 | 최종보고서 |
발행국가 | 대한민국 |
언어 | 한국어 |
발행년월 | 2016-02 |
과제시작연도 | 2015 |
주관부처 | 농촌진흥청 Rural Development Administration(RDA) |
등록번호 | TRKO201600003165 |
과제고유번호 | 1395041572 |
사업명 | 작물시험연구 |
DB 구축일자 | 2016-06-25 |
DOI | https://doi.org/10.23000/TRKO201600003165 |
Ⅳ. 연구개발결과
콩ㆍ참깨ㆍ팥ㆍ조의 재배농가 저수 요인 및 요인별 생산성 감소 정도 규명과 농가현장 실증 실시
Yield gap of sesame between leading (110kg/10a) and usual farm (66kg/10a) is 60%. Purpose of this research is to investigate the reason and compensate the defects, thus reduce the yield gap between these two groups.
Firstly, questionnaire on cultivation practice and final yield was conducted to f
Yield gap of sesame between leading (110kg/10a) and usual farm (66kg/10a) is 60%. Purpose of this research is to investigate the reason and compensate the defects, thus reduce the yield gap between these two groups.
Firstly, questionnaire on cultivation practice and final yield was conducted to figure out which is the main reason of yield decrease. For each cultivation practices such as planting density and pest control, ratio of farmers who follow the standard cultivation method and who are not was calculated. According to this survey, following the appropriate planting density (31.6%), and renewal of varieties (26.9%) turned out to be the most influential factors affecting yield.
Based on the aforementioned results, plant growth and yield in customary and standard cultivation farm were compared. This investigation was conducted in five regions-Goesan, Yecheon, Miryang, Gochang and Haenam. 1000-seed weight and yield showed significant difference between varieties and planting density. Farmers who followed the standard cultivation method achieved higher yield and seed quality. Therefore, providing appropriate guidance to customary cultivation farmer using these results is strongly required.
Currently cultivation area of soybean and percentage of self-sufficiency has been decreasing in Korea. The trend of soybean yield in farm is at a standstill. The difference of soybean yield between farm is large and soybean yield is low compared to the potential yield. During that time, to obtain a high yield in soybean many researchs focused on imputing cultivation techniques. A research for factors affecting to soybean yield through comprehensive analysis of actual condition in soybean cultivation have not practiced in our country. Accordingly, this research was carried out to investigate factors affecting to soybean yield based on actual condition of farmer’s field. This research was performed at three major soybean producing districts, Paju, Andong and Muan from 2013 to 2014. The soybean cultivar Daewon was grown in Paju and Andong, and the other cultivar Taekwang in Muan. Survey was conducted in 2013 for soybean cultivation factors in 2012, and the investigation in 2014 was practiced for survey on cultivation factors in 2013 along with field investigation. The contents of questions and field investigation were seeding dates, planting distances, frequency of fungicide and pesticide treatment, degree of weed occurrence, P.E. film mulching or non mulching, amount of fertilizer application, irrigation frequency, paddy or upland field and soybean yields in this study. Investigation factors were analyzed using multiple regression model of SAS program. The results of multiple regression analysis in three districts for three years are described follows: soybean yield increased by 488kg/ha(23%) under P.E. film mulching, 520kg/ha(24%) in paddy field cultivation, and 165kg/ha(7%)/10a per supplement irrigation to three times. Based on above results, even though factors affecting to soybean yield differs under weather condition in each district, major factor of soybean yield decrease was shortage of soil moisture during June and September according to the investigated data at three districts during three years in this research. At the farmer’s field experiment, result which were conducted three locations at the same site, was higher 19 % than farmer’s traditional cultivation.
Anaylsis on cause of yield degradation factor and gap of farm productivity in Adzuki bean(Vigna angularis Ohwi & Ohashi). This research was conducted for 3 years from 2013 to 2015. The survey information was cultivar, seeding date, way of sowing, planting distance, cropping system, fertilization method, way of weed, disease and insect pest control, P.E. film mulching, irrigation frequency and adzuki bean yield. Most of farmhouses cultivated varieties like Chungju-pat, Hongeon-pat and Arari-pat, whereas 26% of farmhouses cultivated domestic varieties. Seeding date was various depending on each farmhouse; 10% the early of June, 15% the middle of June, 22% the end of June, 25% the early of July, 18% the middle of July and 8% the end of July in 2014. Most of the farmers did not follow the standard planting distance and fertilizer using rate was very low(45%). 23% of adzuki bean farmers cultivated in monoculture and rest of them adopted multi-cropping system with following crop. Average yield of farmhouses of new cultivars was higher than that of domestic varieties.
Foxtail millet (Setaria italica L.) traditionally played an important role in farming and food culture in Korea. Although foxtail millet productivity has recently been increased, it is still relatively low compared with that of other countries. Production of foxtail millet sharply declined about from 1,771 ton in 2000 to 785 ton in 2010. This situation has been attributed to the non-technological constraints (infrastructure, policies, input/output markets, and adverse climatic conditions) which reduced profitability and adoption of new technologies. Also, the rate of adoption of a new technology depends on low adoption of production technologies and management systems, like fertilization, plant density and optimal planting date due to lack of efforts to breed high yielding varieties.
Increasing agricultural productivity or yield is critical to economic growth and development. This can be achieved by using improved agricultural technologies and management systems. Yield refers to production per unit area. Yield of a crop is the yield obtained when it is grown in a suitable environment of adequate moisture and nutrients, without pest and disease problems. Yield indicated that, given the area as well as cropping season, yield potential depends on amount of moisture, sunshine intensity, temperature, crop-sowing date, maturity rating, plant population, and light-use efficiency of photosynthesis. Understanding yield gap is very crucial for it’s relationship to crop yield predictions since yield potential shows the probable future productivity to be achieved. Also, information on determinants of yield gap can be used in policy interventions for enhancing crop production. Crop production depends on the crop area and crop yield, therefore it is necessary to raise either of them in order to increase production.
This study was a component of a survey conducted for the aim of delivering improved foxtail millet (Setaria italica L.) production practices to farmers to raise their productivities and the need to increase production by using increasing productivity technologies. It is also important to examine the possibility of realizing the yield potential through the use of improved production practices. This study was, therefore, conducted ⅰ) to measure the variations and the causes for decreasing productivity levels of foxtail millet in different production zones, together with the associated causal factors, ⅱ) to analyze the yield gap as well as some factors of foxtail millet yield, and ⅲ) to develop a suitable strategy to improve the productivity levels of foxtail millet by on-farm evaluation. Hence, it is imperative to assess the yield gaps between farmers and experiments.
This study conducted a cross-sectional survey of selected different climatic zones of foxtail millet-growing districts for two year (2013 ~ 2014). These study were chosen because they have the largest area and a long history of foxtail millet cultivation. The districts selected for the survey were also representative of the relatively diverse range of environments and management practices based on soil type, landscape and history of foxtail millet cultivation obtained from a preliminary survey and secondary data, the production areas in 12 agroecological zones.
The total of 101 survey respondents were randomly selected with multi-stage cluster sampling technique. The survey list contained climatic conditions, locational condition, soil fertility, agricultural technologies and management systems, like cultivation methods, fertilization, plant density, planting date and pests and diseases. Data were collected on management practices, soil properties and crop yields in foxtail millet fields of the sample households in each selected village. A farm survey employing a semi-structured interview, combined with a field visit, was used in collecting information on farmers’ foxtail millet practices for the individual sample households. Information obtained from the farmer interview included - the variety of foxtail millet used, planting date, methods, plant density and amounts of chemical fertilizer and/or manure applied, methods of weeding, disease and insect management done on the crop sampled field, field, and number of years that the household has cultivated foxtail millet. Crop sampling was done for 101 fields, one field for each sample household. In each field, each 1×1 m2, were harvested during the two year from 2013 to 2014. Crop sampling was used to measure foxtail millet yield from each field, while soil samples were taken for laboratory analyses. Prior to harvesting of each plot, plant counts were made, and any insect or disease damage was recorded. Weed density was also scored on a scale of 1-3, where 1=low, 2=moderate, and 3=high weed density. Yield gaps from the highest yielding field were determined for the individual groups. To determine the factors causing the yield gaps, the relationships between yield and possible influencing factors, and between these factors themselves, were first examined using correlations. The factors included - soil quality score, soil type, planting date, crop duration, weed density score, number of weeding, plant population, and years of farmer’s experience in growing foxtail millet.
The survey data were subjected to descriptive and inferential analyses. The experimental yield gap was calculated as the difference between the estimated average yield and the maximum experiment-based yield potential achieved in on-station trials at Department of Functional Crop, NICS. The farmer’s yield gap was also computed as the difference between the maximum farmer yield potential and the estimated average yield which were derived from the yield data of on-station trials(2014). The percent contribution was calculated by dividing grain yield gap over test factor contribution and multiplied by 100. The test factor contribution was calculated by the difference between means of improved yields and those of farmer’s yield of individual test factor. The field experiment was designed to estimate potential yield per hectare gap, factor contribution and yield level of various treatment. The data from which the experimental foxtail millet yield potential was derived were generated from an on-station trial. The yield gaps and their proportion to yield potentials were estimated by data from the survey and on-station trials. The experimental yield gap were calculated as the difference between the estimated average and maximum yield and the experiment-based yield potentials which resulted from on-station trials at Department of Functional Crop, NICS. The farmer’s yield potential was estimated as the maximum of the yields achieved by the respondents on their farms. The factors of foxtail millet yields were analyzed using a regression model. Finally, selected fields for the individual yield groups were compared for the levels of factors that showed a significant influence on yields to elucidate the factors that caused the yield gaps at different yield levels.
In order to assess the gap between farmer’s yields and yields due to improved practices, studies on relative effects of variety, method of sowing measures and management systems, like fertilization, plant density and optimal planting date on grain yield of foxtail millet in 2015. The complete factorial design was applied because it generate data for estimation of yield gap, contribution of individual test factor. The factorial component consisted of factors(production input) at two level, i.e farmer’s practice (FP) and improved practice (IP). This experiment was carried out at four farm fields in Yeongwol-gun (Alluvial plain), yaecheon-gun (Local allvial valley), haenam-gun (Mountain footslope), and naju-si (Rolling hill) under four different locational condition. In the first test factor, which was related to variety, local seed was used in case of farmer’s practice (FP) while improved variety ‘Samdachal’ a waxy blue-gray grain (medium maturing, 133) and ‘Kyeongkwan1‘ a waxy gray grain (medium maturing, 135) were used in improved practice (IP). In the second test factor, which was planting methods, conventional culture was used in case of farmer’s practice (FP) while improved cultivation practices were used ‘High ridge sowing‘ in Yeongwol-gun (Alluvial plain) and in the Yaecheon-gun (Local allvial valley), used ‘Wide row drill seeding‘ in the Haenam-gun (Mountain footslope), and used ‘Broadcast sowing‘ in the Naju-si (Rolling hill). ‘High ridge sowing‘ method seeded by point seeder in high ridge row (60 × 10 cm), ‘Broadcast sowing‘ method was broadcasted on a cross stripes of the field by engine powered duster, and ‘Wide row drill seeding‘ method seeded with a drill seeder attached to tractor in wide ridge. Fertilizer was applied to directly seeded treatments using a combination of 100 kg N, 80 kg P2O5 and 70 kg K2O per ha at 2 day before sowing. Herbicides were sprayed ‘glyphosat-isopropylamine’ 30㎖ of liquid chemical solution to 20ℓ of water on foxtail millet. Measurements including plant height, stem diameter, number of tillers per plant were taken by measuring tape while at harvest, yield parameters like panicle weight, and grain weight were taken by weighing balance.
At maturity, growth upland crops such as plant height, stem diameter, pod number per plant, grain number per panicle and grain yield per unit area were determined each plot. Mean values of minerals compositions and antioxidant compounds were expressed as means±standard deviation (SD) for three replicates. Statistical analysis of growth and yield data were performed by Anova to determine treatment effects at 5% level of significance using statistical package (SAS 2002). Duncan Multiple test was used to separate means across treatments.
The results of this study revealed substantial variations for foxtail millet yields in the production areas. The maximum yield obtained (397.0 kg 10a-1) was considered as the representative of the maximum farm yield. However, great yield gaps relative to the maximum yield were shown for most fields, with the potential for doubling the yield in more than 50% of the fields. The main yield constraints identified were poor emergence, inappropriate methods, lodging, pests, diseases, bird damage and local variety. The field of the highest yield exhibited none of these constraints, while declining crop yields were associated with increasing numbers of constraints, but the constraints sometimes differed for different fields at the same yield level. This situation had been attributed to the low adoption of foxtail millet production technologies. The lowest yielding fields had all factors as constraints. The findings indicated that the percentage of farmer’s yield gap from studies of foxtail millet, for instance, averaged 78.1% for maximum from farmer, and 73.9% for an experiment-based approach of yield potential. The “experimental” yield gap (YGE), “farmer” yield gap (YGF) and “Low farmer” yield gap (YGL) were linked as follows: YGF ≤ YGE ≤ YGL. The “experimental” yield gap (YGE) was estimated to be 73.9 kg per 10a (383.9 - 310.0 kg), “farmer” yield gap (YGF) was estimated to be 87.0 kg per 10a (397.0 - 310.0 kg), and “Low farmer” yield gap (YGL) as estimated to be 292.0 kg per 10a (397.0 - 105 kg). The regression analysis indicated that poor emergence by drought at sowing day, lodging, frequency of spraying fungicides against downy mildew disease, spraying insecticides against corn borer, weeding of farms, local variety planted by farmer, area of farm and total production variables had significant impact on foxtail millet yield. The main factors of this gap were poor emergence by drought at sowing day, inappropriate cultivation methods (36.8%), lodging in harvesting stage (27.6%), pests and diseases (27.9%), bird damage (22.4%) and local varieties (17.0%). The indication of huge yield gap by this study challenges to encourage foxtail millet farmers through pragmatic measures to adopt the increasing yield technologies of foxtail millet production to minimize excessive land expansion.
Contribution of different factors responsible for the increase of foxtail millet production improved practices, studies on relative effects of variety, methods of sowing measures and management systems, like fertilization, plant density and optimal planting date was carried out at four farm field. The results of this study showed that improved practices like variety, methods of sowing and fertilizer in terms of improved practices have significantly increased the foxtail millet grain yield. The grain yield gap was determined by the difference between the yield obtained with all test factors at improved practice (IP) and the yield obtained at farmer’s practice (FP). The grain yield indicated that there was 65.05 kg 10a-1 average yield gap for foxtail millet, showing an increase of 20.7% over that of farmer’s practice, It means that there was a great scope for enhancing foxtail millet productivity. The contribution of individual test factors was calculated as the difference between averaging the yield over all treatments obtained with that test factor at the farmer’s level and the average of yield over all treatment given by that test factor at the improved level. Improved practice (IP) shows that variety, sowing dates and method of sowing by landform were the most prominent constraints in on-farm trial. Their contribution towards average grain yield increase was 14.0% in Yeongwol-gun (Alluvial plain) used ‘High ridge sowing‘, 34.9% in the Haenam-gun (Mountain footslope) used ‘Wide row drill seeding‘ and 17.5% in the Naju-si (Rolling hill) used ‘Broadcast sowing‘.
The Results of this study recommended that the government should encourage foxtail millet farmers, through pragmatic measures, to adopt improved technologies for enhancing productivity instead of focusing on excessive land expansion which eventually leads to low productivity. Different technologies or improved management practices are needed to improve crop yields for the individual fields. Thus, strategies need to be devised to target technologies that are appropriate for individual fields.
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