• Journal of Multimedia Information System
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• 제7권1호
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• pp.17-24
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• 2020

Rice (Oryza Sativa) is an important source of food for the people of our country, even though of world also .It is also considered as the staple food of our country and we know agriculture is the main source country's economy, hence the crop of Rice plays a vital role over it. For increasing the growth and production of rice crop, ground-breaking technique for the detection of any type of disease occurring in rice can be detected and categorization of rice crop diseases has been proposed in this paper. In this research paper, we perform comparison between two classifiers namely MDC and Bayes' classifiers Survey over different digital image processing techniques has been done for the detection of disease in rice crops. The proposed technique involves the samples of 200 digital images of diseased rice leaf images of five different types of rice crop diseases. The overall accuracy that we achieved by using Bayes' Classifiers and MDC are 69.358 percent and 81.06 percent respectively.

• Agribusiness and Information Management
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• 제7권1호
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• pp.1-9
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• 2015

The purpose of this study is to develop a growth prediction model that can predict growth and development information influencing the production of citrus fruits: the growth model algorithm that can predict floral leaf ratio, number of fruit sets, fruit width, and overweight depending on the main period of growth and development with consideration of the applied weather factors. Every year, large scale of manpower was mobilized to investigate the production of outdoor-grown citrus fruits, but it was limited to recycling the data without an observation supporting system to systemize the database. This study intends to create a systematical database based on the basic data obtained through the observation supporting system in application of an algorithm according to the accumulated long term data and prepare a base for its continuous improvement and development. The importance of the observed data is increasingly recognized every year, and the citrus fruit observation supporting system is important for utilizing an effective policy and decision making according to various applications and analysis results through an interconnection and an integration of the investigated statistical data. The citrus fruit is a representative crop having a great ripple effect in Jeju agriculture. An early prediction of the growth and development information influencing the production of citrus fruits may be helpful for decision making in supply and demand control of agricultural products.

• 한국작물학회지
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• 제44권4호
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• pp.330-338
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• 1999

Extensive research has been conducted on effects of drought stress on growth and development of soybean but information is rather restricted on the limited-irrigation system by way of precaution against a long-term drought condition in the future. The experiment for limited-irrigation was conducted in transparent vinyl shelter at Asian Vegetable Research and Development Center (AVRDC), Taiwan in 1997. Two soybean varieties, Hwangkeum and AGS292, improved in Korea and AVRDC, respectively were used for this experiment. The relationships between normalized transpiration rate (NTR) and fraction of transpirable soil water (FTSW) in both varieties were similar that the NTR was unchanged until FTSW dropped to about 0.5 or 0.6. At FTSW less than those values, NTR declined rapidly. Days required to harvest in both varieties were significantly prolonged at IR6 treatment compared to any other treatments. Daily mean transpiration rate was significantly higher at IR5 treatment, as averaged over varieties. Similarly, water use efficiency was also high at 1R5 treatment. In both varieties, seed yield was the greatest at the IR5 treatment, as compared to any other limited-irrigation treatments, due to the increased seed number and high transpirational water use efficiency. The indices of input water and seed yield for the different limited-irrigation treatments against control indicated that Hwangkeum produced 59.6% or 60.7% of seed yield using 36.1% or 44.9% of input water, as compared to control, by irrigation at only R5 or R6 stages, respectively. The AGS292 produced 56.1% of seed yield with 35.4% of input water of control, when irrigated at R5 stage. The results of this study have elucidated that the limited irrigation at R5 stage in soybean can be minimized yield loss with such small quantity of water under the environment of long-term drought stress and the expected shortage of agricultural water in the future.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.1209-1211
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• 2012

최근 들어 모바일 단말기의 보급이 확대되면서 스마트 워크, NFC, USN등 사회 전반적으로 많은 분야에서 활용도가 높아지고 있다. 이에 본 논문에서는 모바일 단말기를 활용하여 농가에서 시설 원예작물의 생장 및 생산량을 예측하고 데이터를 관리하기 위한 연구를 진행하여 농가에서의 모바일 단말기 활용을 돕고 시설 원예작물의 재배에 도움이 되고자 한다.

• 한국작물학회지
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• 제23권2호
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• pp.141-144
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• 1978

패모린경의 무게를 15gr, 3gr, 5gr, 7gr, 9gr의 5등급별로 나뉘어 파종하였을 때에 그에 따른 발아상태, 초장, 개화, 자구 및 수량에 대하여 조사하였다. 1. 인경의 무게가 1.5gr 및 3gr되는 것은 발아시, 발아기간이 5gr, 7gr, 및 9gr되는 것에 비하여 발아시가 늦고 발아기간이 긴 경향을 나타냈고, 초장도 3∼5분지 1밖에 되지 않었다. 2. 개화는 인경이 무겁고 영양상태가 양호한 7gr∼9gr 상태에서 50％∼75％ 였으나, 3gr이하의 것은 1％에 불과했다. 또한 자구는 5gr이상에서 현저한 증가를 보였다. 3. 수량을 증가시키기 위하여서는 5gr이상의 패모를 사용하여야 한다는 사실을 알게 되었다.

• 스마트미디어저널
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• 제12권10호
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• pp.47-54
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• 2023

지구 온난화로 인해 갑작스러운 기후변화와 농업 생산성에 대한 이해가 점점 중요해지면서, 토양 수분 예측은 농업에서 핵심 주제로 떠오르고 있다. 토양 수분은 농작물의 성장과 건강에 큰 영향을 미치며, 적절한 관리와 정확한 예측은 농업 생산성 향상과 자원 관리의 핵심 요소이다. 이러한 이유로 토양 수분 예측은 농업 및 환경 분야에서 큰 주목을 받고 있다. 본 논문에서는 머신러닝 알고리즘인 랜덤 포레스트를 통하여 시범포를 이용하여 노지 환경 데이터를 수집하고 분석하여 데이터 특성들과 토양 수분의 상관관계를 구하고 토양 수분 실제 값과 예측값을 비교하였으며 비교 결과 예측률이 약 92%의 정확성을 갖는다는 것을 확인하였다. 추후 연구를 통해 작물의 생장 데이터 변수들을 추가하여 토양 수분 예측을 진행한다면 토양 수분에 따른 작물의 생장 속도, 적절한 관수 타이밍 등의 주요 정보를 정확하게 제어함으로써 작물의 품질 상승, 물 관리 효율 증가 등 생산성 및 자원 효율성에 좋은 영향을 미칠 것이라고 기대된다.

• 현장농수산연구지
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• 제26권2호
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• pp.14-24
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• 2024

To enhance the usability of smart agriculture, methods for utilizing smart farm data are required. Therefore, this study proposes a scheme for utilizing regional smart farm data by linking it to services. The current status of domestic and foreign smart farm data collection and linkage services is analyzed. To collect and link regional smart farm data, necessary data collection, data cleaning, data storage structure and schema, and data storage and linkage systems are proposed. Based on the standards currently being implemented for regional smart farm internal data storage, a farm schema, environmental information schema, facility control information schema, and growth information schema are designed by extending the crop schema and crop main environmental factor information database schema. A data collection and management system structure based on the Hadoop Ecosystem is designed for data collection and management at regional smart farm data centers. Strategies are proposed for utilizing regional smart farm data to provide smart farm productivity improvement and revenue optimization services, image-based crop analysis services, and virtual reality-based smart farm simulation services.

• International journal of advanced smart convergence
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• 제9권1호
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• pp.132-140
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• 2020

It is very important to use appropriate nutrition water for crop growth in hydroponic farming facilities. However, in many cases, the supply of nutrition water is not designed with a precise plan, but is performed in a conventional manner. We proposes a forecasting technique for nutrition water requirements based on a data analysis for optimal strawberry production. To do this, the proposed forecasting technique uses linear regression for correlating strawberry production, soil condition, and environmental parameters with nutrition water demand for the actual two-stage strawberry production soil. Also, it includes predicting the optimal amount of nutrition water requires according to the heterogeneous cultivation environment and variety by comparing the amount of nutrition water needed for the growth and production of different kinds of strawberries. We suggested study uses two types of section beds that are compared to find out the best section bed production of strawberry growth. The dataset includes 233 samples collected from a real strawberry greenhouse, and the four predicted variables consist of the total amounts of nutrition water, average temperature, humidity, and CO₂ in the greenhouse.

• 농업과학연구
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• 제45권4호
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• pp.749-760
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• 2018

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, the Korean government has pursued cultivating upland crops in paddy fields to reduce overproduced rice in Korea. For this policy to succeed, it is critical to understand the topographic information of paddy fields and its effects on upland crops cultivated in the soils of paddy fields. The objective of this study was to characterize the growth properties of sesame and perilla from paddy fields with three soil topographic features and soil water effects which were induced by the topographic features of the sesame and perilla. The crops were planted in paddy fields located in Miryang, Gyeongnam with different topographies: mountain foot slope, local valley and alluvial plain. Soil water contents and groundwater levels were measured every hour during the growing season. The paddy field of the mountain foot slope was significantly effective in alleviating wet injury for the sesame and perilla in the paddy fields. The paddy field of the mountain foot slope had a decreased average soil water content and groundwater level during cultivation. Stress day index (SDI) from the alluvial plain paddy field had the greatest values from both crops and the smallest from the ones from the paddy field of the mountain foot slope. This result means that sesame and perilla had the smallest stress from the soil water content of the paddy field on the mountain foot slope and the greatest stress from the soil water content of the alluvial plain. It is important to consider the topography of paddy fields to reduce wet injury and to increase crop yields.

• 대한원격탐사학회지
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• 제30권4호
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• pp.493-503
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• 2014

이 논문에서는 대규모 작물 재배 지역의 작물 분류도의 조기 제작을 목적으로 분광학적 혼재를 줄이고, 과거 토지피복도의 작물 재배 패턴을 반영할 수 있는 계층적 분류 방법론을 제안하였다. 특히 작물 생육 주기로부터 다른 분광 특성을 고려한 계층적 분류 접근을 적용하고, 과거 작물 재배 패턴으로부터 추출된 시간적 문맥 정보를 함께 고려함으로써 분광 혼재가 두드러진 화소의 영향을 줄일 수 있다. 제안 분류 기법의 적용성을 평가하기 위해 미국 아이오와 주 전체를 대상으로 시계열 MODIS 250 m 정규식생지수 자료와 과거 crop data layer를 사용하는 사례 연구를 수행하였다. 사례 연구를 통해 다른 분류 단계와 과거 작물 재배 패턴을 고려함으로써 대상 지역의 주요 재배 작물이면서 분광학적 유사도가 두드러진 콩과 옥수수를 효과적으로 구분할 수 있었다. 그리고 분광 정보만을 이용한 분류 결과에 비해 제안 기법이 최소 7.68%p에서 최대 20.96%p의 향상된 분류 정확도를 보였다. 또한 분류 단계에서 시간적 문맥 정보를 결합함으로써 사용 NDVI 자료의 수에 영향을 덜 받는 가장 높은 분류 정확도(최대 전체 정확도: 86.63%)를 얻을 수 있었다. 따라서 제안 분류 기법은 주요 곡물 수입국의 대규모 작물 구분도의 조기 제작에 유용하게 사용될 수 있을 것으로 기대된다.