• 농업과학연구
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• 제51권1호
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

• Journal of Biosystems Engineering
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• 제24권2호
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• pp.135-144
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• 1999

An yield monitoring system plays a key role in precision farming. An yield monitoring system and a DGPS were implemented to a widely used domestic combine for yield mapping of a small sized paddy field, and yield mapping algorithms were investigated in this study. The yield variation in the 0.1ha rice paddy field was measured by installing a yield flow sensor and a grain moisture sensor at the end of the clean grain elevator discharging grains into a grain tank. Yield map of the test filed was drawn in a point map and a linear interpolated map based on the result of the field test. The size of a unit yield grid in yield mapping was determined based on the combine traveling speed, effective harvesting width and data storing period. It was possible to construct the yield map of a small sized paddy field.

• 드라이브 ㆍ 컨트롤
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• 제21권2호
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• pp.36-43
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• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• Journal of Biosystems Engineering
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• 제41권4호
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• pp.408-417
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• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.773-782
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• 2007

The statistical process control charts are very extensively used for monitoring of process mean, deviation, defect rate or reject rate. In this paper we consider a control chart to monitor the process reject rate in the high yield process, which is based on the observed cumulative probability of the number of items inspected until r defective items are observed. We first propose selection of the optimal value of r in the CPC-r charts, and also consider the usefulness of the chart in high yield process such as semiconductor or TFT-LCD manufacturing process.

• 대한원격탐사학회지
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• 제33권5_2호
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• pp.617-620
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• 2017

농작물 작황 추정은 생산량 예측을 통한 수급 조절, 가격 예측, 농가 소득 보전을 위한 정책 수립 등에 중요한 판단자료로 활용된다. 급변하는 국내외 여건에서 작물의 안정생산과 식량안보, 생태계 지속성 평가를 위해 원격탐사 등 국가차원의 미래기술 개발 노력이 요구되고 있다. 농촌진흥청은 2010년부터 국내외 주요 곡물생산지대 작황 평가를 위한 원격탐사, 작물모형, 농업기상 분야 원천기술 개발을 위해 노력해왔다. 본 특별호는 농촌진흥청에서 지난 8년간 국내외 작황 평가를 위해 수행해 온 원격탐사, 작물모형, 농업기상 분야의 연구개발 성과 및 연계된 이들 분야 간 융복합 연구 수행 현황을 정리하고 향후 연구 방향을 제시하고자 발간하게 되었다.

• 대한산업공학회지
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• 제36권3호
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• 한국농림기상학회지
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• 제22권3호
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• pp.176-182
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• 2020

작황조사시험은 우리나라주요 재배지점에 대해 해당 지역에서 주로 재배되는 품종들을 선정하여 장기적으로 벼의 생육과 수량을 관찰하는 연구이다. 이 연구의 목적은 기상 및 병해충의 변화에 따라 재배방법을 능동적으로 수정하여 대응하기 위한 것이다. 장기적인 자료 축적으로 이를 다양한 분야에서도 활용할 수 있도록 이 시험의 이루어지는 장소와 재배관리, 각 장소에 대응하는 기상관측소, 관찰되는 항목들에 대해 소개하였다. 각 관찰항목은 표준적인 절차에 따라 조사되어 일정한 품질이 유지되고 있으며 이 정보들은 현재 문헌으로 모두 공개되어 있으며 전산자료의 형식으로 획득할 수 있다.

• 한국지반환경공학회 논문집
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• 제11권6호
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• pp.57-67
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• 2010

국가지하수관측소와 같은 관측 지점에서의 지하수 시계열 자료를 활용한다면 지하수위 변동법에 의한 지하수 함양율을 산정할 수 있으나, 비산출율 추정에 필요한 양수시험 자료와 토양시료 등의 부족으로 적용에 제약이 있어 왔다. 본 연구에서는 3개의 군집에 속하는 34개 국가지하수 관측망의 충적 관측정을 대상으로 갈수기의 강우 이벤트와 지하수위 상승량 관계를 이용한 비산출율 산정 기법을 적용해 보았다. 군집 1과 군집 2에 속하는 관측정은 강우에 대한 지하수위 반응이 뚜렷하지 않기 때문에 본 방법의 적용이 곤란하며, 군집 3에서 강우에 대한 지하수위 반응 시차가 2일 이내인 19개 관측정의 경우는 추정 비산출율이 0.06에서 0.27의 범위로써 평균 0.17로 분석되었는데 이는 토양 입자에 따른 비산출율 및 양수시험에 의한 비산출율과 유사한 것으로 나타났다. 본 방법은 주변 하천과의 관계, 배출 작용, 증발산 및 양수 등의 영향으로 일부 과다 산정의 우려가 있으나 현장조사를 통하여 주변 영향이 적은 국가지하수 관측정을 선정한다면 적용 가능하다.

• 한국작물학회지
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• 제53권4호
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• pp.388-393
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• 2008

광범위한 지역의 재배면적과 생산량을 신속하고 경제적으로 모니터링 할 수 있는 광학(LANDSAT) 중해상도 위성 영상을 활용하여 벼 재배면적, 생육 및 수량을 모니터링 할 수 있는지를 검토하였다. 1. 식생지수와 수량과의 관계를 살펴보면, EVI를 제외한 모든 식생지수와 수량간에는 정의 상관관계를 보였으며, NDVI_SWIR이나 EVI_SWIR과는 유의성이 없었다. NDVI가 RVI보다 수량과의 상관도가 다소 높았으며, 수량과 가장 밀접한 식생지수는 $NDVI_R$(r = 0.68)이었다 2. LANDSAT 단일시기 영상(2004년 7월 29일)을 활용하여 서산간척지 지역내 벼 수량을 모니터링한 결과 $NDVI_R$와 백미수량간에는 1차 직선관계($R^2$ = 0.46)가 성립하였으며, 필 지중에서 면적이 다소 적거나 주변에 반사특성에 영향하는 요인이 있는 지역을 제외하여 살펴본 결과 추정도가 다소 높아졌다($R^2$ = 0.66). 3. 논구역 벡터를 사용하여 논구역 정보를 추출하는 기존의 방법 대신 raster 기반의 논구역 masking을 제작하여 논 구역 정보를 추출하였는데 이 방법을 통해 쉽고 빠르게 논구역 정보를 추출할 수 있었다. 4. 연차별 지역적용가능성을 검토하기 위해 1994년 7월 26일 경기도내 7개 시군의 논구역 masking을 제작하여 NDVIred를 추출하고 $NDVI_R$-수량관계식을 이용하여 수량을 추정한 결과 1:1 line에 근접하여 비교적 잘 일치되었다.