• International Journal of Computer Science & Network Security
• /
• 제22권9호
• /
• pp.403-413
• /
• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• 대한원격탐사학회지
• /
• 제34권1호
• /
• pp.141-150
• /
• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• Journal of Crop Science and Biotechnology
• /
• 제10권1호
• /
• pp.3-7
• /
• 2007

Classification of blast resistance type of 129 Korean rice cultivars was carried out based on reaction pattern to 10 Japanese blast pathogen isolates(Pyricularia oryzae). The cultivars were divided into 11 groups based on the presumed resistance genes as follows; Pia type(19 cultivars), Pita-2 type(4), Pik type(3), Pib type(5), Piz type(11), Pik-s type(8), Pik and Pii type(4), Pia and Pita type(8), Pia and Pik type(6), Pita, Pik and Pii type(4) and no-grouping type(57). These results would provide important information to rice breeding for durable and broad resistance to rice blast.

• 한국작물학회:학술대회논문집
• /
• 한국작물학회 2000년도 춘계 학술대회지
• /
• pp.138-139
• /
• 2000

• Advances in nano research
• /
• 제14권3호
• /
• pp.225-234
• /
• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• The Korean Journal of Ecology
• /
• 제6권2호
• /
• pp.114-127
• /
• 1983

The production and productivity of $C_3 and C_4$ type plants in Korea was studcied In the areas, in which the summer temperature is above $30^{\circ}C,;C_3$ type plants showed“M” type productivity curves exhibiting two peaks in spring and autumn, and C4 type plants showd “Bell” type productivity curves which show one peak in summer(Figs. 1,2,3,4,5). From the result of researching the standing crop of $C_3 and C_4$type plants dcuring August and September in which the standing crop reaches the highest peak, the dominant plants in the natural grass vegetation were almost all of $C_4$ type plants, showing the high standing crop, while the standing crop of $C_3$ type plants shows its high peak in the humid areas, riversides and dams.

• 한국작물학회지
• /
• 제43권4호
• /
• pp.205-208
• /
• 1998

Silica bodies (phytoliths) are becoming of wide use for pedology, archaeology, paleobotany and paleoecology in botany. This study investigated morphological differences of silica bodies in the lamina of wild, indica type, and japonica type rice. Phytoliths in the epidermis of lamina showed noticeable difference among tested plants. Besides, there were also significant differences in the shape and distribution of the silica bodies around stomata and trichomes. Silica bodies in the lamina of the rice plants could be used to classify subspecies of Oryza genus.

• 한국작물학회지
• /
• 제28권2호
• /
• pp.233-239
• /
• 1983

종전에는 Brassica napus에서 성분이 개량되지 않은 유채의 일반 품종들의 Winter type만을 대상으로 춘파성 정도를 분류하고 추태로서 분류기준을 삼았으나 본 시험에서는 같은 B. napus인 Summer type까지를 포함하고 성분이 개량된 양질유ㆍ양박 품종을 공시하여 임실여부로서 분류기준을 삼는 새로운 분류를 시도하여 춘파성 정도를 조사하였던 바 그 결과를 요약하면 다음과 같다. 1. 현재 목포지장에서 보유하고 있는 양질유ㆍ양박 유채(Brassica napus) 품종 및 육성계통들은 8단계 group으로 춘파성 정도를 분류할 수 있었고 춘파성 정도 제Ⅶ group는 Summer type의 계통들이 이에 속하였으며 이들 계통은 Oro, Midas 등의 Summer type의 품종과 교배하여 선발된 계통들이었다. 2. 춘파 파종기에 따른 성숙기변화는 춘파시기가 늦을수록 성숙기는 지연되는 경향이었고 춘파성 정도가 높음에 따라 생육일수와 적산온도가 줄어드는 경향이었다. 3. 춘파성 정도와 내한성 관계는 춘파성 정도가 높을수록 내한성이 낮았으며 춘파성 정도와 초성간에는 춘파성이 높을수록 초성에서 I형에 가깝고 주경의 신장이 분지보다 빈약한 바 이들 모든 상호관계는 고도의 부상관으로 나타났다. 4. 월동에 안전한 추파재배용계통은 춘파성 정도가 낮은 0, I, II group로서 공시품종중 59 품종이 이에 속하였다.

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

• 한국작물학회지
• /
• 제41권3호
• /
• pp.332-339
• /
• 1996

본 시험은 고구마 육종에 필요한 기초 자료를 제공하고자 1993년과 1994년에 작물시험장에서 보유하고 있는 유전자원 100품종에 대하여 전기영동법으로 esterase 동위효소와 단백질 특성을 분류하였던 바 결과는 다음과 같다. 1. 잎의 esterase 동위락소 특성은 14가지 형으로 분류되었고 Ⅸ형에 가장 많은 46품종이 속하여 있으며, 다음은 Ⅶ, I, III, Ⅷ, II 및 V형의 순으로 47품종이 속하여 있고 나머지 7품종은 각기 다른 특성을 가지고 있었다. 효소의 수가 많은 I형에는 신율미, Beniastma 및 High Starch 등 육질이 분질인 품종이 분포 되었다. 2. 괴근의 esterase 동위리소 특성은 18가지 형으로 분류되 었고 C형은 가장 많은 22품종을 포함하고 있으며 그 다음은 B, K, A, E, 1 및 N 형 순이었다. 3. 괴근의 단백질 특성은 7가지 형으로분류되었고 I형은 36품종, IV형 27품종을 포함하였으며 다음은 II, III, Ⅶ 및 Ⅵ형 순이었다. 4. 잎과 괴근의 major esterase 동위효소와 major 단백질 분석 결과 Beniastma, Beniaka, Beniazuma 및 Benikomachi, Shiroshistma와 Shiroshastma는 유사한 품종이었고 기타는 다른 품종임을 알 수 있었다.