• Journal of Climate Change Research
• /
• v.7 no.2
• /
• pp.193-203
• /
• 2016

The importance of forecasting agricultural production is receiving attention while climate change is accelerating. This study suggested three types of crop yield forecasting model for major vegetable crops by using downscaled meteorological information of main production area on farmland level, which identified as limitation from previous studies. First, this study conducted correlation analysis with seven types of farm level downscaled meteorological informations and reported crop yield of main production area. After, we selected three types of meteorological factors which showed the highest relation with each crop species and regions. Parameters were deducted from meterological factor with high correlation but crop species number was neglected. After, crop yield of each crops was estimated by using the three suggested types of models. Chinese cabbage showed high accuracy in overall, while the accuracy of daikon and onion was quiet revised by neglecting the outlier. Chili and garlic showed differences by region, but Kyungbuk chili and Chungnam, Kyungsang garlic appeared significant accuracy. We also selected key meteorological factor of each crops which has the highest relation with crop yield. If the factor had significant relation with the quantity, it explains better about the variations of key meteorological factor. This study will contribute to establishing the methodology of future studies by estimating the crop yield of different species by using farmland meterological information and relatively simplify multiple linear regression models.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.4
• /
• pp.203-214
• /
• 2017

There are two references of genetic information in Korean soybean cultivar. This study suggested that the new seven genetic information to supplement the uncertainty on prediction of potential yield of two references in soybean, and assessed the availability of two references and seven genetic information for future research. We carried out evaluate the prediction on flowering time and potential yield of the two references of genetic parameters and the new seven genetic parameters (New1~New7); the new seven genetic parameters were calibrated in Jinju, Suwon, Chuncheon during 2003-2006. As a result, in the individual and regional combination genetic parameters, the statistical indicators of the genetic parameters of the each site or the genetic parameters of the participating stations showed improved results, but did not significant. In Daegu, Miryang, and Jeonju, the predictability on flowering time of genetic parameters of New7 was not improved than that of two references. However, the genetic parameters of New7 showed improvement of predictability on potential yield. No predictability on flowering time of genetic parameters of two references as having the coefficient of determination ($R^2$) on flowering time respectively, at 0.00 and 0.01, but the predictability of genetic parameter of New7 was improved as $R^2$ on flowering time of New7 was 0.31 in Miryang. On the other hand, $R^2$ on potential yield of genetic parameters of two references were respectively 0.66 and 0.41, but no predictability on potential yield of genetic parameter of New7 as $R^2$ of New7 showed 0.00 in Jeonju. However, it is expected that the regional combination genetic parameters with the good evaluation can be utilized to predict the flowering timing and potential yields of other regions. Although it is necessary to analyze further whether or not the input data is uncertain.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.2
• /
• pp.122-133
• /
• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• Korean Journal of Medicinal Crop Science
• /
• v.23 no.6
• /
• pp.480-488
• /
• 2015

Background : In order to determine the effects of planting methods on root growth of ginseng varieties, two different methods, direct seed sowing and transplanting were compared in terms of their effects on different root growth characteristics. Methods and Results : Higher fresh root weight was observed in ginseng grown by direct seed sowing. Direct seed sowing of three cultivars (Sunhyang, Chungsun and K-1) resulted in higher yield, whereas no difference was observed in the yield of one cultivar (Chungsun). Gumpoong was highly tolerant to physiological stress, as it showed fewer symptoms of rusty and rough skin root diseases in both direct seed sowing and transplanting. The average main root length per total root length of ginseng grown by direct seed sowing was 33.6%, whereas that of ginseng grown by the average of those by transplanting was 22.4%. Other root growth characteristics, including root length, main root diameter, and number of side roots, improved when the direct seed sowing method was used. Conclusions : To our knowledge, this is the first study reporting the differences in root growth parameters of ginseng varieties grown by direct seed sowing or transplanting at the same planting density. Because of the advantages of direct sowing during ginseng planting, developing new varieties and improving cultivation methods are imperative.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.18-18
• /
• 2022

Barley has been used for the production of malt in the brewing industry. Malting is the process of preparing barley through partial germination. Malt extract is the most important quality parameter for malt quality. The grain and malt quality parameters of ten Korean malting barley varieties were studied. Malts was prepared using Phoeix automated micro malting system(Phoenix Bio, Australia). Quality analysis of Barley and malt was determined according to European brewery convention(EBC, 1998) and American society of brewing chemists(ASBC, 1997) method. And the hordeins of barley and malt were extracted with 50% isopropyl alcohol(IPA, 2-propanol) of 1% dithiothreitol(DTT). The analysis of hordeins was carried out by ultra-performance liquid chromatography(UPLC). The mean values of 1000-grains weight, assortment rate, protein content, starch content, beta-glucan content, husk rate, germination energy, germination capacity and water sensitivity of grain were 45.8g, 86.8%, 11.9%, 58.0%, 3.8%, 14.0%, 96.2%, 97.2%, 10.0%, respectively. The mean values of protein content, friability, diastatic power, extract, soluble protein, Kolbach index, beta-glucan of malt and wort were 11.3%, 87.6%, 201WK(Windish Kolbach), 79.3%, 4.6%, 41%, 85mg/L, respectively. UPLC analysis of grain and malt hordeins revealed that the amount of hordeins significantly degraded during malting. Also, we could successfully be used to compare hordein polypeptide patterns with malt quality.

• Korean Journal of Soil Science and Fertilizer
• /
• v.47 no.2
• /
• pp.85-91
• /
• 2014

Ground-based polarimetric scatterometers have been effective tools to monitor the growth of crop with multi-polarization and frequencies and various incident angles. An important advantage of these systems that can be exploited is temporal observation of a specific crop target. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. We analyzed the relationships between L-, C- and X-band signatures, biophysical measurements over the whole corn growth period. The Vertical transmit and Vertical receive polarization (VV) backscattering coefficients for all bands were greater than those of the Horizontal transmit and Horizontal receive polarization (HH) until early-July, and then thereafter HH-polarization was greater than VV-polarization or Horizontal transmit and Vertical receive polarization (HV) until the harvesting stage (Day Of Year, DOY 240). The results of correlation analysis between the backscattering coefficients for all bands and corn growth data showed that L-band HH-polarization (L-HH) was the most suited for monitoring the fresh weight ($r=0.95^{***}$), dry weight ($r=0.95^{***}$), leaf area index ($r=0.86^{**}$), and vegetation water content ($r=0.93^{***}$). Retrieval equations were developed for estimating corn growth parameters using L-HH. The results indicated that L-HH could be used for estimating the vegetation biophysical parameters considered here with high accuracy. Those results can be useful in determining frequency and polarization of satellite Synthetic Aperture Radar stem and in designing a future ground-based microwave system for a long-term monitoring of corn.

• Journal of Forest and Environmental Science
• /
• v.38 no.2
• /
• pp.122-127
• /
• 2022

Agroforestry in terms of intercropping cow pea as summer forage with Grewia tenax was undertaken under sub -irrigation system in two consecutive seasons of 2017 and 2018 in saline soil of Khartoum State of Sudan. The aims were to find out suitable agro forestry system for saline soils as well as to investigate effect of tree spacing on field summer forage crop under semi -irrigation system. Therefore G. tenax trees that spaced at 4×4 m were used as main factor versus cow pea crop that incorporated at 25×50 cm intervals by using completely randomized block design with 3 replications. Trees and crop parameters were determined in terms of plant growth and yield. In addition to land equivalent ratio and soil chemical and physical properties at different layers were determined. The results revealed that, soil parameters in terms of CaCo₃, SAR, ESP, pH paste and EC ds/m were increased with increasing soil depths. Meanwhile tree growth did not show any significant differences in the first season in 2017. Whereas in the second season in 2018 tree growth namely; tree height, tree collar and canopy diameters were higher under intercropping than in sole trees. Cow pea plant height recorded significant differences under sole crop in the first season in 2017. Unlike the forage fresh yield that was significant under the inter cropped plots. Tree fruit yield was higher under sole trees and land equivalent ratio was more advantageous under GS2 (1.5 m) which amounted to 4. Therefore it is possible to introduce this agroforestry system under saline soils to provide summer forage of highly nutritive value to feed animals and to increase farmers' income as far as to halt desertification and to sequester carbon.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.17-28
• /
• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1993.10a
• /
• pp.1273-1281
• /
• 1993

Estimation of daily and seasonal evaportranspiration is essential for water resource planning irrigation feasibility study, and real-time irrigation water management . This paper is to evaluate the applicability of neural networks to the estimation of evapotranspiration . A neural network was developed to forecast daily evapotranspiration of the rice crop. It is a three-layer network with input, hidden , and output layers. Back-propagation algorithm with delta learning rule was used to train the neural network. Training neural network wasconducted usign daily actural evapotranspiration of rice crop and daily climatic data such as mean temperature, sunshine hours, solar radiation, relative humidity , and pan evaporation . During the training, neural network parameters were calibrated. The trained network was applied to a set of field data not used in the training . The created response of the neural network was in good agreement with desired values. Evaluating the neural networ performance indicates that neural network may be applied to the estimation of evapotranspiration of the rice crop.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.1 no.1
• /
• pp.41-45
• /
• 2000

The effect of topical application with hydrocortisone on economic parameters was analysed following treatment of last larval stadium. The treated larvae showed a significant increase in larval weight at higher concentrations along with other enhanced larval, cocoon and adult parameters. This suggests that hydrocortisone can be used effectively for commercial silkworm rearing. The larvas period was significantly increased in all the treated groups with increased female cocoon weights, its shell weights and male cocoon shell weight at 20$\mu\textrm{g}$/ml treated group. Filament length, weight and denier were increased significantly in all the treated groups. Moth emergence percentage, length of the ovariole, eggs per ovariole, fecundity and rind hatching percentage were unaffected when compared with that of the carrier control group. This suggests that hydrocortisone in addition to affecting larval growths also affect silk crop.