• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.444-451
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• 2022

Recently, long-term cultivation is becoming more common with the increase in tomato hydroponics. In hydroponics, it is very important to supply an appropriate nutrient solution considering the nutrient and moisture requirements of crops, in terms of productivity, resource use, and environmental conservation. Since seasonal environmental changes appear severely in long-term cultivation, it is so critical to manage irrigation control considering these changes. Therefore, this study was carried out to investigate the effect of irrigation volume on growth and yield in tomato long-term cultivation using coir substrate. The irrigation volume was adjusted at 4 levels (high, medium high, medium low and low) by different irrigation frequency. Irrigation scheduling (frequency) was controlled based on solar radiation which measured by radiation sensor installed outside the greenhouse and performed whenever accumulated solar radiation energy reached set value. Set value of integrated solar radiation was changed by the growing season. The results revealed that the higher irrigation volume caused the higher drainage rate, which could prevent the EC of drainage from rising excessively. As the cultivation period elapsed, the EC of the drainage increased. And the lower irrigation volume supplied, the more the increase in EC of the drainage. Plant length was shorter in the low irrigation volume treatment compared to the other treatments. But irrigation volume did not affect the number of nodes and fruit clusters. The number of fruit settings was not significantly affected by the irrigation volume in general, but high irrigation volume significantly decreased fruit setting and yield of the 12-15th cluster developed during low temperature period. Blossom-end rot occurred early with a high incidence rate in the low irrigation volume treatment group. The highest weight fruits was obtained from the high irrigation treatment group, while the medium high treatment group had the highest total yield. As a result of the experiment, it could be confirmed the effect of irrigation amount on the nutrient and moisture stabilization in the root zone and yield, in addition to the importance of proper irrigation control when cultivating tomato plants hydroponically using coir substrate. Therefore, it is necessary to continue the research on this topic, as it is judged that the precise irrigation control algorithm based on root zone-information applied to the integrated environmental control system, will contribute to the improvement of crop productivity as well as the development of hydroponics control techniques.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.63-72
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• 1994

The objective of the study is to develop weather generators for daily rainfall and small pan evaporation and to test the applicability with recorded data. Daily rainfall forecasting model(DRFM) was developed that uses a first order Markov chain to describe rainfall seque- nces and applies an incomplete Gamma function to predict the amount of precipitation. Daily evaporation forecasting model(DEFM) that adopts a normal distribution function to generate the evaporation for dry and wet days was also formulated. DRFM and DEFM were tested with twenty year weather data from eleven stations using Chi-square and Kolmogorov and Smirnov goodness of fit tests. The test results showed that the generated sequences of rainfall occurrence, amount of rainfall, and pan evaporation were statistically fit to recorded data from eleven, seven, and seven stations at the 5% level of significance. Generated rainfall data from DRFM were very close in frequency distri- bution patterns to records for stations all over the country. Pan evaporation for rainy days generated were less accurate than that for dry days. And the proposed models may be used as tools to provide many mathematical models with long-term daily rainfall and small pan evaporation data. An example is an irrigation scheduling model, which will be further detailed in the paper.

• Agribusiness and Information Management
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• v.8 no.1
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• pp.17-26
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• 2016

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world's area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On $23^{rd}$ November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called 'Andhra Pradesh Micro Irrigation Project (APMIP)', first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied ($X_1$) and fertigation cost ($X_2$) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of 'Information and Communication Technology (ICT) and its applications in irrigation water management' for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.93-100
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• 2011

Maintenance of adequate soil water potential during the period of crop growth is necessary to support optimum plant growth and yields. A better understanding of soil water movement within and below the rooting zone can facilitate optimal irrigation scheduling aimed at minimizing the adverse effects of water stress on crop growth and development and the leaching of water below the root zone which can have adverse environmental effects. The objective of this study was to evaluate the feasibility of using a portable irrigation controller with an Watermark sensor for the cultivation of drip-irrigated vegetable crops in a greenhouse. The control capability of the irrigation controller for a soil water potential of -20 kPa was evaluated under summer conditions by cultivating 45-day-old tomato plants grown in three differently textured soils (sandy loam, loam, and loamy sands). Water contents through each soil profile were continuously monitored using three Sentek probes, each consisting of three capacitance sensors at 10, 20, and 30 cm depths. Even though a repeatable cycling of soil water potential occurred for the potential treatment, the lower limit of the Watermark (about 0 kPa) obtained in this study presented a limitation of using the Watermark sensor for optimal irrigation of tomato plants where -20 kPa was used as a point for triggering irrigations. This problem might be related to the slow response time and inadequate soil-sensor interface of the Watermark sensor as compared to a porous and ceramic cup-based tensiometer with a sensitive pressure transducer. In addition, the irrigation time of 50 to 60 min at each of the irrigation operation gave a rapid drop of the potential to zero, resulting in over irrigation of tomatoes. There were differences in water content among the three different soil types under the variable rate irrigation, showing a range of water contents of 16 to 24%, 17 to 28%, and 24 to 32% for loamy sand, sandy loam, and loam soils, respectively. The greatest rate increase in water content was observed in the top of 10 cm depth of sandy loam soil within almost 60 min from the start of irrigation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4279-4295
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• 1977

Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka＋Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.179-180
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• 2001

1. 실험목적 : 벼 휴립건답직파재배시 절수재배에 알맞은 질소 수비량을 구명하고자 함. 2. 재료 및 방법 가. 공시품종 : 동진벼 나. 공시토양 : 전북통(미사질양토) 다. 물관리방법 : 3엽기부터 완전낙수기까지 5일 간격 고랑관개 라. 처리내용 -파종량(kg/ha) : 60, 100 -질소 수비량(kg/ha) : 24(50% 감비), 48(표준), 75(50% 증시), 96(100% 증시)(중략)

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.43-48
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• 1998

In order to provide basic information for the estimation of evapotranspiration for grass (Joycia Japonica), both field lysimeter experiment and model prediction were performed to estimate daily ET Various methods were used to predict daily reference crop ET and crop coefficients. Measured mean daily ET during the 1997 growing season was 4.5mm Model predicted mean daily ET during the 1997 growing season varied from 3.6 to 4.7mm depending on the prediction model Crop coefficients varied from 0.96 to 1.27 depending on the prediction model Comparison of the seven reference crop ET prediction methods used in this study shows that the Penman-Monteith method gave the smallest ET while the Hargreaves method gave the largest ET. The crop coefficient by the corrected Penman method was 1.03, which is closest to 1.0, suggesting that this method may he the best prediction method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.28 no.2
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• pp.31-41
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• 1986

Knowledge of the degree of yield reduction due to water stress at different crop growth stages in rice production is important for rational scheduling of irrigation during periods of insufficient water supply. Previous studies to determine the degree of yield reduction duo to water stress suffered from interruptions by rain during experiment. Also the findings did rot relate the degree of water stress to the soil water potential and water deficit status of rice plants. In this study, two years experiments were conducted using the high yielding rice varieties, an Indica x Japonica (Nampoong) and a Japonica variety(Choochung). These were grown in 1/200$^{\circ}$ plastic pots placed under a rainfall autosensing, sliding clear plastic roof facility to control rainfall interruptions. The results obtained were as follows. 1.The two varieties differed in the growth stage most sensitive to water stress as well as the degree of yield reductions. When rice plants were stressed to the leaf rolling score 4 and soil water potential of about - 20 bar at major crop growth stages which included heading, booting, non-effective tillering, panicle initiation and early tillering stages, the yield reductions in the Indica x Japonica variety were 58%, 34%, 27%, 22%, and 21%, respectively, whereas in the Japonica vairety they were 23%, 36%, 1%, 13% and 22%, respectively. This result show that the recommended drainage during non-effective tillering is valid only for the Japonica variety. Sufficient irrigation at booting, heading and early tillering stages are necessary for both varieties. 2.The two varieties showed visible wilting symptoms when the soil water potential dropped to about - 3.0 bar. The Japonica variety showed more leaf rolling than the Indica X Japonica. However, it had a higher retention of leaf water content and greater stomatal diffusive resistance. When the soil water potential dropped, the Japonica variety showed leaf rolling score (LRS) 1 at 0 soil-5. 0 bar and LRS 2 at 0 soil -6.0 bar while the Indica X Japonica showed LRS 1 at 0 soil - 5.5 bar and LRS 2at 0 Soil - 9.0 bar. The stomatal diffusive resistance was maximum at the second top leaf blade in both varieties at intermediate water stress of 0 soil - 4.5 bar. 3.The number of days that was required for the soil water potential to drop to-3. 0 bar and to - 20.0 bar after drainage of irrigation water from the 20cm deep silty clay loam soil in the pots were 6 and 13 days, respectively for booting stage, and 7 and 11 days, respectively for heading stage, 9 and 12 days, respectively for panicle initiation stage, and 12 and 19 days, respectively for early tillering stage. 4.Water stress during the early tillering stage recorded the longest delay in beading time, the largest reduction in panicle numbers and a substantial yield decrease of 20%. This calls for better water management to ensure the availability of water at this stage, particularly during drought periods. In addition, a reexamination of the conventional inter-drainage practice during the non-effective tillering stage is necessary for the high yielding Indica X Japonica varieties.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.131-131
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• 2017

작물의 체온인 엽온은 작물의 증발산량 또는 작물의 스트레스와 관련이 있으며, 일반적으로 일사, 풍속, 습도 등 기상조건과 잎의 크기, 형태 등 생리작용 등에 의해 지배된다. 엽온을 작물의 수분스트레스지수, 증발산량 등을 산정하기 위한 인자로 많이 활용되고 있으며, 최근 ICT 기술의 발달로 인해 열영상 카메라, 적외선 센서 등을 활용해서 실시간 측정을 하고, 정보를 작물 생육환경 제어에 활용하는 연구들이 많이 이루어지고 있다. 본 연구에서는 시설오이를 대상으로 캐노피 온도(Canopy temperature, $T_c$)와 대기온도(Air temperature, $T_a$)간의 상관관계, 또 ($T_c-T_a$)와 포화수증기압차(Vapor pressure deficit, VPD)와의 관계를 분석하였다. 대기온도와 상대습도를 이용하여 산정된 VPD가 엽온에 미치는 영향을 분석한 결과, 엽온 증가에 따라 VPD가 증가하였으며, 캐노피와 대기온도간의 차이 또한 VPD간에 음의 상관관계($R^2=0.82{\sim}0.89$)가 나타났는데, 이는 대기온도에 따른 엽온과 포화수증기압의 상승이 원인인 것으로 나타났다. ($T_c-T_a$)와 VPD값을 이용하면 작물 수분스트레스(Crop Water Stress Index, CWSI)를 산정할 수 있는 데, 결과값을 분석한 결과 $T_c$와 $T_a$의 차가 적은 경우 CWSI값이 증가함을 알 수 있었다. 향후 연구에서는 추가적으로 다양한 재배환경에서의 캐노피 온도, 포화수증기압차, 그리고 CWSI를 산정하여, 적정 생육 환경조성을 위한 지표로 활용할 계획이다.