1,138 research outputs found

    Decision support for optimised irrigation scheduling

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    The system, developed under the FLOW-AID (an FP6 project), is a farm level water management system of special value in situations where the water availability and quality is limited. This market-ready precision irrigation management system features new models, hardware and software. The hardware platform delivers a maintenance-free low cost dielectric tensiometer and several low-end irrigation or fertigation controllers for serving different situations. The software includes a complete, web based, Decision Support System (DSS) that consists of an expert planner for farm zoning (MOPECO) and a universal irrigation scheduler, based on crop-water stress models (UNIPI) and water and nutrient uptake calculations. The system, designed also to service greenhouse fertigation and hydroponics, is scalable from one to many zones. It consists of 1) a data gathering tool which uploads agronomic data, from monitored crops around the world, to a central web Data Base (DB), and 2) a web based Decision Support System (DSS). The DSS processes intelligently the data of the crop using Crop Response Models, Nutrient Uptake Models and Water Uptake Models. The central system returns over Internet to the low-end controller a command file containing water scheduling and nutrient supply guideline

    κ°œλ³„ 이온 및 μž‘λ¬Ό μƒμœ‘ μ„Όμ‹± 기반의 μ •λ°€ 수경재배 μ–‘μ•‘ 관리 μ‹œμŠ€ν…œ

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    ν•™μœ„λ…Όλ¬Έ (박사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 농업생λͺ…κ³Όν•™λŒ€ν•™ λ°”μ΄μ˜€μ‹œμŠ€ν…œΒ·μ†Œμž¬ν•™λΆ€(λ°”μ΄μ˜€μ‹œμŠ€ν…œκ³΅ν•™), 2020. 8. 김학진.In current closed hydroponics, the nutrient solution monitoring and replenishment are conducted based on the electrical conductivity (EC) and pH, and the fertigation is carried out with the constant time without considering the plant status. However, the EC-based management is unable to detect the dynamic changes in the individual nutrient ion concentrations so the ion imbalance occurs during the iterative replenishment, thereby leading to the frequent discard of the nutrient solution. The constant time-based fertigation inevitably induces over- or under-supply of the nutrient solution for the growing plants. The approaches are two of the main causes of decreasing water and nutrient use efficiencies in closed hydroponics. Regarding the issues, the precision nutrient solution management that variably controls the fertigation volume and corrects the deficient nutrient ions individually would allow both improved efficiencies of fertilizer and water use and increased lifespan of the nutrient solution. The objectives of this study were to establish the precision nutrient solution management system that can automatically and variably control the fertigation volume based on the plant-growth information and supply the individual nutrient fertilizers in appropriate amounts to reach the optimal compositions as nutrient solutions for growing plants. To achieve the goal, the sensing technologies for the varying requirements of water and nutrients were investigated and validated. Firstly, an on-the-go monitoring system was constructed to monitor the lettuces grown under the closed hydroponics based on the nutrient film technique for the entire bed. The region of the lettuces was segmented by the excess green (ExG) and Otsu method to obtain the canopy cover (CC). The feasibility of the image processing for assessing the canopy (CC) was validated by comparing the computed CC values with the manually analyzed CC values. From the validation, it was confirmed the image monitoring and processing for the CC measurements were feasible for the lettuces before harvest. Then, a transpiration rate model using the modified Penman-Monteith equation was fitted based on the obtained CC, radiation, air temperature, and relative humidity to estimate the water need of the growing lettuces. Regarding the individual ion concentration measurements, two-point normalization, artificial neural network, and a hybrid signal processing consisting of the two-point normalization and artificial neural network were compared to select an effective method for the ion-selective electrodes (ISEs) application in continuous and autonomous monitoring of ions in hydroponic solutions. The hybrid signal processing showed the most accuracy in sample measurements, but the vulnerability to the sensor malfunction made the two-point normalization method with the most precision would be appropriate for the long-term monitoring of the nutrient solution. In order to determine the optimal injection amounts of the fertilizer salts and water for the given target individual ion concentrations, a decision tree-based dosing algorithm was designed. The feasibility of the dosing algorithm was validated with the stepwise and varying target focusing replenishments. From the results, the ion-specific replenishments formulated the compositions of the nutrient solution successfully according to the given target values. Finally, the proposed sensing and control techniques were integrated to implement the precision nutrient solution management, and the performance was verified by a closed lettuce cultivation test. From the application test, the fertigation volume was reduced by 57.4% and the growth of the lettuces was promoted in comparison with the constant timer-based fertigation strategy. Furthermore, the system successfully maintained the nutrient balance in the recycled solution during the cultivation with the coefficients of variance of 4.9%, 1.4%, 3.2%, 5.2%, and 14.9%, which were generally less than the EC-based replenishment with the CVs of 6.9%, 4.9%, 23.7%, 8.6%, and 8.3% for the NO3, K, Ca, Mg, and P concentrations, respectively. These results implied the developed precision nutrient solution management system could provide more efficient supply and management of water and nutrients than the conventional methods, thereby allowing more improved water and nutrient use efficiencies and crop productivity.ν˜„μž¬μ˜ μˆœν™˜μ‹ 수경재배 μ‹œμŠ€ν…œμ—μ„œ μ–‘μ•‘μ˜ 뢄석과 보좩은 전기전도도 (EC, electrical conductivity) 및 pHλ₯Ό 기반으둜 μˆ˜ν–‰λ˜κ³  있으며, μ–‘μ•‘μ˜ 곡급은 μž‘λ¬Όμ˜ μƒμœ‘ μƒνƒœμ— λŒ€ν•œ κ³ λ € 없이 항상 μΌμ •ν•œ μ‹œκ°„ λ™μ•ˆ νŽŒν”„κ°€ λ™μž‘ν•˜μ—¬ κ³΅κΈ‰λ˜λŠ” ν˜•νƒœμ΄λ‹€. κ·ΈλŸ¬λ‚˜ EC 기반의 μ–‘μ•‘ κ΄€λ¦¬λŠ” κ°œλ³„ 이온 λ†λ„μ˜ 동적인 λ³€ν™”λ₯Ό 감지할 수 μ—†μ–΄ λ°˜λ³΅λ˜λŠ” 보좩 쀑 λΆˆκ· ν˜•μ΄ λ°œμƒν•˜κ²Œ λ˜μ–΄ μ–‘μ•‘μ˜ 폐기λ₯Ό μ•ΌκΈ°ν•˜λ©°, κ³ μ •λœ μ‹œκ°„ λ™μ•ˆμ˜ μ–‘μ•‘ 곡급은 μž‘λ¬Όμ— λŒ€ν•΄ κ³Όμž‰ λ˜λŠ” λΆˆμΆ©λΆ„ν•œ λ¬Ό κ³΅κΈ‰μœΌλ‘œ 이어져 λ¬Ό μ‚¬μš© 효율의 μ €ν•˜λ₯Ό μΌμœΌν‚¨λ‹€. μ΄λŸ¬ν•œ λ¬Έμ œλ“€μ— λŒ€ν•΄, κ°œλ³„ 이온 농도에 λŒ€ν•΄ λΆ€μ‘±ν•œ μ„±λΆ„λ§Œμ„ μ„ νƒμ μœΌλ‘œ λ³΄μΆ©ν•˜κ³ , μž‘λ¬Όμ˜ μƒμœ‘ 정도에 κΈ°λ°˜ν•˜μ—¬ ν•„μš”ν•œ μˆ˜μ€€μ— 맞게 양앑을 κ³΅κΈ‰ν•˜λŠ” μ •λ°€ 농업에 κΈ°λ°˜ν•œ μ–‘μ•‘ 관리λ₯Ό μˆ˜ν–‰ν•˜λ©΄ λ¬Όκ³Ό λΉ„λ£Œ μ‚¬μš© 효율의 ν–₯상과 μ–‘μ•‘μ˜ μž¬μ‚¬μš© κΈ°κ°„ 증진을 κΈ°λŒ€ν•  수 μžˆλ‹€. λ³Έ μ—°κ΅¬μ˜ λͺ©μ μ€ μžλ™μœΌλ‘œ, 그리고 κ°€λ³€μ μœΌλ‘œ μž‘λ¬Ό μƒμœ‘ 정보에 κΈ°λ°˜ν•˜μ—¬ μ–‘μ•‘ κ³΅κΈ‰λŸ‰μ„ μ œμ–΄ν•˜κ³ , μž‘λ¬Ό 생μž₯에 μ ν•©ν•œ 쑰성에 맞게 ν˜„μž¬ μ–‘μ•‘μ˜ 이온 농도 센싱에 κΈ°λ°˜ν•˜μ—¬ μ μ ˆν•œ μˆ˜μ€€λ§ŒνΌμ˜ λ¬Όκ³Ό κ°œλ³„ μ–‘λΆ„ λΉ„λ£Œλ₯Ό 보좩할 수 μžˆλŠ” μ •λ°€ 수경재배 μ–‘μ•‘ 관리 μ‹œμŠ€ν…œμ„ κ°œλ°œν•˜λŠ” 것이닀. ν•΄λ‹Ή λͺ©ν‘œλ₯Ό λ‹¬μ„±ν•˜κΈ° μœ„ν•΄, λ³€μ΄ν•˜λŠ” λ¬Όκ³Ό μ–‘λΆ„ μš”κ΅¬λŸ‰μ„ μΈ‘μ •ν•  수 μžˆλŠ” λͺ¨λ‹ˆν„°λ§ κΈ°μˆ λ“€μ„ λΆ„μ„ν•˜κ³  각 λͺ¨λ‹ˆν„°λ§ κΈ°μˆ λ“€μ— λŒ€ν•œ 검증을 μˆ˜ν–‰ν•˜μ˜€λ‹€. λ¨Όμ €, μž‘λ¬Όμ˜ λ¬Ό μš”κ΅¬λŸ‰μ„ μ‹€μ‹œκ°„μœΌλ‘œ κ΄€μΈ‘ν•  수 μžˆλŠ” μ˜μƒ 기반 μΈ‘μ • κΈ°μˆ μ„ μ‘°μ‚¬ν•˜μ˜€λ‹€. μ˜μƒ 기반 뢄석 ν™œμš©μ„ μœ„ν•΄ 박막경 기반의 μˆœν™˜μ‹ 수경재배 ν™˜κ²½μ—μ„œ μžλΌλŠ” μƒμΆ”μ˜ 이미지듀을 전체 λ² λ“œμ— λŒ€ν•΄ μˆ˜μ§‘ν•  수 μžˆλŠ” μ˜μƒ λͺ¨λ‹ˆν„°λ§ μ‹œμŠ€ν…œμ„ κ΅¬μ„±ν•˜μ˜€κ³ , μˆ˜μ§‘ν•œ μ˜μƒ 쀑 상좔 λΆ€λΆ„λ§Œμ„ excess green (ExG)κ³Ό Otsu 방법을 톡해 λΆ„λ¦¬ν•˜μ—¬ νˆ¬μ˜μž‘λ¬Όλ©΄μ  (CC, canopy cover)을 νšλ“ν•˜μ˜€λ‹€. μ˜μƒ 처리 기술의 μ μš©μ„± 평가λ₯Ό μœ„ν•΄ 직접 λΆ„μ„ν•œ νˆ¬μ˜μž‘λ¬Όλ©΄μ  κ°’κ³Ό 이λ₯Ό λΉ„κ΅ν•˜μ˜€λ‹€. 비ꡐ 검증 κ²°κ³Όμ—μ„œ νˆ¬μ˜μž‘λ¬Όλ©΄μ  츑정을 μœ„ν•œ μ˜μƒ μˆ˜μ§‘ 및 뢄석이 μˆ˜ν™• μ „κΉŒμ§€μ˜ 상좔에 λŒ€ν•΄ 적용 κ°€λŠ₯함을 ν™•μΈν•˜μ˜€λ‹€. 이후 μˆ˜μ§‘ν•œ νˆ¬μ˜μž‘λ¬Όλ©΄μ κ³Ό 기온, μƒλŒ€μŠ΅λ„, μΌμ‚¬λŸ‰μ„ 기반으둜 μƒμœ‘ 쀑인 상좔듀이 μš”κ΅¬ν•˜λŠ” 물의 양을 μ˜ˆμΈ‘ν•˜κΈ° μœ„ν•΄ Penman-Monteith 방정식 기반의 μ¦μ‚°λŸ‰ 예츑 λͺ¨λΈμ„ κ΅¬μ„±ν•˜μ˜€μœΌλ©° μ‹€μ œ μ¦μ‚°λŸ‰κ³Ό λΉ„κ΅ν•˜μ˜€μ„ λ•Œ 높은 μΌμΉ˜λ„λ₯Ό ν™•μΈν•˜μ˜€λ‹€. κ°œλ³„ 이온 농도 μΈ‘μ •κ³Ό κ΄€λ ¨ν•˜μ—¬μ„œλŠ”, μ΄μ˜¨μ„ νƒμ„±μ „κ·Ή (ISE, ion-selective electrode)λ₯Ό μ΄μš©ν•œ 수경재배 μ–‘μ•‘ λ‚΄ 이온의 연속적이고 자율적인 λͺ¨λ‹ˆν„°λ§ μˆ˜ν–‰μ„ μœ„ν•΄ 2점 μ •κ·œν™”, 인곡신경망, 그리고 이 λ‘˜μ„ λ³΅ν•©μ μœΌλ‘œ κ΅¬μ„±ν•œ ν•˜μ΄λΈŒλ¦¬λ“œ μ‹ ν˜Έ 처리 κΈ°λ²•μ˜ μ„±λŠ₯을 λΉ„κ΅ν•˜μ—¬ λΆ„μ„ν•˜μ˜€λ‹€. 뢄석 κ²°κ³Ό, ν•˜μ΄λΈŒλ¦¬λ“œ μ‹ ν˜Έ 처리 방식이 κ°€μž₯ 높은 정확성을 λ³΄μ˜€μœΌλ‚˜, μ„Όμ„œ κ³ μž₯에 μ·¨μ•½ν•œ 신경망 ꡬ쑰둜 인해 μž₯κΈ°κ°„ λͺ¨λ‹ˆν„°λ§ μ•ˆμ •μ„±μ— μžˆμ–΄μ„œλŠ” κ°€μž₯ 높은 정밀도λ₯Ό 가진 2점 μ •κ·œν™” 방식을 μ„Όμ„œ μ–΄λ ˆμ΄μ— μ μš©ν•˜λŠ” 것이 적합할 κ²ƒμœΌλ‘œ νŒλ‹¨ν•˜μ˜€λ‹€. λ˜ν•œ, 주어진 κ°œλ³„ 이온 농도 λͺ©ν‘œκ°’에 λ§žλŠ” λΉ„λ£Œ μ—Ό 및 물의 졜적 μ£Όμž…λŸ‰μ„ κ²°μ •ν•˜κΈ° μœ„ν•΄ μ˜μ‚¬κ²°μ •νŠΈλ¦¬ ꡬ쑰의 λΉ„λ£Œ νˆ¬μž… μ•Œκ³ λ¦¬μ¦˜μ„ μ œμ‹œν•˜μ˜€λ‹€. μ œμ‹œν•œ λΉ„λ£Œ νˆ¬μž… μ•Œκ³ λ¦¬μ¦˜μ˜ νš¨κ³Όμ— λŒ€ν•΄μ„œλŠ” 순차적인 λͺ©ν‘œμ— λŒ€ν•œ 보좩 및 νŠΉμ • 성뢄에 λŒ€ν•΄ 집쀑적인 λ³€ν™”λ₯Ό λΆ€μ—¬ν•œ 보좩 μˆ˜ν–‰ μ‹€ν—˜μ„ 톡해 κ²€μ¦ν•˜μ˜€μœΌλ©°, κ·Έ κ²°κ³Ό μ œμ‹œν•œ μ•Œκ³ λ¦¬μ¦˜μ€ 주어진 λͺ©ν‘œκ°’듀에 따라 μ„±κ³΅μ μœΌλ‘œ 양앑을 μ‘°μ„±ν•˜μ˜€μŒμ„ ν™•μΈν•˜μ˜€λ‹€. λ§ˆμ§€λ§‰μœΌλ‘œ, μ œμ‹œλ˜μ—ˆλ˜ μ„Όμ‹± 및 μ œμ–΄ κΈ°μˆ λ“€μ„ ν†΅ν•©ν•˜μ—¬ NFT 기반의 μˆœν™˜μ‹ 수경재배 λ°°λ“œμ— 상좔 재배λ₯Ό μˆ˜ν–‰ν•˜μ—¬ μ‹€μ¦ν•˜μ˜€λ‹€. 싀증 μ‹€ν—˜μ—μ„œ, μ’…λž˜μ˜ κ³ μ • μ‹œκ°„ μ–‘μ•‘ 곡급 λŒ€λΉ„ 57.4%의 μ–‘μ•‘ κ³΅κΈ‰λŸ‰ κ°μ†Œμ™€ 상좔 μƒμœ‘μ˜ 촉진을 ν™•μΈν•˜μ˜€λ‹€. λ™μ‹œμ—, 개발 μ‹œμŠ€ν…œμ€ NO3, K, Ca, Mg, 그리고 P에 λŒ€ν•΄ 각각 4.9%, 1.4%, 3.2%, 5.2%, 그리고 14.9% μˆ˜μ€€μ˜ λ³€λ™κ³„μˆ˜ μˆ˜μ€€μ„ 보여 EC기반 보좩 λ°©μ‹μ—μ„œ λ‚˜νƒ€λ‚œ λ³€λ™κ³„μˆ˜ 6.9%, 4.9%, 23.7%, 8.6%, 그리고 8.3%보닀 λŒ€μ²΄μ μœΌλ‘œ μš°μˆ˜ν•œ 이온 κ· ν˜• μœ μ§€ μ„±λŠ₯을 λ³΄μ˜€λ‹€. μ΄λŸ¬ν•œ 결과듀을 톡해 개발 μ •λ°€ κ΄€λΉ„ μ‹œμŠ€ν…œμ΄ 기쑴보닀 효율적인 μ–‘μ•‘μ˜ 곡급과 관리λ₯Ό 톡해 μ–‘μ•‘ 이용 νš¨μœ¨μ„±κ³Ό μƒμ‚°μ„±μ˜ 증진에 κΈ°μ—¬ν•  수 μžˆμ„ κ²ƒμœΌλ‘œ νŒλ‹¨λ˜μ—ˆλ‹€.CHAPTER 1. INTRODUCTION 1 BACKGROUND 1 Nutrient Imbalance 2 Fertigation Scheduling 3 OBJECTIVES 7 ORGANIZATION OF THE DISSERTATION 8 CHAPTER 2. LITERATURE REVIEW 10 VARIABILITY OF NUTRIENT SOLUTIONS IN HYDROPONICS 10 LIMITATIONS OF CURRENT NUTRIENT SOLUTION MANAGEMENT IN CLOSED HYDROPONIC SYSTEM 11 ION-SPECIFIC NUTRIENT MONITORING AND MANAGEMENT IN CLOSED HYDROPONICS 13 REMOTE SENSING TECHNIQUES FOR PLANT MONITORING 17 FERTIGATION CONTROL METHODS BASED ON REMOTE SENSING 19 CHAPTER 3. ON-THE-GO CROP MONITORING SYSTEM FOR ESTIMATION OF THE CROP WATER NEED 21 ABSTRACT 21 INTRODUCTION 21 MATERIALS AND METHODS 23 Hydroponic Growth Chamber 23 Construction of an On-the-go Crop Monitoring System 25 Image Processing for Canopy Cover Estimation 29 Evaluation of the CC Calculation Performance 32 Estimation Model for Transpiration Rate 32 Determination of the Parameters of the Transpiration Rate Model 33 RESULTS AND DISCUSSION 35 Performance of the CC Measurement by the Image Monitoring System 35 Plant Growth Monitoring in Closed Hydroponics 39 Evaluation of the Crop Water Need Estimation 42 CONCLUSIONS 46 CHAPTER 4. HYBRID SIGNAL-PROCESSING METHOD BASED ON NEURAL NETWORK FOR PREDICTION OF NO3, K, CA, AND MG IONS IN HYDROPONIC SOLUTIONS USING AN ARRAY OF ION-SELECTIVE ELECTRODES 48 ABSTRACT 48 INTRODUCTION 49 MATERIALS AND METHODS 52 Preparation of the Sensor Array 52 Construction and Evaluation of Data-Processing Methods 53 Preparation of Samples 57 Procedure of Sample Measurements 59 RESULTS AND DISCUSSION 63 Determination of the Artificial Neural Network (ANN) Structure 63 Evaluation of the Processing Methods in Training Samples 64 Application of the Processing Methods in Real Hydroponic Samples 67 CONCLUSIONS 72 CHAPTER 5. DECISION TREE-BASED ION-SPECIFIC NUTRIENT MANAGEMENT ALGORITHM FOR CLOSED HYDROPONICS 74 ABSTRACT 74 INTRODUCTION 75 MATERIALS AND METHODS 77 Decision Tree-based Dosing Algorithm 77 Development of an Ion-Specific Nutrient Management System 82 Implementation of Ion-Specific Nutrient Management with Closed-Loop Control 87 System Validation Tests 89 RESULTS AND DISCUSSION 91 Five-stepwise Replenishment Test 91 Replenishment Test Focused on The Ca 97 CONCLUSIONS 99 CHAPTER 6. ION-SPECIFIC AND CROP GROWTH SENSING BASED NUTRIENT SOLUTION MANAGEMENT SYSTEM FOR CLOSED HYDROPONICS 101 ABSTRACT 101 INTRODUCTION 102 MATERIALS AND METHODS 103 System Integration 103 Implementation of the Precision Nutrient Solution Management System 106 Application of the Precision Nutrient Solution Management System to Closed Lettuce Soilless Cultivation 112 RESULTS AND DISCUSSION 113 Evaluation of the Plant Growth-based Fertigation in the Closed Lettuce Cultivation 113 Evaluation of the Ion-Specific Management in the Closed Lettuce Cultivation 118 CONCLUSIONS 128 CHAPTER 7. CONCLUSIONS 130 CONCLUSIONS OF THE STUDY 130 SUGGESTIONS FOR FUTURE STUDY 134 LIST OF REFERENCES 136 APPENDIX 146 A1. Python Code for Controlling the Image Monitoring and CC Calculation 146 A2. Ion Concentrations of the Solutions used in Chapter 4 (Unit: mgβˆ™Lβˆ’1) 149 A3. Block Diagrams of the LabVIEW Program used in Chapter 4 150 A4. Ion Concentrations of the Solutions used in Chapters 5 and 6 (Unit: mgβˆ™Lβˆ’1) 154 A5. Block Diagrams of the LabVIEW Program used in the Chapters 5 and 6 155 ABSTRACT IN KOREAN 160Docto

    HYDROPONIC DEVICES FOR GREEN FODDER PRODUCTION: A REVIEW

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    In traditional farming, plants require a lot of space (growing area), they consume a large amount of water, absorb a small percentage of nutrients in soil and are completely dependent on meteorological conditions. Therefore, growing crops in this way entails high costs and a high risk of invested funds. One of the measures to reduce these factors is the use of hydroponics.In the study six types of hydroponic systems (HS) plant constructions based on plant nutrient supply technology were reviewed: ebb and flow HS; nutrient film technique (NFT) HS; aeroponics; deep water culture HS; β€œwick” HS and drip-irrigation HS. In addition, a review of the structural design of the hydroponic systems identified their advantages and disadvantages in green fodder production.The most promising technology for the cultivation of green fodder is the NFT HS. This cultivation technology is appreciated in feed production for its highly utilized growing room volume and closed-loop irrigation solution to plants, which allows it to be easily automated based on solution parameters. Seven farms already have this technology in place in Lithuania. In order to optimize hydroponic fodder cultivation technology, it is expedient to improve NFT equipment and process control systems

    Automated System that Monitors and Controls the pH and Electrical Conductivity of a Closed-Hydroponic Setup

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    The Automated Closed Hydroponics System relates to a system that monitors the pH and electrical conductivity (EC) of the nutrient solution. It is constructed to modify and optimize the conventional hydroponic system as determined through its specific operational requirements to utilize the system safely and profitably. The modules are electronically integrated into the system that continuously monitors the pH level and the EC level of the nutrient solution and automatically adjusts its content to the proper range suitable for the plant used. The developed system lessens human involvement, and in turn, eliminates human error while keeping expenses at a minimum and ensuring yield at maximum. This article discusses the operation of the system which consists of the reservoirs for the dispensing of acid, base, nutrient solution, and water, with its necessary valves, motors, hose, and flow regulators; level sensors installed to the reservoirs to monitor the refilling requirement and operational conditions; pH monitoring and control; electrical conductivity (EC) monitoring and control; and, the nutrient uptake analysis to illustrate the plant nutritional status verifying that the plants were taking up the nutrient balance they require when the pH and EC are on their respective exact levels. The automation in the hydroponic system results in a more balanced culture, creating healthier and more homogeneous leaves

    Wireless ICT monitoring for hydroponic agriculture

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    It is becoming increasingly evident that agriculture is playing a pivotal role in the socio-economic development of South Africa. The agricultural sector is important because it contributes approximately 2% to the gross domestic product of the country. However, many factors impact on the sustainability of traditional agriculture in South Africa. Unpredictable climatic conditions, land degradation and a lack of information and awareness of innovative farming solutions are among the factors plaguing the South African agricultural landscape. Various farming techniques have been looked at in order to mitigate these challenges. Among these interventions are the introduction of organic agriculture, greenhouse agriculture and hydroponic agriculture, which is the focus area of this study. Hydroponic agriculture is a method of precision agriculture where plants are grown in a mineral nutrient solution instead labour- intensive activity that requires an incessant monitoring of the farm environment in order to ensure a successful harvest. Hydroponic agriculture, however, presents a number of challenges that can be mitigated by leveraging the recent mobile Information and Communication Technologies (ICTs) breakthroughs. This dissertation reports on the development of a wireless ICT monitoring application for hydroponic agriculture: HydroWatcher mobile app. HydroWatcher is a complex system that is composed of several interlacing parts and this study will be focusing on the development of the mobile app, the front-end of the system. This focus is motivated by the fact that in such systems the front-end, being the part that the users interact with, is critical for the acceptance of the system. However, in order to design and develop any part of HydroWatcher, it is crucial to understand the context of hydroponic agriculture in South Africa. Therefore, complementary objectives of this study are to identify the critical factors that impact hydroponic agriculture as well as the challenges faced by hydroponic farmers in South Africa. Thus, it leads to the elicitation of the requirements for the design and development of HydroWatcher. This study followed a mixed methods approach, including interviews, observations, exploration of hydroponic farming, to collect the data, which will best enable the researcher to understand the activities relating to hydroponic agriculture. A qualitative content analysis was followed to analyse the data and to constitute the requirements for the system and later to assert their applicability to the mobile app. HydroWatcher proposes to couple recent advances in mobile technology development, like the Android platform, with the contemporary advances in electronics necessary for the creation of wireless sensor nodes, as well as Human Computer interaction guidelines tailored for developing countries, in order to boost the user experience

    A lunar base reference mission for the phased implementation of bioregenerative life support system components

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    Previous design efforts of a cost effective and reliable regenerative life support system (RLSS) provided the foundation for the characterization of organisms or 'biological processors' in engineering terms and a methodology was developed for their integration into an engineered ecological LSS in order to minimize the mass flow imbalances between consumers and producers. These techniques for the design and the evaluation of bioregenerative LSS have now been integrated into a lunar base reference mission, emphasizing the phased implementation of components of such a BLSS. In parallel, a designers handbook was compiled from knowledge and experience gained during past design projects to aid in the design and planning of future space missions requiring advanced RLSS technologies. The lunar base reference mission addresses in particular the phased implementation and integration of BLS parts and includes the resulting infrastructure burdens and needs such as mass, power, volume, and structural requirements of the LSS. Also, operational aspects such as manpower requirements and the possible need and application of 'robotics' were addressed

    Prospects in Agricultural Engineering in the Information Age - Technological Development for the Producer and the Consumer

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    Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is an Invited article from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 1 (1999): N. Sigrimis, Y. Hashimoto, A. Munack and J. De Baerdemaker. Prospects in Agricultural Engineering in the Information Age - Technological Development for the Producer and the Consumer

    Decision-tree-based ion-specific dosing algorithm for enhancing closed hydroponic efficiency and reducing carbon emissions

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    The maintenance of ion balance in closed hydroponic solutions is essential to improve the crop quality and recycling efficiency of nutrient solutions. However, the absence of robust ion sensors for key ions such as P and Mg and the coupling of ions in fertilizer salts render it difficult to effectively manage ion-specific nutrient solutions. Although ion-specific dosing algorithms have been established, their effectiveness has been inadequately explored. In this study, a decision-tree-based dosing algorithm was developed to calculate the optimal volumes of individual nutrient stock solutions to be supplied for five major nutrient ions, i.e., NO3, K, Ca, P, and Mg, based on the concentrations of NO3, K, and Ca and remaining volume of the recycled nutrient solution. In the performance assessment based on five nutrient solution samples encompassing the typical concentration ranges for leafy vegetable cultivation, the ion-selective electrode array demonstrated feasible accuracies, with root mean square errors of 29.5, 10.1, and 6.1 mgΒ·L-1 for NO3, K, and Ca, respectively. In a five-step replenishment test involving varying target concentrations and nutrient solution volumes, the system formulated nutrient solutions according to the specified targets, exhibiting average relative errors of 10.6 Β± 8.0%, 7.9 Β± 2.1%, 8.0 Β± 11.0%, and 4.2 Β± 3.7% for the Ca, K, and NO3 concentrations and volume of the nutrient solution, respectively. Furthermore, the decision tree method helped reduce the total fertilizer injections and carbon emissions by 12.8% and 20.6% in the stepwise test, respectively. The findings demonstrate that the decision-tree-based dosing algorithm not only enables more efficient reuse of nutrient solution compared to the existing simplex method but also confirms the potential for reducing carbon emissions, indicating the possibility of sustainable agricultural development

    Designing, fabrication and evaluation of a small-scale vertical hydroponic system to produce leafy vegetables

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    The agricultural productivity in Newfoundland and Labrador (NL) faces many challenges, including severe weather conditions, short growing seasons, and poor soil conditions. To address these challenges in NL, researchers should explore innovative methods like hydroponic farming to improve local food production. This study was conducted to design, fabricate, and evaluate a household hydroponic system capable of producing year-round leafy vegetables. A vertical hydroponic system was designed, fabricated and tested along with two other systems including 1) a vertical drip hydroponic system (G-DNA), 2) a vertical wick hydroponic system (C-Tree), and 3) a horizontal deep water culture (DWC) system as the control, under two growth conditions (a grow tent experiment and an experiment without a grow tent). The growth of spinach, water use efficiency (WUE) and nitrogen use efficiency (NUE) in three systems were tested. Results showed that the G-DNA system produced significantly higher spinach yield and outperformed the C-Tree hydroponic system. While G-DNA and C-Tree hydroponic systems had no significant effect on WUE, compared to the DWC system which demonstrated nearly twice the WUE. The G-DNA system exhibited the highest NUE in both environmental conditions, suggesting that spinach in the G-DNA system could absorb more nitrogen from the nutrient solution and yield more with the same amount of absorbed nitrogen compared to DWC and C-Tree systems. These findings indicate that the G-DNA system holds greater potential for improved NUE, and higher spinach yield compared to the C-Tree system. However, the G-DNA and C-Tree systems had no significant effect on WUE
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