Date: Mon Aug 1, 2016
Time: 4:20 PM - 6:00 PM
Table Grape (Vitis vinifera L.) is the main exporting horticultural crop in Chile, with the country being one of the top exporters at the world level.
Commonly, grape producers perform trials of different commercial products which are not evaluated in an objective way. On the other hand they do not have the tools to easily identify areas within the field that may have some limiting factor. The use of active ground sensors that pass under the canopy several times during the season may be a suitable tool to solve these problems. In this regard, in an average field, producers go under the canopy > 20 times during the season to perform different managements, occasions that could be used to monitor it.
In order to assess the use of active ground sensors to evaluate commercial treatments and to define areas with potential limiting factors, two field studies were carried out in the Central Region of Chile during the 2014/2015 season.
In the first study three table grape fields var. Red Globe with a commercial treatment and two with a control treatment (producer) were evaluated. Fields had an average area of 3 ha. After application of the treatments, the canopy of each field was evaluated through the use of the OptRx sensor (AgLeader Technologies, Inc.) which was operated about one meter from the canopy, from an ATV, below the grapevine. The OptRx is an active three-band sensor, Red, Red Edge and near infrared (NIR), from which the NDVI was calculated. Evaluations were carried out on October 9, October 30, November 10, and December 5 2014; and January 12 and 28 2015. Within each field a systematic grid of 20 points was established; at each sampling point the number of clusters / plant and weight of bunches in four evaluation dates were determined: 12/5/2014, 1/12/2015, 1/29/2015 and 3/3/2015, the latter date to harvest. At harvest, the grapes collected at each point were assessed for: number of berries / bunch, berry weight, pH and Brix. Regression models using NDVI as an independent variable were developed to evaluate treatment effects.
In the second study, several fields of two table grape varieties (Thompson Seedless and Red Globe) were evaluated using the OptRx sensor in January 2015. With sensor data NDVI was estimated for each field. Fields were classified in three vigor zones (low, medium, and high NDVI). Each zone was sampled using composited soil samples and several chemical, microbiological and biochemical (enzymatic activity) were determined at 0-30 cm depth. Zones of low vigor of the Thompson Seedless variety were amended using compost and fields evaluated again one year later. Analysis of variance was used to evaluate the effect of zones on selected soil properties.
Results indicated that OptRx sensor is a simple and useful tool to study canopy changes in table grapes. The NDVI from the sensor is a good variable to incorporate in regression models to evaluate modest treatment effects. Stratified sampling using NDVI allowed identifying few soil properties that may explain plant vigor.
Nowadays, internet and mobile technologies are developing and being used in everyday life. Systems based on mobile technologies and IoT (Internet of Things) are being popular in every area of life and science. Innovative IoT applications are helping to increase the quality, quantity, sustainability and cost effectiveness of agricultural production.
In this study; a system which monitors temperature, relative humidity and PAR (Photosynthetically Active Radiation) and warns the farmer via SMS if any of these atmospherical parameters is beyond the pre-defined limits, in order to prevent damages to the plants, was developed. A software and hardware was developed which interprets data from sensors and transmits data into GSM terminal. Data have been collected with a computer that is connected to the system via USB. Later, these data have been used to identify data loss via GSM connection. A website has been used to monitor actual values and save data in an online database.
Experiments was held firstly in a laboratory for 6 months during development period and then in a greenhouse between 21 February and 25 February, 2015. Temperature, relative humidity and PAR values were uploaded to a remote server via GPRS and analyzed on the computer. Between these dates; temperature values outside the pre-defined limits occurred 3 times and relative humidity values outside the pre-defined limits occurred 10 times. The developed system sent 70 SMS messages which informs the farmer that temperature is low for 2100 minutes total and 129 SMS messages which informs that the relative humidity is high for 3908 minutes total. Total SMS loss was identified as 0.5%.
At the end of the experiments, differences was observed between data saved on the computer and data on the remote server. These differences were 150 repeating records, 25 missing record and 1 wrong record on the remote server. It is believed that these errors occurs because of the EMI (Electromagnetic Interference) from GSM terminal and atmospheric charges.
In conclusion, greenhouse monitoring systems such as developed in this study are seem to be successful. When designing systems to be used in greenhouses, a faraday cage which blocks the EMI and an earth connection should be used to protect the system from atmospheric charges.
Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs) and a machine vision technique would be useful in measuring and managing the concentrations of nutrients based on the biomass estimation of crops grown in a plant factory. In this study, a computer-based nutrient management system was developed to effectively manage concentrations of NO3, K, and Ca ions using an array of ISEs and fertilizer pumps to grow lettuce in a closed hydroponic system. Images of lettuce grown were obtained with a RGB camera and an image processing algorithm based on Excess Green (ExG) and RGB indexes was developed to estimate biophysical parameters related to lettuce growth, such as LCA and fresh weight. The growth parameters estimated with the developed image algorithm were validated by a comparison to the actual values. In a validation test, the fresh weights of lettuce plants estimated with the developed image processing algorithm were almost comparable to actual values, exhibiting slopes of 1.26 and with R2 of 0.89. In addition, a Gompertz growth model fitted changes in the estimated fresh weight over time well (R2 >0.99). There were no significant correlations between individual ion absorption rate and the parameters of lettuce growth, but NO3 ion absorption showed a potential (P<0.1) as a nutrient for managing plant growth. The results of this research provided a potential of using an automated nutrient control system and an image processing method for efficient management of lettuce plants grown in a plant factory. Further studies include variable nutrient management of lettuce based on automated sensing of lettuce growth status using an on-the-go image acquisition system that can automatically take lettuce images while moving along a predefined path.
Number of greenhouses has been increased in many countries to control the cultivation conditions and improve crop yield and quality. Recently, various sensors and control devices, and also wireless communication tools have been adopted for efficient monitoring and control of the greenhouse environments. However, there have been farmers’ demands for improved compatibility among the sensors and control devices. In the study, sensor and control interface modules with improved compatibility were developed and tested in field conditions. Sensing parameters may include light intensity, temperature, humidity, CO2, wind, and rain for ambient environment, and EC, pH, and nutrient contents for root zone environments. Control devices may include lamp, heater, cooler, humidifier, fan, CO2 generator, and window motor for ambient environment, and nutrient and water supply devices for root zone environment. For monitoring and control of greenhouse environment, sensors and control interface modules were fabricated using atmega128 as the mainboard with 8-channal relay for control, LCD for display and checking, zig bee for wireless communication, and the termite software for cording. The module was designed so that could send and receive data from computer and control a window opening and closing motor, a cooling & heating unit, ventilation fans through comparison operations of the measured and input setting values. Using the interface module and user computer, the operating conditions and the environmental conditions of the greenhouse were monitored, and the changes in temperature, humidity, light intensity, carbon dioxide, and other environmental parameters were confirmed in real-time, and also the environment setting values were easily changeable. Fabricated interface modules were tested in strawberry and chrysanthemum fields. The experiments were conducted five times and each experiment took about one hour. Optimal temperature, humidity and carbon dioxide conditions were checked whether it was maintained or not through the change of temperature, humidity, carbon dioxide artificially with sensor and control interface module that was developed. After confirming the maintenance of optimal growth conditions, table and graph were created by the result values and required time. For advancement of our sensor and control interface module, tuning, safety and emergency handle function was considered. First, since the malfunction and shorten the life of the product concerned by the resonance phenomenon in the greenhouse to prevent this phenomenon was ensuring the safety of products. Second, electrical safety certification was given by the electrical appliances safety certification system through the institute for safety assessment for safety of greenhouse sensor and control interface module Third, the module was controlled by the optimal safety conditions in the greenhouse through the disaster emergency response algorithms, such as hurricanes and earthquakes and torrential rains. It’s also expected that resolving difficult to deal with greenhouse environmental programs and contributing to technical improvement of the control program related field and greenhouse environmental control system.