Greenhouse Control Research Articles

Verbena × hybrida and Scaevola aemula flowers provide nutrients for the reproduction of Nesidiocoris tenuis used for biological pest control in greenhouses

Verbena × hybrida and Scaevola aemula flowers provide nutrients for the reproduction of Nesidiocoris tenuis used for biological pest control in greenhouses

IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control

Agriculture is the foundation of human civilization. However, the rapid increase of the global population poses a challenge on this cornerstone by demanding more food. Modern autonomous greenhouses, equipped with sensors and actuators, provide a promising solution to the problem by empowering precise control for high-efficient food production. However, the optimal control of autonomous greenhouses is challenging, requiring decision-making based on high-dimensional sensory data, and the scaling of production is limited by the scarcity of labor capable of handling this task. With the advances of artificial intelligence (AI), the internet of things (IoT), and cloud computing technologies, we are hopeful to provide a solution to automate and smarten greenhouse control to address the above challenges. In this paper, we propose a smart agriculture solution named iGrow, for autonomous greenhouse control (AGC): (1) for the first time, we formulate the AGC problem as a Markov decision process (MDP) optimization problem; (2) we design a neural network-based simulator incorporated with the incremental mechanism to simulate the complete planting process of an autonomous greenhouse, which provides a testbed for the optimization of control strategies; (3) we propose a closed-loop bi-level optimization algorithm, which can dynamically re-optimize the greenhouse control strategy with newly observed data during real-world production. We not only conduct simulation experiments but also deploy iGrow in real scenarios, and experimental results demonstrate the effectiveness and superiority of iGrow in autonomous greenhouse simulation and optimal control. Particularly, compelling results from the tomato pilot project in real autonomous greenhouses show that our solution significantly increases crop yield (+10.15%) and net profit (+92.70%) with statistical significance compared to planting experts. Our solution opens up a new avenue for greenhouse production. The code is available at https://github.com/holmescao/iGrow.git.

Efficacy of Biorational Products for Managing Diseases of Tomato in Greenhouse Production

Gray mold (Botrytis cinerea), late blight (Phytophthora infestans), powdery mildew (Leveillula taurica), pith necrosis (Pseudomonas corrugata), and bacterial canker (Clavibacter michiganensis) are major diseases that affect tomato (Solanum lycopersicum L.) in greenhouse production in Mexico. Management of these diseases depends heavily on chemical control, with up to 24 fungicide applications required in a single season to control fungal diseases, thus ensuring a harvestable crop. While disease chemical control is a mainstay practice in the region, its frequent use increases the production costs, likelihood of pathogen-resistance development, and negative environmental impact. Due to this, there is a need for alternative practices that minimize such effects and increase profits for tomato growers. The aim of this study is to evaluate the effect of biorational products in the control of these diseases in greenhouse production. Four different treatments, including soil application of Bacillus spp. or B. subtilis and foliar application of Reynoutria sachalinensis, Melaleuca alternifolia, harpin αβ proteins, or bee honey were evaluated and compared to a conventional foliar management program (control) in a commercial production greenhouse in Central Mexico in 2016 and 2017. Disease incidence was measured at periodic intervals for six months and used to calculate the area under the disease progress curve (AUDPC). Overall, the analysis of the AUDPC showed that all treatments were more effective than the conventional program in controlling most of the examined diseases. The tested products were effective in reducing the intensity of powdery mildew and gray mold, but not that of bacterial canker, late blight, and pith necrosis. Application of these products constitutes a disease management alternative that represents cost-saving to tomato growers of about 2500 U.S. dollars per production cycle ha−1, in addition to having less negative impact on the environment. The products tested in this study have the potential to be incorporated in an integrated program for management of the examined diseases in tomato in this region.

On the Extremum Control Problem with Pointwise Observation for a Parabolic Equation

In this paper we consider a control problem with pointwise observation for a one-dimensional parabolic equation which arises in a mathematical model of climate control in industrial greenhouses. We study a general equation with variable diffusion coefficient, convection coefficient, and depletion potential. For the extremum problem of minimizing an integral weighted quadratic cost functional, we establish the existence and uniqueness of a minimizing function. We also study exact controllability and dense controllability of the problem. Necessary conditions for an extremum are obtained, and qualitative properties of the minimizing function are studied.

Renewable Energy Based Green House Environment Monitoring System Using IOT

In greenhouses, plants like flowers and vegetables are grown. Daytime sunshine heats the soil, plants and structure itself inside greenhouses. Many farmers struggle to generate respectable income from greenhouse crops as a result of their failure to manage two essential factors that influence plant development and productivity. Temperatures in greenhouses shouldn’t drop unless certain circumstances apply. The effects of high humidity include crop transpiration, water vapour condensation on various greenhouse surfaces and water evaporation from moist soil. These issues are addressed by the monitoring and management system for greenhouses. This study shows how to develop and use a variety of sensors for monitoring and controlling the greenhouse environment. The temperature and humidity sensors, soil moisture sensor, Node-MCU module and water pump are all part of this greenhouse control system, which is run by an Atmega328 microprocessor. The utilization of solar panels ensures constant power supply. Temperature and humidity in the atmosphere are measured through a DH11 sensor. The pumps turn on as the soil moisture sensor detects a reduction in the soil’s water content. Monitoring and managing the system will be simple in this manner. The IOT module (ESP8266) receives data pertaining to these parameters at the same time. Regardless of any threshold mismatch identified, the data is delivered at regular intervals to IOT. The ESP8266 Node-Microcontroller, the DHT11 sensor, a solar panel and a soil moisture sensor are all used in this project. The Wi-Fi module built inside the microcontroller transmits the data to cloud database of the BLYNK app.

Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse

Greenhouse climate is a highly complex system that contains nonlinearity and dependencies between each system state. This paper proposes a novel nonlinear model predictive control (NMPC) framework for greenhouse climate control to minimize the total control cost mainly coming from energy use. A nonlinear dynamic model of the greenhouse climate, including temperature, humidity, CO2 level, and light intensity, is first constructed based on developed mass balances and energy transport phenomena. Real-world greenhouse climate data and outdoor weather data are gathered to systematically identify the system parameters for the nonlinear greenhouse climate model. The nonlinear dynamic model is then integrated into the proposed NMPC framework which iteratively solves a nonlinear programming problem to obtain the optimal control inputs of fan airflow rate, pad cooling air velocity, heating pipe flow rate, CO2 injection rate, fogging rate, supplemental light intensity, and shade curtain coverage. The stability and feasibility issues of the proposed NMPC framework on a semi-closed greenhouse are explicitly discussed in this work. Case studies on controlling a greenhouse located in Cornell University campus are simulated to demonstrate the performance of the proposed NMPC framework. The results show the NMPC framework could efficiently minimize total control cost and constraint violation. Humidity, CO2 level, and light intensity can be controlled with nearly no violation on the predetermined constraints over different seasons and climate conditions. As for temperature, it is almost always maintained within the acceptable region in winter and spring. On extreme days of summer, there are some temperature violations due to the limited cooling capacity.

Transparent conductive far-infrared radiative film based on cotton pulp (CP) with carbon fiber (CF) in agriculture greenhouse

There are many types of transparent conductive films, the most common made by depositing indium-tin-oxide (ITO) on ultra-thin glass substrate by physical or chemical methods. ITO films are good conductor of electricity, achieving low resistivity of 10−4 Ω cm which is similar to metal. This however results in high power dissipation rate of 1500–6000W/m2 when connected to 220–240V, which results in high surface temperatures of 300–1000 °C. In this study, a transparent conductive film is developed specifically for agriculture heating, application of mercerization of CP-CF film (mixed conductive carbon fiber (CF) with cotton pump (CP) substrate), and depositing acrylics. For suitability in agricultural heating, the resistivity is designed to be around 40–50 Ω mm, which is much higher than typical ITO films. The newly developed CP-CF transparent film has an average Edge-to-Edge Resistance of 545.65Ω, light transmittance of 67.9% and has a heating capability of 88.70 W/m2 via far-infrared light. The film has improved light transmittance and is suitable for deployment as part of the retaining structure of agricultural greenhouses as it allows adequate sunlight penetration for the necessary photosynthesis of crops. The analysis evidence showed promising result and can solve the long-term problems of agriculture in seasonable regions such as northern China during the winter. The developed CP-CF film conveys improved energy efficient replacement to conventional greenhouse control to meet the optimal light transmittance and required temperature needs for of crop growth.

Effects of interaction and effectiveness of weed control when using tank mixtures of herbicides in maize crops

Many countries are now facing the problem of increase in resistant biotypes of weeds. The spread of herbicide-resistant weeds across agrophytocenoses poses a threat of decrease in the effectiveness of use of herbicides in agricultural fields. In order to develop anti-resistant compositions of herbicides for protection of maize (Zea mays L.) crops, we studied effects of interaction and efficiency of weed control in greenhouse and field experiments. We studied the possibility of combined use of 4-hydroxyphenyl pyruvate dioxygenase-inhibiting herbicide tolpyralate and inhibitor of transport of electrons in photosystem 2 of chloroplasts – terbuthylazine – and acetolactate synthase-inhibiting rimsulfuron. In greenhouse experiments on model objects, we found that interaction in the mixtures of tolpyralate with rimsulfuron was antagonistic, but the antagonism may be overcome by increasing the rate of applied rimsulfuron. At joint use of tolpyralate and terbuthylazine, a synergistic increase in phytotoxic effect was observed, caused by increase in the effectiveness of the blocking electron-transport chain and increase in intensity of formation of reactive oxygen species. According to the results of the field experiments, we drew the conclusion that the efficacy of using the mixture of tolpyralate and rimsulfuron depends on the species composition of weeds. In the presence of rimsulfuron-resistant weeds, interaction with tolpyralate becomes antagonistic even in the conditions of increased rate of application of rimsulfuron, and thus the effectiveness of the protection significantly decreases. At the same time, after applying tank mixture of tolpyralate with terbuthylazine, the synergistic character of the interaction was maintained toward a broad range of species of grass and dicotyledonous weeds, providing high efficiency of maize crop protection. The herbicide compositions that were analyzed and are presented in the article allow one to decrease the possibility of emergence of resistant biotypes of weeds, and also to effectively control the already existing resistant biotypes.

Fuzzy Logic Design to Control the Duration of Irrigation Time in the Greenhouse

Automatic irrigation is not new, this method has been invented by mankind to irrigate large areas of land through drip irrigation systems. The system is implemented to reduce water wastage in irrigation. In greenhouse irrigation control, computerized control is very important to increase productivity. On the other hand, conventional irrigation control in greenhouses is not effective, because it is based on on-off or proportional control. This paper presents a solution to control irrigation time duration based on fuzzy logic method. Fuzzy logic controller (FLC) was developed using the Mamdani method. FLC is built on the NodeMCU ESP8266 board mounted with a DHT22 and soil moisture sensor. Temperature and water content in the soil parameters are used as input for fuzzy logic to determine the duration of irrigation time. The linguistic values used as fuzzy membership functions include soil moisture (water, wet, dry), temperature (cold, normal, hot), and watering time (zero, short, medium, long). Based on the membership function, 9 fuzzy rule bases are determined. The testing results on fuzzy logic built on NodeMCU ESP8266 with fuzzy logic built on MATLAB software obtained an average error of 0.59%.

Comprehensive Review on Climate Control and Cooling Systems in Greenhouses under Hot and Arid Conditions

This work is motivated by the difficulty of cultivating crops in horticulture greenhouses under hot and arid climate conditions. The main challenge is to provide a suitable greenhouse indoor environment, with sufficiently low costs and low environmental impacts. The climate control inside the greenhouse constitutes an efficient methodology for maintaining a satisfactory environment that fulfills the requirements of high-yield crops and reduced energy and water resource consumption. In hot climates, the cooling systems, which are assisted by an effective control technique, constitute a suitable path for maintaining an appropriate climate inside the greenhouse, where the required temperature and humidity distribution is maintained. Nevertheless, most of the commonly used systems are either highly energy or water consuming. Hence, the main objective of this work is to provide a detailed review of the research studies that have been carried out during the last few years, with a specific focus on the technologies that allow for the enhancement of the system effectiveness under hot and arid conditions, and that decrease the energy and water consumption. Climate control processes in the greenhouse by means of manual and smart control systems are investigated first. Subsequently, the different cooling technologies that provide the required ranges of temperature and humidity inside the greenhouse are detailed, namely, the systems using heat exchangers, ventilation, evaporation, and desiccants. Finally, the recommended energy-efficient approaches of the desiccant dehumidification systems for greenhouse farming are pointed out, and the future trends in cooling systems, which include water recovery using the method of combined evaporation–condensation, as well as the opportunities for further research and development, are identified as a contribution to future research work.

Risk management system for the monitoring and control of a small lettuce greenhouse

The management of agricultural risks is a scenario that allows knowing the probable factors that can affect a crop, knowing the variables allow designing control and mitigation of projects in case of any affectation, failure to do so may cause loss of production, the objective This research was the design and construction of a monitoring system for greenhouses that would allow to carry out a small-scale control of the environment, through knowledge of the behavior of the different agroecological variables that intervene in the process, allowing to generate different scenarios For the control of the different variables of nutrition, irrigation, and lighting, it was possible to carry out a set of experiments that showed that the system allows controlling the production in the established time, as well as the effect of the control on the quality of the vegetables.

Photosynthetic Responses of Greenhouse Ornamentals to Interaction of Irradiance, Carbon Dioxide Concentration, and Temperature

Supplemental lighting, temperature control, and CO2 enrichment can improve the productivity of greenhouse crops, but operating costs for greenhouse control systems to maintain environmental parameters at desired setpoints can be expensive. To balance operating costs with productivity, growers need to be able to predict how a crop will perform as a function of photosynthetic photon flux density (PPFD), CO2 concentration, and temperature. The objective of this study was to explore the response of net photosynthetic rate (Pn) to PPFD and CO2 concentration, for plants acclimated to different growth environment temperatures or light intensities. We measured Pn at all combinations of 14 irradiances and four CO2 concentrations of calibrachoa (Calibrachoa ×hybrida ‘Superbells Lemon Slice’), petunia (Petunia ×hybrida ‘Supertunia Mini Strawberry Pink Veined’), and verbena (Verbena ×hybrida ‘Superbena Royale Whitecap’) grown at three light intensities, and of geranium (Pelargonium ×hortorum ‘Maverick Red’), pepper (Capsicum annuum ‘California Wonder’), and sunflower (Helianthus annuus ‘Pacino Gold’) grown at three different temperatures. Sunflower, pepper, and geranium were fit to a model representing Pn as a function of PPFD, CO2 concentration, and leaf temperature. Photosynthetic light response curves, at each CO2 concentration, were fit for each species and growth environment using a nonrectangular hyperbola. These models can be used to identify multiple combinations of PPFD, CO2 concentration, and leaf temperature that would result in equivalent rates of photosynthesis, allowing the most cost-effective combination to be chosen.

Design and Implementation of a Wireless Sensor Network for Smart Greenhouse Controller

Sensors play an essential role in gathering environmental information for greenhouse farming. Wireless sensor network creates and manages links between sensor blocks in the system. As a result, not only various environmental parameters can be collected, but the sensor location can also be flexibly deployed. Sensor blocks require low energy consumption and inexpensive implementation costs with typical operating conditions. The research has built a wireless sensor network based on open Radio Frequency (RF) technology. Each sensor block has a low deployment cost and operates independently via a solar-powered unit. A novel communication protocol is designed for the proposed sensor network. In addition, a greenhouse controller exploiting designed wireless sensor networks is also constructed to evaluate the practicality of the system. Sensor networks developed are intended to be applied to the existing agricultural greenhouses in the surveyed area. The greenhouse is medium-sized, and the system implemented in practice is for vegetable farming. As a result, the controller can connect to the Internet to serve IoT links and applications. Experimental results prove the practicality of sensor blocks and the stability and efficiency of the wireless sensor network. It helps to reduce deployment costs and improve applicability. In addition, the sensor blocks are designed and built with low energy consumption, which can be operated with a small solar power source.

Discrete controller synthesis applied to smart greenhouse

The popularization of the Internet of Things allowed the emergence of different monitoring and control solutions in different economic sectors. For example, in agriculture, this type of technology has supported the monitoring of environmental variables essential in decision-making, defining when and how much water to use in a given crop. Besides, it made it possible to control various devices to meet each crop type's environmental requirements, increasing productivity. In this sense, there is a need for increasingly improved control strategies to meet crop requirements in real-time, ensuring sustainable production and reliable quality. This work presents Discrete Event System techniques to develop an agricultural greenhouse controller considering self-configuring mechanisms for adapting to dynamic environments and preventing conflicting rules from violating control objectives. The controller was validated through a simulator based on temperature balance equations, allowing the environment's temperature control. We used accurate climate data from actual Brazilian meteorological stations to evaluate different control scenarios in the year's four seasons, checking the controller's efficiency and the control strategy adopted, guaranteeing the crop's thermal comfort and minimizing water loss. Applying this control technique, we achieved the crop's thermal comfort under 87% of the time, influencing the absolute humidity and evapotranspiration rates over 31 days. Besides, we were also able to reach 66% more energy efficiency than other approaches.

Strength and Durability of Geo-Polymer Concrete with Mineral Admixture

Abstract: It is important to durable of structure and reduce co2 emission through the greater use of substitute of cement. The use of supplementry cementitious materials as partial replacement for the cement in concrete will play a significant role with respect to the environmental control of greenhouse and global temperature reduction. The development of geopolymer concrete (GPC) processing of geopolymer using black rice husk ash, GGBS in combination with sodium hydroxide and sodium silicate solutions, offers a promising alternative to ordinary portland cement concrete. This study compares the different ratio of black rice husk ash to GGBS where50:50 60:40 40:60 ratios and differing the molarities of alkaline solutions which are 8m , 10m and 12m and comparing the strength of the above ratios and conducting durability characteristics of fly ash and GGBS based geopolymer concrete by conducting test procedure like compressive strength , split tensile strength test, sorpitivity test. Keywords: Geo-polymer concrete ,Black rice husk ash (BRHA),Ground granulated blast furnace slag (GGBS).

Exercise on Environmental Monitoring and Control of Green house by IoT Devices toward Smart Agriculture

Exercise on Environmental Monitoring and Control of Green house by IoT Devices toward Smart Agriculture

Silica coated insect proof screens for effective insect control in greenhouses

Insect proof screens were coated with silica (SiO 2 ) nanoparticles using the plasma coating process. The work studied whether a screen coated by SiO 2 nanoparticles could be more effective on insects' control than a non-coated screen. Thus, the insect control properties of 25- and 40-mesh screens were studied. Besides, a series of experiments were performed to investigate the mechanical, optical, and airflow properties of different (25, 40, and 50) mesh screens coated or not with SiO 2 nanoparticles. The air permeability of the screens was affected, while the mechanical and optical properties of the screens were not significantly affected by the SiO 2 coating. Compared to 40- and 50-mesh non-coated screens, a 25-mesh SiO 2 -coated screen had 54% and 66% higher air permeability values, respectively. The mean number of aphids infesting the leaves and stems of the crop grown under a 25- or a 40-mesh SiO 2 -coated screen was up to 93% and 81% lower than those grown under the non-coated screens, respectively. The number of aphids found on plants grown under a 25-mesh SiO 2 -coated screen were significantly lower (about 80%) than those recorded under a 40-mesh non-coated screen. Based on the differences observed on screen's air permeability and on greenhouse ventilation models available in the literature, it was estimated that a greenhouse with a 25-mesh SiO 2 -coated screen will have 11.5% and 23.1% higher ventilation rate than a greenhouse with a 40- or 50-mesh non-coated screen, respectively. • Insect proof screens were coated with SiO 2 nanoparticles using plasma coating process. • SiO 2 coating slightly affected the optical and mechanical properties of screens. • Use of SiO 2 coated screens decreased 80% the population of aphids in the greenhouse. • A 25 mesh SiO 2 coated screen was very effective on insects' control. • A 25 mesh SiO 2 coated screen has higher air permeability than a 40 mesh non-coated.

Synergistic effect of naturally occurring Granulosis virus isolates (PbGV) with phagostimulants against the cabbage butterfly, Pierisbrassicae (L.) for its eco-friendly management

BackgroundTo manage the cabbage butterfly, Pierisbrassicae (L.) (Lepidoptera: Pieridae), it is not wise to use insecticides on leafy vegetables which are eaten mostly fresh. During the past decades, the efforts to manage the pest, through chemical insecticides have raised serious health. Investigations were carried out to isolate naturally occurring GVs (PbGV) as a potent biopesticide against P.brassicae and to explore their efficacy with the application of phagostimulants.ResultsAmong the four naturally occurring isolates obtained from Northwestern Himalayas, Sudhmahadev isolate was found to be the most promising based on virulence and speed of kill against all the instars tested in the laboratory, showing the natural incidence of PbGV infection in field conditions. In concentration and time–response bioassay, all the isolates of P.brassicae Granulosis virus were found high virulent against second instar larvae of cabbage butterfly. Therefore, for enhanced efficacy of PBGV, its combined application with phagostimulants (Lepidiumsativum + Teepol + jaggery) or sticker (Teepol + jaggery), applied in field trials, resulted into greater mortality of larval instars than the single one. Overall, the results indicated that the introduction of a more isolates PBGV strain into populations of P.brassicae could be of vital importance for eco-friendly suppression of this pest globally with the combination of phagostimulants. The application virus alone with the pre-standardized concentration of 1 × 1012 OBs/ha did not reduce the larval population density to the desirable extent in the greenhouse chamber and therefore was not included in field experiments. Overall, the most promising treatments in reducing the larval population of the pest were PbGV + Teepol + B.thuringiensis (93.49 and 91.39%) and PbGV + Teepol + L.sativum (88.79 and 86.97%) over control in both greenhouse and field trials, respectively.ConclusionsIn this study, the native isolates of PbGV from different target locations to test their efficacy against different instars of P.brassicae were explored. Using native PBGV isolates with phagostimulant combinations played an important role for regulating the pest effectively. These phagostimulants not only protected the OBs from degradation in the presence of sunlight but also increased the speed of killing. The biocontrol potential of PbGV in both laboratory and field conditions indicated that baculoviruses are sustainable alternative to chemical insecticides.

Exercise on Environmental Monitoring and Control of Greenhouse Using Smart devices

Exercise on Environmental Monitoring and Control of Greenhouse Using Smart devices

Practical use of Deep Learning-Based Daily Stem Elongation Measurement of Tomato Plants in Two Commercial Greenhouses

Skilled farmers generally evaluate the growth of a crop by observing the crop's appearance. However, with the increasing digitalization of agricultural practices, a numerical index representing the crop's growth status is strongly needed. For this purpose, the speaking plant approach (SPA), a sophisticated strategy for environmental control in greenhouses, has attracted a lot of attention. The first and most important step in SPA is to obtain physiological information from a plant and then judge whether the plant is healthy. The daily measurement of plant growth is therefore important in SPA, particularly for environmental control. Various imaging techniques have been studied for this purpose. A robotized chlorophyll fluorescence (CF) imaging system that evaluates daily changes in the photosynthetic function of a tomato canopy was developed in our previous study and later commercialized. In this study, for the measurement of the daily stem elongation of tomato plants, we developed a deep learning model that detects a tomato plant's shoot apex in a CF image. YOLOv3, a representative object detection algorithm, was used for the shoot apex detection model. Images captured at Ehime University were used for training and validating the model. The developed shoot apex detection model was applied to two different commercial greenhouses (Asai Nursery and Agrimind; largest greenhouses in Japan) to measure the daily stem elongation of tomato plants. The developed model detected the shoot apexes with an average F-measure of 0.97 for the greenhouse from which the training dataset was derived (Ehime University test dataset) and with average F-measures of 0.69 and 0.82 for the two commercial greenhouses (Asai Nursery and Agrimind test datasets). Then, the 19 days and 26 days consecutively measurements were conducted, and the daily stem elongation of tomato plants was measured. The obtained results indicate that the developed deep learning model is effective for measuring the daily stem elongation of tomato plants in commercial greenhouses.