Background

Agriculture in Mexico is an important sector of the country's economy, both historically and politically, although it now represents only a small percentage of Mexico's GDP (3.6% in 2015). World Bank 2015. Mexico is one of the cradles of Mesoamerican agriculture where plants such as corn, beans, chilies, tomatoes, pumpkins, avocados, cacao, various kinds of species and many more plants were domesticated. Agriculture from the colonial era until the Mexican Revolution was concentrated in large private estates, farms, but with the Mexican Revolution the lands were divided and redistributed. Since the second half of the 20th century, the North American Free Trade Agreement (NAFTA) and the country's economic policies have again favored large commercial agricultural enterprises. The main crops in Mexico are grains such as corn and wheat, and tropical fruits such as oranges and bananas INEGI (2009). The most important agricultural exports are tropical fruits such as watermelon and vegetables such as tomatoes. Sixty percent of Mexico's agricultural exports go to the United States. MIT Media Lab (2009).

As of the beginning of the 21st century, the rural labor force continues to be important, but it is shrinking . Traditional farming methods of small plots worked by families and small communities continue to dominate in many regions, especially those with large indigenous populations such as the Southern Plateau. In these areas, the main crops are corn, beans and squash, as in the Mesoamerican period. Many farmers still subsist thanks to self-consumption agriculture and earn money by selling surplus crops in local markets, especially in central and southern Mexico. Zalta (2012).

The export of agricultural products to the United States is particularly important, especially since the creation of the FTA. While only twelve percent of agricultural exports from the United States go to Mexico, approximately 60% of Mexico's agricultural exports go to the United States. Chamber of Commerce (2012). The growing population of Mexico has turned the country into a net importer of grains. Johnson 2009. Because of the FTA, the US they obtain advantages against Mexico in the production of corn, but Mexico benefits in relation to the United States in the production of vegetables, fruits and beverages. Among the crops whose exports to the United States grow fastest are winter fruits and vegetables, as well as fruit juices and fresh flowers. Two important products for export to the United States are avocado and tomato. USA prohibited the importation of avocado for 80 years, for hygienic reasons. In 1997, imports of avocados from Michoacán to the United States were again allowed. Most of the imported tomatoes that are currently consumed in the United States come from Mexico .Chamber of Commerce (2012).Faced with this situation, the automation of small and large scale agriculture is of colossal importance, since applying mechatronic technologies to agriculture would help detonate productivity in the Mexican countryside, an important role in this situation is the Arduino board, for its versatility and its low cost. Arduino is a project of Massimo Banzi born in 2005 with the idea of developing a free hardware board integrated with a microcontroller and an interface to program it. It is designed and built to be very easy to use and can be developed multidisciplinary projects. Electrontools (2016). The objective of this work is to know the current state of the applications of this board in agriculture of the country.

1 Materials and Methods

A systematic and thorough search was conducted for data collection in printed data bases, Internet, journals scientific, graduate and postgraduate university thesis, newspaper articles, etc.

2 Literature Review

In Table 1 shows the results of the search for the use of the arduino board in world agriculture.

3 The Arduino Board in Mexican Agriculture

Negrete (2016) Review the status of the automation in Mexican greenhouses and perspectives for the future and also suggests the use of mechatronics to automate and increase the productivity of agriculture, animal production and beekeeping (Negrete, 2015; 2017a; 2017b; 2017c). The Arduino  is Used in Different Fields of Agriculture.

3.1 Irrigation

Gonzales (2017): Developed an irrigation system that aims to optimize the use of water through an automated irrigation mechanism, this facilitates irrigation through a sensor that monitors the state of moisture in the land, watering the object only when you need water. If the humidity level is low, the system is turned on by means of solenoid valves, if on the other hand the humidity level is high, the system is turned off. The logistic processes of the system are controlled by means of an Arduino Uno Integrated Circuit. The main objective is to achieve a considerable decrease in the use of water, and in turn generate labor savings. Likewise, the irrigation system can be adapted to different types of terrain, even to wavy typefaces, which do not require leveling.

Gaona (2017): Development a soil moisture measurement system using an electronic sensor, the sensor measures the electrical conductivity of a soil. For a period of seven days, readings provided by the sensor were collected and, simultaneously, the volumetric moisture content of the soil was manually evaluated and a potential type function was adjusted to characterize its behavior. The research was done in the laboratory using a container with 15120 g of soil with a mass of 18007 g. A potential relationship was found between soil volumetric moisture and sensor values in the evaluated soil. Gravimetric analyzes of soil samples show a correlation of R2 = 0.9094. An Arduino UNO board of free programming, a sensor of humidity Fc-28, a reader of SD and a battery was used. Additionally, the sensor readings were related to the moisture content of the soil by the gravimetric method.

Lozoya (2016): Presents a model driven control strategy applied to an irrigation system, in order to make an efficient use of water for large crop fields, that is, applying the correct amount of water in the correct place at the right moment. The proposed model uses a predictive algorithm that senses soil moisture and weather variables, to determine optimal amount of water required by the crop. This proposed approach is evaluated against a traditional irrigation system based on the empirical definition of time periods and against a basic soil moisture control system. Results indicate that the use of a model predictive control in an irrigation system achieves a higher efficiency and significantly reduce the water consumption.

Osorio (2016): Realized a research to automate the process for the realization of Fertigation solutions where the main objective is to design a prototype and a computer program with a friendly user interface for producers or people who need to prepare Fertigation solutions. The software will interact with the Arduino platform as an electronic element to control actuators and read sensor data. The actuators will be solenoid valves to allow the passage of substances to a container for the preparation of the solution and flow sensors will be used to determine the necessary quantity of each substance in question. The free software (Java) and free hardware (Arduino) with which the prototype will be built will allow a reduction in costs.

3.2 Livestock production

Nava (2017): Proposes the design of a device that detects mounts in cows at any time, and is able to record the time and number of mounts, as well as being able to transmit information at medium distances and in a wireless way. This can be done with the use of radio frequency signals, which is a fast and efficient way to transmit information. The purpose is to reduce economic losses by not detecting the estrus period early and increase milk production in cattle. The device for detecting mounts is composed of 4 main elements: a proximity sensor SHARP GP2Y0A710K, an Arduino Microboard, a Xbee S2 radio frequency module with its respective Breakout Board (it works as a base and voltage regulator), finally a rechargeable portable battery with 5V output.

3.3 Agricultural machines

Lopez (2017): Develop and evaluate the control system for a maize-husking machine’s cutting blade positioning system through an artificial vision system, the positioning mechanism and a maize processing algorithm was designed with OpenCV software. A control system was developed to adjust the position of the cutting blade by applying MATLAB and Arduino cards. The system applies a PID controller with a stabilization time of 0.04 s and a cutting error of ± 5.7 mm.

Sandoval (2017): Presents the electronic design, construction and evaluation of a mechatronic system (SM) for the control of the dosifiers and the pneumatic system of a seeder-fertilizer, as well as for the measurement of variables that allow to characterize the performance of the machine in laboratory and field. The electronic design of the SM is based on microcontrollers, using a master element (Arduino MEGA based on ATmega2560) and multiple slave components (ATmega328P) which support bidirectional communication via I2C. The SM consists of eleven modules, where the master module is responsible for controlling the general operation of the system and for receiving user operating instructions; slave modules receive from the master the information necessary to operate and control the operation of the dozers (seed, fertilizer and pesticide), the pneumatic system and the conveyor belt (used in tests), allow measurements of the speed of displacement of the seeder, level of the hoppers, mass of the input thrown by the dozers and quantity of seeds thrown by the discharge tube.

3.4 Photovoltaic energy

Lopez (2016): Redesign the structure obtained in the thesis work Energetic evaluation of an array of photovoltaic panels with automatic guidance. Resendez  (2014) in order to reduce to the maximum the limitations presented by its operation, improvements were made in the structure and in the electronic system of automatic orientation, and with this it was possible to obtain an increase of 20% (1.88 h) in the time of the period of capture of solar radiation. A net increase in the efficiency of the solar panels was obtained with automatic orientation of 37.49% compared to the panels installed in a fixed way, with a net power generation of 5.9 kW / day and 4.3 kW / day respectively. In addition, the electronic system works continuously and demanded an energy consumption of 37.3 kW / day, which represents a 1.15% of the net energy generated. We used an electric motor with Arduino UNO and a module of 2 relays for the tracking mechanism of the Sun.

3.5 Biotechnology

Rodríguez (2016): Use of the hydrocyclone as a photobioreactor is proposed, for this purpose a system was developed which allowed to study the fluid mechanics inside of one hydrocyclone. Considering the results obtained, it could be established the operational conditions to assess the growth of the microalgae Scenedesmus incrassatulus inside the system. This study was made in the Microalgae Laboratory of the Biotechnology and Bioengineering Department at the Center of Research and Advanced Studies of the National Polytechnic Institute Campus Zacatenco, this work was divided into four steps: 1) design and make the installation and the hydrocyclone-reactor (RH), 2) arrange the installation and characterize the flow-sensors, 3) visualize the fluids flow developed inside the RH and determine the growth kinetics conditions and 4) asses the growth of Scenedesmus incrassatulus inside the RH. The installation’s design was divided in four systems; hydraulic, pneumatic, lighting and holder. Meanwhile, the RH was designed with two tangential opposite inlets, the first one supplies the culture medium and the second one dispenses the air so that the interaction between the two flows stimulates the mixing, which in turn propitiates the microalgae’s growth. The installation was instrumented with manometers to measure pressure, while the flow-monitoring was made with a Hall-effect-sensors array, an Arduino Nano and one LCD-display.

3.6 Agricultural education

Aguilar (2015): Created an out-of-school science dissemination program, in which participants can apply knowledge of electronics, programming and mathematics mainly, to invent various products using the Arduino programming environment, which is an open source mechatronic applications development environment, with a wide community of participants in the world, which allows the creation of products with a comprehensive scientific and social approach. The methodology used was as follows: 1. A training programming workshop was developed through which basic concepts of training are presented. Arduino; 2. Arduino workshops were given in several high schools; 3. After each workshop, the students defined the projects to be developed and the knowledge they should acquire for it; 4. Follow-up and advice was given to each project; 5. In the end, the results of the projects were presented to the school community, in areas as diverse as home automation, robotics, security and agriculture.

3.7 Agrometeorological

Alfaro (2015): Presents the development of a wireless agrometeorological station, for which the program was held in Arduino five sensors (humidity, air temperature, soil temperature, soil moisture and wind speed) in order to monitor mentioned variables, was installed at the greenhouse of the Agricultural Mechanical Engineering. Department (DIMA) of the Chapingo Autonomous University, to monitor the weather within it. Each sensor was programmed individually, in the case of the sensors related to soil moisture and wind speed; they had to be calibrated before programming. In the soil moisture case the gravimetric method was used to calibrate, we found a potential relationship between the volumetric soil moisture and the sensor values in the evaluated soil.

Corral (2016): Presents the development of a wireless sensor network, carrying out monitoring of climatic parameters of temperature and humid in a geographic area defined by a coverage of radio-frequency links, as well as actuators that activate devices to prevent low temperatures in crops. The wireless sensor network is built with a card based on an open hardware microcontroller called Arduino,a card of Xbee wireless communications over the IEEE 802.15.4.2 standard-based Zig-Bee stages, a card of sensors and actuators, and a power supply module provided by batteries.

3.8 Greenhouses

Lugo (2014): Development of a package of low-cost technology for monitoring greenhouse environment. The package is based on the use of free software and hardware and considers the construction and adaptation of sensors for measuring meteorological variables inside and outside a greenhouse, the construction and adaptation of electronic interfaces to capture sensors readings and the development of software for interpreting data. Java and Arduino were used as free software and hardware platforms, respectively. Sensors were compared against commercial sensors developed in the same climatic conditions, and the same data were obtained. However, there was a notable difference in the action time of the sensor developed due to the weight increased by materials used in its construction.

Barrera (2014): Made the proposal of a model of automation of a greenhouse for the cultivation of the garden of the radish making use of the Arduino technology and thus to know the kindness of production that a smart greenhouse could provide to people that are interested in doing a plantation or cultivation at home or on a larger scale, since the time of dedication that a person could provide towards their plants would decrease considerably, because this control system will do the work of monitoring the environmental parameters (temperature and humidity) at the right time so that the crop does not lose his properties.

Ramirez (2015): Carry out the design of a control and monitoring system within a hydroponic greenhouse, to provide constant readings of the internal conditions of the same, since the study of the growth of vegetables such as tomato, represents a strenuous task in the collection of information. An Arduino1R3 board and an Arduino Ethernet Shield were used to control the sensors.

Cortes (2015): Proposed the design of a control and monitoring system of a hydroponic greenhouse, providing constant readings of the internal conditions of the same. For the automation of the greenhouse, different sensors and the Arduino R3 boards and the Arduino Ethernet board were used.

Baltazar et al. (2014): Development of different proposals to automate the temperature control in a greenhouse, which were the use of a PLC, Microcontroller (PIC), Arduino and a Shinko temperature controller, analyzed the advantages and disadvantages of using each device, finding that the Temperature controller was the most suitable.

Diaz et al. (2014): Presents a project that controls and supervises the climatic variables of a greenhouse, and integrates wireless tools so that the environment to be controlled is monitored from a different place from the location of the production site, through a web page. used two arduino boards, one slave and another master interconnected, the master arduino board controls the brightness sensor, the web interface, the wireless access point to the Wi-Fi network and the Wifly shield; the Arduino slave board controls the temperature sensors, the humidity, the output of the rotor for vents, the electronic valve and the outlet for a fan.

3.9 Robotics

Cebada (2017): Plant tissue culture is the technique of manipulating living plant tissues in a sterile culture medium. This process is performed by taking slices of plant tissue from either leaves or axillary buds as basic cuts. However, there is the possibility of contamination of the samples by human error due to lengthy cuts. Robotic manipulators can help to achieve more efficient cutting of the plant tissue. Nevertheless, the tuning of control algorithms and the parameterization of the system is a difficult task. Thus, a good approach can be the use of a global optimization algorithm to auto-tune the designed controller. In this work, the bio-inspired Cuckoo search algorithm is used for tuning the linear system's dynamic model with three degrees of freedom. It should be noted that using trajectory algorithms, it is necessary to know the fully dynamic model. The Cuckoo's algorithm can estimate indirectly nine parameters of the dynamic model and look for a set of optimal values for them until it finds the function value that satisfies a specified goal. We used the performance index with target function and a saturated PD+ controller where the average of the position errors tends to zero in order to obtain convergence of the model parameters.

Cebada et al. (2016): In vitro culture is constituted by four phases. Cutting is the most important step and where the application of technological advances are important tools to provide the laboratory specialists working with plant tissue. To accomplish this objective, a Cartesian robot of three degrees of freedom was developed using electronic technology using Arduino and programmed with MATLAB GUIDE. The performance of the position control of the Cartesian robot was evaluated using two ways of tuning, the maximum and the method of bio-inspired optimization Seacrh Cuckoo (CS). Mechanical efficiency declines with maximum robot tuning, while the CS adjustment algorithm helps to identify the gains, increasing the mechanical efficiency of the system. The optimized gain values were implemented in the experimental platform which, consisted of the three degrees of freedom robot, an interface designed with MATLAB-GUIDE and the electronics implemented on an Arduino microcontroller.

Reyes (2017): Instrumented a vehicle scaled to measure and apply a control with feedback, using geographical coordinates and GPS, Rover 5 crawler chassis, manufactured by Dagu Electronics, an Arduino one plate, an inertial measurement unit (IMU), a GPS GPS Breakout Version 3 from the company Ada fruit unit, an XBee Module, a XBee USB adapter card, an Arduino Sensor Shield, a H Bridge Circuit.

Romantchik (2016): Developed an automatic system to transport the biological material to the workspaces in the desk, its cutting and deliver it in the growth zone in the in vitro coffee cultivation process. During the execution of the tasks we have developed two robots: one Cartesian with three degrees of freedom and another anthropomorphic with five degrees of freedom. The first was designed to move the cutting tool according to the necessary trajectory, and the second was designed to move the work material to the desk and to the reproduction area. We also design and build mechanical and electrical devices; the control system, which contains position sensors and electromotors. With the video system, the position of the work organ and the cutting material is analyzed. Using mathematical models of movement dynamics, optimized control algorithms were selected so that the work organ reaches a given point of space with a certain speed, as well as the movement of the manipulator for a given trajectory. Technical data of the robots, Figure 1 show developed robots and their elements, Figure 2 show electrical control system of a motor. The basic material for mechanical systems is an aluminum-based alloy.

3.10 Fruit classification and dehydration

Espitia et al. (2014): Presents the Design and construction of three different detection systems and fruit classification (round tomato) based on the average equatorial diameter; this with the intention to compare and determine which of these maintains greater efficiency. To develop the 3 systems, first artificial vision algorithms and the artificial neural network were designed, taking into account the standard NMX-FF-031-1997, which presents the classification for tomato type ball (small, medium, large and extra large). The first one (Matlab) was focused mainly on the analysis of images, so its algorithm was based on some basic operations such as: color separation, binarization, filtering, filling and contour detection. Likewise, the algorithm contains a basic classification method, which uses a separation by means of conditionals. The second system (Matlab), like the previous one, contains a code for the processing of images, as well as incorporating a neural network perceptron monolayer (2 neurons) to achieve its objective. Finally, the algorithm developed in Python language (third system), focuses essentially on artificial vision techniques, the main variations being the processing card in which it was implemented and the library used (Open CV). Once the codes were obtained, they proceeded to acquire results and finally compare them. A prototype conveyor belt was also manufactured to visualize and analyze the types of tomatoes obtained. The Raspberry Pi2 microprocessor and the Arduino Uno microcontroller were used.

Dueñas et al. (2014): Design and implement an infrared dryer for the dehydration of fresh fruit (strawberry, apple, and mango), applying the control architecture corresponding to the control, p (proportional) for the temperature and on * -off control for moisture using an arduino card, in order to control these variables of the process to achieve reduce the amount of water in fruits below 10%, reducing the time of dehydration.

4 Conclusions

From the review of literature made highlights the amount of research work and design proposals for systems based on the Arduino board with application in Indian agriculture, over the other countries in which it is used. Reason why our country should emphasize this application of this low-cost and easy-to-apply technology to raise the productivity of agricultural activities that are so lacking in the current era, as it shows the next graphic in the Figure 3.

Likewise it was found that the Arduino board is used in the different fields of agriculture in Mexico; Irrigation, Livestock Production, Agricultural Machines, Photovoltaic Energy , Biotechnology, Agricultural Education, Agrometeorological , Greenhouses, Robotics, Fruit classification and dehydration.

Acknowledgments

Thanks to the Editorial Board of the International Journal Of Horticulture for cooperation and support for publish this article.

References

Allam T., Raju M., S. Sundeep Kumar, 2016, Design of PID controller for DC Motor Speed Control Using Arduino Microcontroller, International Research Journal of Engineering and Technology (IRJET) Volume: 03 Issue: 09 www. irjet. net

Agricultura, INEGI. 2009, v v. http://cuentame.inegi.org.mx/economia/primarias/agri/default.aspx?tema=E

Agrawal N., Smita Singh, 2015, Smart Drip Irrigation System using Raspberry pi and Arduino, International Conference on Computing, Communication and Automation (ICCCA2015) IEEE

Alfaro G.L.F., Alvarado C.N., 2015, Integración de una red Agrometeorológica en una red Inalambrica, B.Sc. Theses, Chapingo Autonomous University, México

Anschau S.P., 2016, Protótipo de alimentador automático para a larvicultura da tilápia (Oreochromis niloticus) M.Sc, These, Universidade Estadual do Oeste do Parana, Brazil

Arnauts G.C.,2015, Automação no controle de um misturador de água utilizado para higienização de ordenhadeiras bovinas.M.Sc, These, Universidade Estadual do Oeste do Parana, Brazil

Aswini D., S. Santhya, T. Shri Nandheni, N. Sukirthini, 2017, Cattle Health and Environment Monitoring System, International Research Journal of Engineering and Technology (IRJET) 0056 Volume: 04 Issue: 03

Aguilar, O.J., Marquez A., 2015, I Ambientes de aprendizaje para la ciencia usando tecnología Arduino I Simposio sobre Comunicación de la Ciencia y la Tecnología en Latinoamérica. Online in http://somedicyt.org.mx/simposio/images/docs/simposio/2015/memorias/ambientes-de-aprendizaje-para-la-ciencia-usando-tecnologia-arduino.pdf

Baltazar A.J., Enciso H.D., Vargas D.M.A., 2014, Diseño e implementación de un dispositivo digital para  el control de la temperatura en un invernadero de tomate, B.Sc., Thesis, IPN., México

Barrera M.E., Herrero N.R.V., Meraz G.A.R., 2014, Invernadero Inteligente, B.Sc., Thesis, IPN, México

Boopathy S, Ramkumar N., 2012, Controlling the Boiler Temperature of Tea Leaves by using Android Application AND Arduino UNO, International Journal of Modern Computer Science (IJMCS) ISSN: 2320-7868 (Online) Volume 4, Issue 3, http://ijmcs.info

Basnet B., Chun H., Ryu I., Bang J., 2016, Design of A Active RC Filter for Sensors of Monitoring System https://www.kics.or.kr/storage/paper/event/20161119_workshop/publish/7B-4.pdf

Bayir R., Albayrak A., 2016, The monitoring of nectar flow period of honey bees using wireless sensor networks. International Journal of Distributed Sensor Networks, Vol. 12(11). ijdsn.sagepub.com

https://doi.org/10.1177/1550147716678003

Boyu Ji, 2015, An Innovative Portable Monitoring Unit For Air Quality In Animal Housing, M.Sc., Thesis, University of Illinois at Urbana-Champaign, USA

Bhusari K., Shekhar Borulkar, Tejas Patil, Badrinath Danave, 2016, Smart Agro System, International Journal of Research in Advent Technology Special Issue National Conference, “NCPCI-2016”, 19 March Available online at www.ijrat.org

Bhavani D.D., R. Bhashya Sri Bharati, 2016, An Efficient Method to Incorporate Precision Farming in Indian Agriculture Using Robotics and Internet of Things, International Journal of Research in IT & Management . Vol. 6, Issue 9, Available online at : http://euroasiapub.org

Cebada J.G., López-Cruz I.L., Hahn F., Sánchez P. and Romantchik E. 2017. PD+ controller tuning with the Cuckoo search algorithm for a leaf cutter robot, Acta Hortic, 1170, ISHS 2017, DOI 10.17660/ActaHortic, 2017, 1170.74 Proc, Int. Symp. on New Tech. and Mgt. for Greenhouses – GreenSys2015 Eds.: F.J. Baptista, J.F. Meneses and L.L. Silva

Cebada,J.G., Hahn,F. F., Ruiz,A., Romantchik E. and Michua A., 2016, Design of a Position Control Based on Cuckoo Search Tuning for a Cutter Leaves Robot EIEEE LATIN AMERICA TRANSACTIONS, VOL. 14, NO. 5

Celinski V.G., Vinicius de F.F.D., F. de Camargo L., 2014, Evaluation of the use of a Microcontroler of Platform Arduino in Eletrical Sensor Reading For correlation With soil Propierties.Iberoamerican Journal of Applied Computing, V.4, N.2

Cortes R.A., 2015, Diseño de un sistema para control y monitoreo de un invernadero hidropónico.B.Sc., Thesis, IPN. México, D.F.

Corral D.A.H., 2016, Análisis de cobertura y modelado del Consumo energético en una red de sensores, M.Sc., Thesis, IPN. CITEDI, Tijuana, México

Choi Sung-Gi, Ganzorig Chimeddorj, Baljinnyam Altankhuyag, Sarantuya Dunkhorol, 2016, Design and implementation of a GPS-enabled mobile wireless sensor network for livestock herd tracking in Mongolian nomadic herding. Strategic Technology (IFOST), 11th International Forum

Choudhary S., Vijay Kumar, Nishant Dwivedi, Ashish Tiwary, 2017, Smart Water Sprinkler System Based on Arduino . Microcontroller International Journal of Engineering Science and Computing, http://ijesc.org/

Deividson L.O., 2012, SOLUÇÃO ELETRÔNICA MICROCONTROLADA PARA A DETERMINAÇÃO DA DISTRIBUIÇÃO LONGITUDINAL DE SEMENTES DE MILHO. M.Sc., Thesis, UNIVERSIDADE ESTADUAL DE PONTA GROSSA, Brazil

Diniz A.M., 2017, Sistema automatizado de aquisição, em tempo real, de umidade e temperatura do solo na irrigação, Ph.D. These Universidade Estadual do Oeste do Paraná, Brazil

Diaz de J.M.E., Lopéz M.F.J., Montoya G.P., 2014, Sistema de supervisión y control remoto de sensors inalambricos para variables climáticas de un invernadero, a través de la web.B.Sc., Thesis, IPN,México

Dhanshree S. Kale, Dinkar L. Bhombe, Dhiraj P. Tulaskar, 2007, Implementation of Energy Harvesting System Using Soil for Agriculture Parameters Monitoring and Controlling using IOT. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering Vol, 5, Issue 4, April 2017  DOI 10.17148/IJIREEICE.2017.5420  

https://doi.org/10.17148/IJIREEICE.2017.5420

Dueñas R.E., Vidal A. VM., 2016, Diseño e implementación de un secador infrarojo.B.Sc., Thesis IPN., México

Edo D.E., 2013, Wireless Farming: a mobile and Wireless Sensor Network based application to create farm field monitoring and plant protection for sustainable crop production and poverty reduction.M.Sc, Thesis Malmö University, Sweden

Estados Unidos-México Chamber of Commerce (ed.). [http:.//www.usmcoc.org/b-nafta9.php «US-México Agricultura:Una historia de éxito comercial

Electrontools 2016, http://www.electrontools.com/Home/WP/2016/04/20/que-es-y-para-que-sirve-arduino/

Emmanuel A., Pranavan M., Vickram V., Girirajkumar S.M., 2017, Fertilizer Spraying Quadcopter using Arduino UNO IJSTE - International Journal of Science Technology & Engineering Volume 3, Issue 09

Enokela J.A., Theophilus O. Othoigbe, 2015, An Automated Greenhouse Control System Using Arduino Prototyping Platform, Australian Journal of Engineering Research

Espitia P.O., Gonzáles L.I., 2017, Clasificador de tomate redondo aplicando técnicas de visión artificial y redes neuronales artificiales con mathlab y phyton.B.Sc., Thesis, Chapingo Autonomous University, México

Gaona P.B., Chávez A.N., López C.G.de J., 2017, Desarrollo de un sistema de Medición de Humedad del Suelo. Development of a soil Moisture measurement System, Memorias XXV Congreso Nacional de Ingeniería Agrícola. Campo Experimental Pabellón Aguascalientes 11, 12 Y 13 octubre

Gavaskar.S., Simithra A., 2017, Design and Development of Pest Monitoring System for Implementing Precision Agriculture using IOT, International Journal of Science Technology & Engineering Volume 3, Issue 09

Geetha S., Priya R.S., 2016, Smart Agriculture Irrigation Control Using Wireless Sensor Networks, GSM and Android Phone, Asian Journal of Information Technology 15(19):3780-3786

González M.M.Z., 2017, Sistema de riego automatizado Automatized irrigation system, Revista Iberoamericana de Produccion Académica y Gestion Educativa, Vol.4, Núm.8

Hashim N.M.Z., Mazlan S. R., Abd Aziz M.Z.A., Salleh A., Ja’afar A.S., Mohamad N.R., 2015, Agriculture Monitoring System: a Study, Jurnal Teknologi (Sciences & Engineering) 77:1 2015, 53–59

Hirafuji M., Yoichi H., Kiura T., Matsumoto K., Fukatsu T., Tanaka K, Shibuya Y, Itoh A., Nesumi H, Hoshi N., Ninomiya S., Adinarayana J., Sudharsan D, Saito Y., Kobayashi K, Suzuki T, 2011, Creating High-performance/Low-cost Ambient Sensor Cloud System Using OpenFS (Open Field Server) for High-throughput Phenotyping Conference Paper

 Iyappan S., Ramaprabha R., 2017, Design and Implementation of Brushless DC Motor based Solar Water Pumping System for Agriculture using Arduino UNO, International Journal of Engineering and Technology (IJET), Vol 9 No 1. DOI: 10.21817/ijet/2017/v9i1/170901424 https://doi.org/10.21817/ijet/2017/v9i1/170901424

Junior M.M., Nunes O.R., Celinski V.G, 2012, Comparison of the Responses of low cost Eletrical Soil Sensors and a Srduino Mocrocontroler Platform, Iberoamerican Journal of Applied Computing, V. 2, N.1

Junior A.S., Junior M.M., Dias A.H., Mathias I.M., Conti G., 2016, Embedded system in Arduino platform with Fuzzy control to support the grain aeration decision. Sistema embarcado em plataforma Arduino, com controle Fuzzy para suporte a decisão de aeração de grãos.Ciência Rural, Santa Maria, v.46, n.11

Kabir M.H., Ahmed K., Furukawa H., 2016, Sensor Based Low Cost Agriculture Monitoring System Using Polymeric Hydrogel, ECS Transactions, 75 (17)

https://doi.org/10.1149/07517.0049ecst

Kalusea A., Arvind Kadamb, Vishal Patilb, Sharad Dhaged, 2017, Automated Drip Irrigation System, International Journal of Innovative and Emerging Research in Engineering Volume 4, Issue 5

Kote D., Kika A., 2016, Sensor and arduino based monitoring system in Albanian agricultural domain, RTA-CSIT 2016 available in https://pdfs.semanticscholar.org/ba39/dae8df0069734560d63cde142071afd435f8.pdf?_ga=2.223063323.1827985392.1510364515-654805340.1510364515

Koprda S., Magdin M., 2015, New Trends and Developments in Automation in Agriculture.COMPUSOFT, An international journal of advanced computer technology, 4 (2),.Volume-IV, Issue-II

Khan A., Rajoriya V., Swapnil Jain, 2016, Analisys of Irrigation Control System for Agriculture Using Wireless Sensor ZigbeeTechnology.International Journal of Advanced Technology for Science & Engineering Research, www.ijatser.com, Volume 1, Issue 10, WWW.IJATSER.COM

Kumar N., Shimi S. L, 2017, Smart Farming System for Indian Farmers using Arduino based Technology, International Journal of Advance Research, Ideas and Innovations in Technology, www.ijariit.com

Lopez E.B., 2017, Sistema de corte de mazorcas con control automático de posición aplicando vision artificial.M.Sc., Thesis, Chapingo Autonomous University

Lopez V.G., Sanchez A.H.C., 2016, Rediseño de un seguidor solar.B.Sc., Thesis Chapingo Autonomous University, México

Lugo E.O., Villavicencio P.G.A., Díaz L.S.A., 2014, Paquete tecnológico para el monitoreo ambiental en invernaderos con el uso de hardware y software libre, Technological package for monitoring greenhouse environment using open hardware and software .Terra Latinoamericana vol.32 no.1

Lozoya C., Mendoza C, Aguilar A., Román A., Castelló R., 2016, Sensor-Based Model Driven Control Strategy for Precision Irrigation Journal of Sensors Volume 2016, Article ID 9784071, 12 pages  

http://dx.doi.org/10.1155/2016/9784071

Mahajan T., 2016, IOT based agriculture automation with intrusion detection, International Journal of Scientific and Technical Advancements, Volume 2, Issue 4, pp. 269-274

Mahesh B.K., R. Priyakanth, T. Hamsa Priya, K. Harini, M. Harshitha, S.M. Keerti Sree, 2017, Arduino Based Real Time Instrumentation System for Remote Precision Farming, International Journal of Electronics & Communication Technology Vol. 8, Issue 2 www.iject.org

Mahure P.S., Fulsunge Amit, Ingole Kartik, 2017, Enhance Energy Efficient Low Cost WSN System for Precision in Agriculture Zone, International Journal of Advance Research, Ideas and Innovations in Technology, Volume3, Issue3, Available online at www.ijariit.com

Meenakshi M., Snehal S., Kharde Advance., 2016, Cattle Health Monitoring System Using Arduino and IOT, International Journal of Advanced Research in Electrical, Electronicsand Instrumentation Engineering Vol. 5, Issue 4

Nalina K.E., Kaliwal R., 2017, Analysis of Soil Parameters in Agriculture Field Using IoT International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 07

Naik P., Kumbi A., Hiregoudar V., Chaitra N .K., Pavitra H K, Sushma B.S., Sushmita J.H., Kuntanahal P., 2017, Arduino Based Automatic Irrigation System Using IoT, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, IJSRCSEIT Volume 2. Issue 3

Nayyar A., Vikram Puri V., 2016, Smart Farming: IoT Based Smart Sensors Agriculture Stick for Live Temperature and Moisture Monitoring using Arduino, Cloud Computing & Solar Technology, Conference Paper November

https://doi.org/10.1201/9781315364094-121

Narechania A., 2015, Android-Arduino System to Assist Farmers in Agricultural Operations, Proceedings of IRF International Conference, 17th May-2015, New Delhi, India, ISBN: 978-93-85465-15-4

Narechania A., KisanVikas, 2015, Android Based ICT Solution in Indian Agriculture to Assist Farmers. Proceedings of the International Conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2015, Kavala, Greece

Nava T.U., Olguin R.J.C., Rangel S.R., 2017, Diseño y Construcción de un Sistema Inalámbrico para la Detección de Celos en Vacas Lecheras, Memorias XXV Congreso Nacional de Ingeniería Agrícola. Campo Experimental Pabellón Aguascalientes 11, 12 Y 13 octubre

Negrete J.C., 2015 Mechatronics in Mexican Agriculture Current Status and Perspectives .SSRG International Journal of Agriculture & Environmental Science (SSRG-IJAES) – volume 2 Issue 3

Negrete J.C., 2016 Automation of greenhouses in Mexico ,current status  and perspectives . Advance Research in Agriculture and Veterinary Science Volume 3(2)

Negrete J.C., 2017a, Precision Apiculture in Mexico, Current Status and Perspectives, International Journal of Recent Development in Engineering and Technology. Volume 6, Issue 1

Negrete J.C., 2017b, Mechatronics and Precision Livestock Farming in Mexican Animal Production, Animal Review Vol. 4, No. 1, pp. 1-7

https://doi.org/10.18488/journal.ar.2017.41.1.7

Negrete J.C., 2017c, Precision agriculture in Mexico, current status, obstacles and strategies. International Journal of Horticulture, Vol.7, No.10, 75-81

Nirdosh K., L.S. Shimi, 2017, Smart Farming System for Indian Farmers using Arduino based Technology International Journal of Advance Research, Ideas and Innovations in Technology, Volume 3, Issue 1, Available online at: www.ijariit.com

Observatory of Economic Complexity, 2009, MIT Media Lab

Oliveira Júnior, A.J. de, 2016, Dispositivo móvel para análise de conforto térmico e ambiência, Masther These, UNESP, Brazil

Osorio G.R.J.H., 2016, Automatización de  Mezcla de soluciones para Fertorrigación. B.Sc., Thesis, Universidad  Autónoma del Estado de México, Texcoco, Edo, De México, México

Pinto R.W.D., 2015, Monitoreo de cultivos con redes de Sensores XBEE, Arduino, y Dispositivos de Medición de Suelos, B.Sc., Thesis, Universidad Tecnológica de Pereira, Colombia

Ramirez Al.C., 2015, Diseño de un sistema para control y monitoreo de un invernadero hidropónico B.Sc., Thesis, IPN, México

Ramos H.J.N, Facuy D.J.P., 2017, Arduino, abriendo la llave al campo agrícola en dosificaciones correcta de abono al cultivo de tomate, Revista Observatorio de la Economía Latinoamericana, Ecuador, En línea:http://www.eumed.net/cursecon/ecolat/ec/2017/arduino-cultivo-tomate.html

Rashid H., Iftekhar Uddin Ahmed, S M Taslim Reza, M. A. Islam, 2017, Solar Powered Smart Ultrasonic Insects Repellent with DTMF and Manual Control for Agriculture. Imaging, Vision & Pattern Recognition (icIVPR), 2017 IEEE International Conference on, DOI: 10.1109/ICIVPR.2017.7890869

https://doi.org/10.1109/ICIVPR.2017.7890869

Raut P., Pradip Shirwale, Abhijeet Shitole , Murade R.T., 2016, A Survey on Smart Farmer Friendly Robot Using Zigbee. International Journal of emerging technology and computer science.Volume: 01, Issue: 01 Available @www.aspirepublishers.com

Reyes M.J., Rodriguez A.N., 2017, Vehículo Autónomo para Exploración de Campos Agrícolas Utilizando Sistema de Posicionamiento Global (GPS), B.Sc., Theses, Chapingo Autonomous University

Rekha Ms.G., M.E.S. Muthu Selvi, 2017, Android Arduino Interface with Smart Farming System, International Journal of Engineering and Computer Science ISSN:2319-7242 Volume 6 Issue 3 March 2017, Page No. 20521-20526 DOI: 10.18535/ijecs/v6i3.22

https://doi.org/10.18535/ijecs/v6i3.22

Rekha P., T. Saranya, P. Preethi, L. Saraswathi, G. Shobana, 2017, Smart AGRO Using ARDUINO and GSM, International Journal of Emerging Technologies in Engineering Research (IJETER) Volume 5, Issue 3. www.ijeter.everscience.org

Rodríguez S.M.A., 2016, Estudio de la mecánica de fluidos y los efectos de un hidrociclón en el crecimiento de la microalga Scenedesmus incrassatulus, M.Sc., Thesis, IPN, México

Rodrigues L.M., Dimuro G.P., Franco D.T., Fachinello J.C., 2013, An Interval Fuzzy Logic-Based System to Predict Pests in Agriculture online, http://www.lbd.dcc.ufmg.br/colecoes/wcama/2013/002.pdf

Romantchik E., Cebada G., Hahn F., López Cruz I., 2016.Pазработка системы из двух робот для подготовки биологического материала in vitro. (Development of a System of two Robots for the Preparation of Biological material in vitro) .Biotechnology in fruit growing: proceedings of the International Scientific Conference (Samokhvalovichy, 13-17 June, 2016). Bielorusia. 220p

Satish T., Bhavani T., Begum S., 2017, Agriculture Productivity Enhancement System using IOT, International Journal of Theoretical and Applied Mechanics, ISSN 0973-6085 Volume 12, Number 3. http://www.ripublication.com

Sawashe.T.A., Mirshikari A.A., Mulla S.M., Ghorpade S.R., 2013, Water Pump Monitoring and Controlling Using Arduino Asian Journal of Convergence in Technology Volume III, Issue I

Salazar R., Rangel J.C., Pinzón C., Rodríguez A., 2013, Irrigation System through Intelligent Agents Implemented with Arduino Technology,Advances in Distributed Computing and Artificial Intelligence Journal DOI: 10.14201/ADCAIJ2014262936

Salunke A., Ramani S., Singh D., Yadav A., Santosh Mishra., 2016, Development of a Prototype of a solar Powered Ploughing Robot IJRET: International Journal of Research in Engineering and Technology Volume: 05 Special Issue: 13 Available http://www.esatjournals.org

Sandoval J.T., 2017, Desarrollo de un  Sistema Mecatrónico para el Control de los Dosificadores de Semilla, Fertilizante y Pesticida de una Sembradora – Fertizadora.Ph.D., Thesis, Chapingo Autonomous University

Sanz A, Nduino, 2017, Low cost vegetal index meter with Arduino for Precision Agriculture, http://www.parajeinnova.com/nduino-low-cost-vegetal-index-meter-with-arduino/

Siththtikumar N., Maduranga M.W.P., 2016, Designing and Implementing an Arduino Based Low Cost Automated Water Irrigation System for Home Gardens, International Research Symposium on Engineering Advancements SAITM, Malabe, Sri Lanka

Sahitya G., N. Balaji, C.D Naidu, 2016, Prototyping of Wireless Sensor Network for Precision Agriculture, International Journal on Cybernetics & Informatics (IJCI) Vol. 5, No. 4, August 2016

Saha M.K.H.T., Jewel M.N., Mostakim N.H., Bhuiyan M.S.A. and M.K. Rahman, 2017, Construction and Development of an Automated Greenhouse System Using Arduino Uno, I.J., Information Engineering and Electronic Business, 2017, 3, 1-8

https://doi.org/10.5815/ijieeb.2017.03.01

Simanjuntak P.P., Napitupulu P.T., Silalahi S.P., Pasaribu K.N., Valešová L., 2017, E-precision agriculture for small scale cash crops in Tobasa regency, 1st Nommensen International Conference on Technology and Engineering IOP Publishing IOP Conf. Series: Materials Science and Engineering 012034 doi:10.1088/1757-899X/237/1/012034

https://doi.org/10.1088/1757-899X/237/1/012034

Sumarudin A., Ghozali A.L., Hasyim A., Effendi A., 2016, Implementation monitoring temperature, humidity and mositure soil based on wireless sensor network for e-agriculture technology, International Conference on Innovation in Engineering and Vocational Education IOP Publishing IOP Conf. Series: Materials Science and Engineering 128, doi:10.1088/1757-899X/128/1/012044  

https://doi.org/10.1088/1757-899X/128/1/012044

Susanto D., Kudang Boro Seminar, Heru Sukoco, Liyantono, 2017, Parallel Processing Implementation on Weather Monitoring System for Agriculture, Indonesian Journal of Electrical Engineering and Computer Science, Vol. 6, No. 3, pp 682 ~ 687

Sheroz M. H.S., 2016, Auto Irrigation Using Arduino. B.Sc., Thesis, Munbai University, India

Vajpayee S., Baban Kumar, Ritula Thakur, Manish Kumar, 2017, Design and Development of Nano pH Sensor and Interfacing with Arduino, International Journal of Electronics, Electrical and Computational System IJEECS ISSN 2348-117X, Volume 6, Issue

Veloso Gustavo Vieira, 2013, Automação do sistema de direção de uma colhedora de café, M.Sc., These, Universidade Federal de Viçosa, Brazil.

World Bank, 2015, https://datos.bancomundial.org/indicador/NV.AGR.TOTL.ZS?locations=MX

Yilmaz M., 2017, Arduino Based Automation in the Soiless Agriculture.Proceedings of 65th ISERD International Conference, Mecca, Saudi Arabia, 23rd-24th, ISBN: 978-93-86291-92-9

Zalta E.N. (ed.), México, Enciclopedia Británica en línea, 2012 edition

Zachariadis S., Kaskalis T.H., 2012, An Embedded System for Smart Vineyard Agriculture, 2nd Pan-Hellenic Conference on Electronics and Telecommunications - PACET΄12, March 16-18, 2012, Thessaloniki, Greece

Zografos, A., 2014, Wireless Sensor-based Agricultural Monitoring System, Master’s Thesis, School of Information and Communication Technology (ICT) KTH Royal Institute of Technology Stockholm, Sweden