EditorialSensors in Precision Agriculture for the Monitoring of PlantDevelopment and Improvement of Food Production

José A. Padilla-Medina ,1 Luis M. Contreras-Medina,2 Miguel U. Gavilán ,3

Jesus R. Millan-Almaraz,4 and Juan E. Alvaro5

1Celaya Institute of Technology, Guanajuato, Mexico2Autonomous University of Queretaro, Queretaro, Mexico3Universidad de Almerıa, Almerıa, Spain4Autonomous University of Sinaloa, Sinaloa, Mexico5Pontificia Universidad Catolica de Valparaıso, Valparaıso, Chile

Correspondence should be addressed to Jose A. Padilla-Medina; alfredo.padilla@itcelaya.edu.mx

Received 11 June 2019; Accepted 18 June 2019; Published 30 July 2019

Copyright © 2019 Jose A. Padilla-Medina et al. �is is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

�e importance of integrating technology into precisionagriculture that allows the monitoring of plants and cropsin order to obtain higher quality food together with anincrease in production is fundamental. �is importance isdue to various factors such as climate change, food shortages,innocuousness factors, efficiency in fooddistribution, and thegrowth of the world population; the impact of these factorscan be mitigated or reduced with the use of sensors that canhelp to generate the conditions for an optimal growth anddevelopment of crops and plants. �e purpose of this specialissue is to provide a scientific link that promotes the exchangeof knowledge related to the use of sensors for the integrationof technology in precision agriculture.

�is special edition contains eight research articlesaccepted for publication aer 2 or 3 review processes.

In the research article “A Preliminary Study of SeedingAbsence Detection Method for Drills on the Soil Surfaceof Cropland Based on Ultrasonic Wave without Soil Dis-turbance”, C. Lu et al. propose the uses of one transmit-ting transducer and one receiving sensor to achieve anaccurate seeding-absence measurement on the soil surface;the seeding-absence states are defined by a circle energyinside the tilled soil above seed layer or untilled soil layer.�e authors used the Zhibolian 5200 ultrasonic detectioninstrument to obtain the ultrasonic information and theproposed method does not need to remove the soil covered

on seeds and does not damage the seedlings. �e authorsconclude that method has the advantages of nondestructivemeasurement with the latest position of seeds immediatelyaer seeding considering two states of seeds depth (25mmand 30mm).

In the research article “Detection of Apple Lesions inOrchards Based on Deep Learning Methods of CycleGANand YOLOV3-Dense”, Y. Tian et al. propose an anthracnoselesions detection method based on YOLO-V3 deep learningand DenseNet. �e authors confirmed a dataset of 140anthracnose apple images and used CycleGAN to learn thefeatures of apple lesions images and transplanted to healthyapple images and 500 healthy apple images. �e authorsconclude that the classification performance of the proposedmethod, compared with several state-of-art deep learningmethods, presents the highest detection accuracy (95.57%).

In the research article “Fuzzy-Classification of the Matu-rity of the Tomato Using a Vision System”, M. J. Villasen∼or-Aguilar et al. report the behavior of tomato maturity basedon color in the RGBmodel; the tomato images were obtainedusing a Camera Module Raspberry Pi 2; the average valueof the color components of four views of the tomato is theinput variables of the Fuzzy System implemented in MAT-LAB which classified the tomato samples into six categoriesaccording to the U.S. Department of Agriculture.�e authorsconcluded that their purposes are a good alternative to

HindawiJournal of SensorsVolume 2019, Article ID 7138720, 2 pageshttps://doi.org/10.1155/2019/7138720

2 Journal of Sensors

evaluate thematurity of tomatoes; this conclusion is based onthe average error of 536.995 x 10−6.

In the research article “Nondestructive Quantificationof the Ripening Process in Banana (Musa AAB Simmonds)Using Multispectral Imaging”, M. Santoyo-Mora et al. pro-pose a nondestructive technique based on the processing ofmultispectral images to evaluate the ripening process of abanana (Musa AAB Simmonds) at the seventh stage of thegrowing process. �e results were obtained using a set ofmultispectral imagery registered in a range of 270-1000 nm;the images were analyzed with three different techniques:Fourier fractal analysis; Hotelling transform; and cooccur-rence matrix. �e authors found that the analysis based onthe cooccurrence matrix gave the best results; this methodhas the following advantages: it does not require complexcalculations; it is rotational invariant; and the homogeneityindex has relatively low variations.

In the research article “Peanut Detection Using DropletMicrofluidic Polymerase Chain Reaction Device”, S.-Y. Maet al. propose the development of a droplet microfluidicPCR device to amplify specific peanut DNA fragments fordetection of foodborne allergens. �e authors used a cross-junction microchannel to induce emulsion droplets of waterin oil for PCR on a chip which presents a 7.24% lower amountof evaporation amount prevented air bubble generation. �edeveloped device was also successfully used to amplify DNAfor various species, including sesame, Salmonella spp., andStaphylococcus aureus.

In the research article “Technology Roadmapping Archi-tecture Based on Knowledge Management: Case Study forImproved Indigenous Coffee Production from Guerrero,Mexico”, D. I. Contreras-Medina et al. make a proposalto improve indigenous coffee production from Guerrero,Mexico. Based on knowledge management and technologyroadmapping architecture, the authors identify the green-houses and the knowledge and technology managementnetworks as best strategies to be implemented, selected by thelocal coffee producers of ParajeMontero and Tierra Coloradafrom Guerrero, Mexico. From this, the use of emergingtechnologies for greenhouse in the stages of cultivation andgrowth according to indigenous coffee producer’s selection isproposed, supported on the design ofmanagement networks.

In the research article “A Benchmarking of LearningStrategies for Pest Detection and Identification on TomatoPlants for Autonomous Scouting Robots Using InternalDatabases”, A. Gutierrez et al. present the comparison oftwo different approaches for pest detection on tomato plantsbased on learning strategies. A solution that combines com-puter vision andmachine learning is compared against a deeplearning solution. �e authors conclude that deep learningtechnique is a better solution than the combination betweencomputer vision and machine learning; this conclusion isbased on the analysis of 4,331 original pictures convertedinto 54,743 images of different insect and eggs of Trialeurodesvaporariorum and Bemisia tabaci.

In the research article “An Approach of Beans PlantDevelopment Classification Using Fuzzy Logic”, P. Correa etal. present a method to monitor the growth of bean plants

from images taken (with controlled background and lighting)in their vegetative phase with a diffuse system that classifiesthese stages based on the extracted characteristics: averageand standard deviation of the area of the plant in pixels. Itwas found that the artificial vision system can identify thestages; the vegetative phase: emergence, primary leaves, andfirst trifoliate leaf.

Conflicts of Interest

�e authors declare that they have no conflicts of interest.

Jose A. Padilla-MedinaLuis M. Contreras-Medina

Miguel U. GavilanJesus R. Millan-Almaraz

Juan E. Alvaro

International Journal of

AerospaceEngineeringHindawiwww.hindawi.com Volume 2018

RoboticsJournal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Active and Passive Electronic Components

VLSI Design

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Shock and Vibration

Hindawiwww.hindawi.com Volume 2018

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwww.hindawi.com

Volume 2018

Hindawi Publishing Corporation http://www.hindawi.com Volume 2013Hindawiwww.hindawi.com

The Scientific World Journal

Volume 2018

Control Scienceand Engineering

Journal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com

Journal ofEngineeringVolume 2018

SensorsJournal of

Hindawiwww.hindawi.com Volume 2018

International Journal of

RotatingMachinery

Hindawiwww.hindawi.com Volume 2018

Modelling &Simulationin EngineeringHindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawiwww.hindawi.com Volume 2018

Hindawiwww.hindawi.com Volume 2018

Navigation and Observation

International Journal of

Hindawi

www.hindawi.com Volume 2018

Advances in

Multimedia

Submit your manuscripts atwww.hindawi.com