TY - GEN
T1 - Advances in Structured Light Sensors Applications in Precision Agriculture and Livestock Farming
AU - Rosell-Polo, Joan R.
AU - Auat Cheein, Fernando
AU - Gregorio, Eduard
AU - Andújar, Dionisio
AU - Puigdomènech, Lluís
AU - Masip, Joan
AU - Escolà, Alexandre
N1 - Funding Information:
This work was partially funded by the Spanish Ministry of Science and Innovation by the SAFESPRAY Project (AGL2010-22304-C04-03); the Mecesup FSM1204-UTFSM, FONDECYT 1140575 (Chile) project.
Publisher Copyright:
© 2015 Elsevier Inc.
PY - 2015
Y1 - 2015
N2 - The sustained growth of the world's population in the coming years will require an even greater role for agriculture to meet the food needs of humankind. To improve the productivity and competitiveness of the agricultural industry, it is necessary to develop new and affordable sensing technologies for agricultural operations. This kind of innovations should be implemented in a framework considering the farm the crops, and their surroundings, with the aim of providing the farmer with information to take better decisions to enhance the production. This is the case of precision agriculture and precision livestock farming. This chapter reviews and discusses the use of structured light sensors in the characterization and phenotyping of crops in orchards and groves, weeds, and animals. As a result of a collaboration between researchers from Spain and Chile, opportunities for this type of sensors have been identified in these countries as examples of South American and European agriculture. In this context, several empirical case studies are presented regarding the use of structured light sensors for flower, fruit, branch, and trunk characterization considering depth and RGB (red-green-blue colors) information in avocados, lemons, apple, and pear orchards. Applications to weed detection and classification as well as to livestock phenotyping are also illustrated. Regarding the presented case studies, experimental and statistical results are provided showing the pros and cons of structured light sensors applied to agricultural environments. Additionally several considerations are included for the use of this type of sensors to improve the agricultural process.
AB - The sustained growth of the world's population in the coming years will require an even greater role for agriculture to meet the food needs of humankind. To improve the productivity and competitiveness of the agricultural industry, it is necessary to develop new and affordable sensing technologies for agricultural operations. This kind of innovations should be implemented in a framework considering the farm the crops, and their surroundings, with the aim of providing the farmer with information to take better decisions to enhance the production. This is the case of precision agriculture and precision livestock farming. This chapter reviews and discusses the use of structured light sensors in the characterization and phenotyping of crops in orchards and groves, weeds, and animals. As a result of a collaboration between researchers from Spain and Chile, opportunities for this type of sensors have been identified in these countries as examples of South American and European agriculture. In this context, several empirical case studies are presented regarding the use of structured light sensors for flower, fruit, branch, and trunk characterization considering depth and RGB (red-green-blue colors) information in avocados, lemons, apple, and pear orchards. Applications to weed detection and classification as well as to livestock phenotyping are also illustrated. Regarding the presented case studies, experimental and statistical results are provided showing the pros and cons of structured light sensors applied to agricultural environments. Additionally several considerations are included for the use of this type of sensors to improve the agricultural process.
UR - http://www.scopus.com/inward/record.url?scp=84943360523&partnerID=8YFLogxK
U2 - 10.1016/bs.agron.2015.05.002
DO - 10.1016/bs.agron.2015.05.002
M3 - Conference contribution
AN - SCOPUS:84943360523
SN - 9780128030523
T3 - Advances in Agronomy
SP - 71
EP - 112
BT - Advances in Agronomy 2015
A2 - Sparks, Donald L.
PB - Academic Press Inc.
ER -