TY - JOUR
T1 - A survey of ranging and imaging techniques for precision agriculture phenotyping
AU - Yandún Narváez, Francisco
AU - Reina, Giulio
AU - Torres-Torriti, Miguel
AU - Kantor, George
AU - Cheein, Fernando Auat
N1 - Funding Information:
Manuscript received August 2, 2016; revised January 20, 2017 and August 29, 2017; accepted October 1, 2017. Date of publication October 8, 2017; date of current version December 13, 2017. Recommended by Technical Editor X.-T. Yan. This work was supported in part by the National Commission for Scientific and Technological Research of Chile under Grant CONICYT-PCHA/Doctorado Nacional/2015-21150694, Grant FONDECYT Grant 1140575, Basal Grant FB0008, Grant DGIP-UTFSM, and in part through Simultaneous Safety and Surveying for Collaborative Agricultural Vehicles under Grant FP7 ERA-NET ICT-AGRI II. (Corresponding author: Francisco Yandun Narvaez.) F. Yandun Narvaez and F. Auat Cheein are with the Advanced Center of Electrical and Electronic Engineering, Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso V-110, Chile (e-mail: [email protected]; fernando. [email protected]).
Funding Information:
The financial support of the FP7 ERA-NET ICT-AGRI II through the grant Simultaneous Safety and Surveying for Collaborative Agricultural Vehicles (S3-CAV) is gratefully acknowledged.
Publisher Copyright:
© 1996-2012 IEEE.
PY - 2017/12
Y1 - 2017/12
N2 - Agricultural production must double by 2050 in order to meet the expected food demand due to population growth. Precision agriculture is the key to improve productivity and efficiency in the use of resources, thus helping to achieve this goal under the diverse challenges currently faced by agriculture mainly due to climate changes, land degradation, availability of farmable land, labor force shortage, and increasing costs. To face these challenges, precision agriculture uses and develops sensing methodologies that provide information about crop growth and health indicators. This paper presents a survey of the state-of-the-art in optical visible and near-visible spectrum sensors and techniques to estimate phenotyping variables from intensity, spectral, and volumetric measurements. The sensing methodologies are classified into three areas according to the purpose of the measurements: 1) plant structural characterization; 2) plant/fruit detection; and 3) plant physiology assessment. This paper also discusses the progress in data processing methods and the current open challenges in agricultural tasks in which the development of innovative sensing methodologies is required, such as pruning, fertilizer and pesticide management, crop monitoring, and automated harvesting.
AB - Agricultural production must double by 2050 in order to meet the expected food demand due to population growth. Precision agriculture is the key to improve productivity and efficiency in the use of resources, thus helping to achieve this goal under the diverse challenges currently faced by agriculture mainly due to climate changes, land degradation, availability of farmable land, labor force shortage, and increasing costs. To face these challenges, precision agriculture uses and develops sensing methodologies that provide information about crop growth and health indicators. This paper presents a survey of the state-of-the-art in optical visible and near-visible spectrum sensors and techniques to estimate phenotyping variables from intensity, spectral, and volumetric measurements. The sensing methodologies are classified into three areas according to the purpose of the measurements: 1) plant structural characterization; 2) plant/fruit detection; and 3) plant physiology assessment. This paper also discusses the progress in data processing methods and the current open challenges in agricultural tasks in which the development of innovative sensing methodologies is required, such as pruning, fertilizer and pesticide management, crop monitoring, and automated harvesting.
KW - Advanced sensing in agriculture
KW - Fruit detection
KW - Morphology characterization
KW - Phenotyping
KW - Physiology assessment
KW - Precision agriculture
UR - http://www.scopus.com/inward/record.url?scp=85031799403&partnerID=8YFLogxK
U2 - 10.1109/TMECH.2017.2760866
DO - 10.1109/TMECH.2017.2760866
M3 - Review article
AN - SCOPUS:85031799403
SN - 1083-4435
VL - 22
SP - 2428
EP - 2439
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
IS - 6
ER -
