Abstract
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.
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