Abstract
In order to make effective decisions on sustainable development, it is essential for sugarcane-producing countries to take into account sugarcane acreage and sugarcane production dynamics. The availability of sugarcane biophysical data along the growth season is key to an effective mapping of such dynamics, especially to tune agronomic models and to cross-validate indirect satellite measurements. Here, we introduce a dataset comprising 3,500 sugarcane observations collected from October 2014 until October 2015 at four fields in the São Paulo state (Brazil). The campaign included both non-destructive measurements of plant biometrics and destructive biomass weighing procedures. The acquisition plan was designed to maximize cost-effectiveness and minimize field-invasiveness, hence the non-destructive measurements outnumber the destructive ones. To compensate for such imbalance, a method to convert the measured biometrics into biomass estimates, based on the empirical adjustment of allometric models, is proposed. In addition, the paper addresses the precisions associated to the ground measurements and derived metrics. The presented growth dynamics and associated precisions can be adopted when designing new sugarcane measurement campaigns.
Highlights
Background & SummarySugarcane is the number one crop worldwide in terms of production quantity
During the first growth stages of the sugarcane, until approximately two meters stalk height, the leaf area index (LAI) measurements are taken from the middle of the Elementary Sampling Units (ESU) in four different directions with one abovecanopy measurement followed by three below-canopy measurements; two times in cross-row direction and two times in along-row direction, see Fig. 5
Cane biomass equation In order to estimate the biomass at ESU we propose a biomass estimation equation, which is based on the sum of stalk biomass and leaf biomass: BMC 1⁄4 BMS þ BML
Summary
Sugarcane is the number one crop worldwide in terms of production quantity. It provides for more than 40% of the car fuel in the largest sugarcane producing nation, Brazil. The campaign addressed two additional needs: that of minimizing the measurements' effects on the remote sensing signals and that of maximizing efficiency in terms of costs Both demands led to the limitation of the destructive biomass procedures. The selection of the surveying locations and the data collection and processing procedures will be explained in the sec:Methods section. Based on high-resolution optical images one should select those ESU locations for which the difference in biophysical parameter is expected to be statistically significant within the fields of interest. The proposed techniques as explained in this paper can be used
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