Fri. May 24th, 2024

Ata is usually grouped into two distinct subsets separated by a
Ata is often grouped into two distinct subsets separated by a boundary. The precise location of this boundary was calculated together with the Kmeans clustering algorithm (see beneath) and is located at about 45 kg in the olive production histogram. The corresponding boundary for the oil production histogram was of 15 ob8 tained thinking of the average yield reported in Table 3 and includes a value of roughly eight litres.Figure 2. Major -from left to right- olive productivity histogram for the 4 regions in the orchard Figure 2. Best -from left to right- olive productivity histogram for the 4 regions of your orchard (yellow, green, blue and red). Bottom, from left toto appropriate, oil productivity histogram the the 4 re(yellow, green, blue and red). Bottom, from left appropriate, oil productivity histogram for for 4 regions gions from the orchard (yellow, green, blue and red). The dashed lines represent the boundaries beof the orchard (yellow, green, blue and red). The dashed lines represent the boundaries between the tween the loading year and unloading year area of your plot, calculated with the k-means algoloading year and unloading year region on the plot, calculated together with the k-means algorithm. rithm.3.two. Leaf Region and D-Fructose-6-phosphate disodium salt Technical Information Canopy radius Estimate from kNN Image Segmentation three.two. Leaf Area and Canopy Radius Estimate from kNN Image Segmentation As a way to predict the total production of a area with the orchard, it is actually important to As a way to a measurable quantity. The affordable measurable parameters considered correlate it with predict the total production of a region with the orchard, it can be required to correlate it with and the canopy radius. Indeed, 1 expects “on average” larger plants to are the leaf area a measurable quantity. The affordable measurable parameters considered are far more olives. The basis of this assumption is thatone density of olives (olive weight make the leaf location and the canopy radius. Indeed, the expects “on average” larger plants to by the canopy volume) is spherically symmetric and it does not decreaseolives divided generate extra olives. The basis of this assumption is the fact that the density of quicker (olive (R/Rmax )-3 . Given the age of the orchardis spherically symmetric and it the above than weight divided by the canopy volume) and its agronomic circumstances, does not decrease quicker thanto be max)-3. Givenand was on the orchard and its agronomic conditions, assumption seems (R/Rreasonable the age verified a posteriori (see Figures 4 and five). The the above assumption seems to become affordable and was verified agood estimation of plant use of modern technologies, particularly UAV Tenidap medchemexpress orthophotos, makes it possible for posteriori (see Figures 4 and five). The usesuch as the normalized difference vegetation index (NDVI), leaf area,estiDrones 2021, five, x FOR PEER Assessment 9 of qualities of modern technologies, especially UAV orthophotos,16allows very good and mation of plant qualities suchthe the normalizedcould be even manually identified on canopy volume [14]. In particular, as canopy radius difference vegetation index (NDVI), the orthophoto and measured when compared with the image size. The canopy radius along with the leaf leaf areaarea, and canopy volume [14]. In specific, the canopy radiusthe automated method described in estimates have been simultaneously obtained adopting may be even manually identified on the orthophoto and measured in comparison with the image size. The canopy Section two the leaf location estimates had been simultaneously obtained adopting the automated rad.