Coefficient of Variation from Vegetation Index for Sugarcane Population and Stalk Evaluation

Abstract

Core Ideas• Variety and planting material affect cane population and millable stalk production.• Coefficient of variation from sensor readings decreases as cane canopy closes.• Cane varieties for sugar and energy production differ greatly in canopy structure.• Canopy structure influences sensor-based profiling of cane population and stalk. ABSTRACT Coefficient of variation (CV) is a statistical measure of variability in data. This study was conducted to evaluate the relationship of CV computed from Vegetation Indices (VIs) with plant population and millable stalk of different sugarcane (Saccharrum spp.) varieties. Two experiments consisted of six cane varieties and two types of planting material (whole stalks vs. billets) with four replications arranged in a split plot in randomized block design were established in St. Gabriel, LA, in 2012 and 2013. Sensor readings were concurrently collected with plant population at 4 and 8 weeks after planting (WAP) and tiller count at early and late tillering stage. Variety had a more evident, consistent effect than planting material on population count, tiller number, and millable stalk (p < 0.001). The regression analysis revealed: (i) a positive linear relationship between NDVI 660 and CV 660 with coefficient of determination (r 2 ) of 0.49*** at 4 WAP, then changed to negative linear at 8 WAP and early tillering stage with r 2 values of 0.52*** and 0.75***, respectively; and (ii) CVs and VIs from the red-edge band had consistently negative linear relationships (p < 0.001), the strongest being at the early tillering stage (r 2 = 0.61-0.73). The linear relationship of CV with plant population and millable stalk improved when variety was included as categorical variable.Future research should focus to categorize varieties into broader group based on canopy structure to develop more refined CV-based model for fast profiling of cane plant stand population, tiller production, and millable stalk.

Seasonal variations of vegetative indices and their correlation with evapotranspiration and soil water storage in a small agricultural catchment

“…Subsequently, spatial variance also gradually increased during autumn and winter after crop harvesting. This inverse relationship between the spatial variability (CV) of VIs and VIs values was consistent with previous findings (Martin et al 2007;Chanda et al 2018).…”

Causation between Agronomic Traits in Homozygous Soybean Lines

“…The results of the analysis of variance showed significant variation in the seed yield and yield components of 150 soybean genotypes (Table 1). The high coefficient of variation (CV) indicated much variability in data [27] among HLs, particularly in the characters of the number of branches, in the number of empty pods, and in wet and dry biomass. ** = significant at 1 % probability level (P < 0.01), * = significant at 5 % probability level (P < 0.05), ns = not significant, CV = coefficient of variation, HS = 100 seed weight (g), FD = days to flowering, MD = days to maturity, G/V = generative/vegetative ratio, PH = plant height (cm), NB = number of branches/plant, NN = number of nodes/plant, FP = number of filled pods/plant, EP = number of empty pods/plant, WB = wet biomass (t/ha), DB = dry biomass (t/ha), HI = harvest index, S/P = weight of seed/plant (g).…”

A simplified approach to satellite-based monitoring system of sugarcane plantation to manage yield decline at Wonji-Shoa Sugar Estate, central Ethiopia

“…The differences observed among cane varieties were also noticed in the conventional method of satellite data processing. For instance, Lofton et al [ 86 ] and Chanda et al [ 87 ] corroborated that spectral reflectance can vary among varieties due to differences in canopy architecture. The three varieties considered in the current study varied considerably in their morphology [ 38 ], which could explain the observed differences.…”