Spatial variability of some biometricattributes of sugarcane plants (variety IACSP93-3046) and its relation to physical and chemical soil attributes

Abstract

Tests to evaluate competition between plants, in general do not consider the soil spatial variability, nevertheless, the uniformity rarely is present and can not be assumed without verification. The aim of this work was to apply geostatistics to verify the spatial variability of the soil in an experimental field near Ribeirão Preto, SP, with sugarcane variety IACSP93-3046. Ninety seven geo-referenced samples, placed at distances of 10 m, were collected for soil chemical analysis, soil resistance to penetration and biometric evaluation of the sugar cane plant included number of tillers, stalk diameter, stalk height, estimated productivity (TSSe) and root density. Geostatistics has been applied by means of semivariogram, data interpolation via kriging and iso-line maps creation. The results have shown soil spatial dependence for most of the evaluated attributes. The spots, within the area, with low resistance to penetration and low soil density have shown the largest number of tillers and the largest root development of sugar cane. For soil chemical attributes, there was spatial dependence showing higher concentration of nutrients in the central area. The sampling allowed a good representativity of the spatial dependence of soil and plants, making it possible to eliminate the randomness hypothesis for the placement of the plots in this area.

Variability and Spatial Correlation between Phenotypic Attributes and Productivity of Papaya

“…The coefficients of asymmetry and kurtosis close to zero for most of the evaluated attributes of papaya, as well as the proximity of the mean and median values, indicate that the variables studied to follow the normal distribution, a fact confirmed by the Kolmogorov-Smirnov test (P = .05) (Table 1). These data are in accordance with the data presented by Grego, Vieira and Xavier [10] and Kitamura, et al [28].…”

“…Of the attributes studied, 45.5% adjusted to the exponential model of the semivariogram, 27.3% to the spherical model and 9.0% to the Gaussian model. In the work of spatialization of plant attributes, it is common to find semivariogram adjustment to the exponential and the spherical models [10,17,36].…”

“…But, these relationships may vary according to the genetic nature of the cultivar, the soil and climatic conditions and the management adopted in the crop [9]. In particular, the spatial variability and correlations of these variables in the field, as studied in other cultures [10,11,12].…”

“…One way to study the spatial variability of agronomic variables is to use geostatistical analysis, a technique widely used in agrarian sciences, which allows the acquisition of information about the spatial and temporal distribution and the relationship of the variables in the field [10]. Several studies show the importance of considering the spatial variability in the field and the gain of information with the use of geostatistics as a tool in this type of study [13,14,15,16], including in the cultivation of papaya [17,18].…”

Using GIS and Geostatistics to Monitoring Spatial Variability in Soil Chemical Properties Impacted by Cultivation Practices

“…The pH values showed low CV (Table 2) since it is considered to be the log-transformed H + concentration. Similar findings were reported by Grego et al, (2010), who discovered that pH had the lowest CV (3.5%) and the low variation. In all sampling periods and both locations, pH was the only one with minimal change (Castro et al, 2016).…”