Statistical Control of Processes Aplied for Peanut Mechanical Digging in Soil Textural Classes

Abstract

Thedigging of peanut, which has the pod production in the subsurface, is directly affected by soil conditions, physical or environmental characteristics, at the time of operation and may be the cause of unwanted losses. Therefore, the quality of the operation is very important for minimizing these losses. Thus, this study aimed to evaluate the quality of mechanizeddiggingoperation of peanut according to three soil textural classes(Sandy, Medium and Loamy) and their water content conditions at operation through statistical process control. The experiment was conducted at three locations in the state of São Paulo, Brazil, under sampling scheme arranged in tracks and 40 sampling points for each textural class of soil, using the mechanical digging variables as indicators of quality. We found that the mechanized digging operation in Sandy soil was the most critical, just meeting the specifications of quality indicators, reflecting higher losses and lower quality of the operation. Medium soil showed at the digginggood and homogeneous conditions in relation to water content in soil and pods, and because it has favorable characteristics it obtained the lower total losses and higher quality of operation. Loamy soil showed satisfactory quality, meeting the specifications as well, but with poorer quality than the Medium Soil.

Multivariate Analysis of Peanut Mechanized Harvesting

“…The x-axis (PC1) shows the contrasts of the six soil classes, three textural classes (VCL, CLA, and CLL) to the right and two (SAN and SAL) to the left, and the centralized intermed iate behavior (SCL). The y-axis (PC2) shows a high direct correlation between the visible losses and windrow height, explained by the adjustment of align ment rolls and inverters of branches together with the plant mass being processed directly interfering with the windrow dimensions in the digging process (Zerbato et al, 2017). Table 5 shows the variables with higher discriminatory power in the first principal co mponent that had direct correlations between YLD, MAT, VDL, IDL, and GAL, enabling an efficient multivariate approach to mechanized harvesting of peanuts.…”

Parameters affecting the mechanical digging of peanut crops from three different shaped plots

“…These methods, coupled with quality analysis tools, can help the decisionmaking process. The quality analysis tools (Statistical Process Control) have been used to monitor the quality of the operation by several authors (Barros and Milan, 2010;Noronha et al, 2011;Cassia et al, 2013;Ormond et al, 2016;Zerbato et al, 2017). However, only Tavares et al (2015) and Paixão et al (2017) used SPC as a tool for managing the quality of the agricultural operation coupled with operational performance.…”

Tillage Interference in the Quality of Peanut Mechanized Harvest

“…The high values of the coefficients of variat ion found are in agreement with those found in the literature when evaluating losses, with CV values in the majority of the studies exceeding 30%. These high CV values found for harvest losses indicate that for the success of a production system it is essential to maintain and improve the quality of the processes during the harvesting operation, which has high variability rates due to factors inherent in the operation itself, and there may be interaction between the machine, condition of culture and climate, especially labor, as attested by several studies in the literature, regardless of the culture studied, such as peanuts (Zerbato et al, 2017), sugar cane (Toledo et al, 2008) and corn (Oliveira et al, 2014).…”

“…In the digging, the pods are removed fro m the ground by the tractor-diggerinverter that plunks and inverts the plants, forming lines, so that the pods are exposed to the sun for the healing phase and later recollection. Digging losses occur during peanut removal fro m soil and are influenced by factors such as harvesting time, climate, crop health, maturation, regulation of machinery and mainly soil conditions such as water content and texture (Zerbato et al, 2017).…”

“…In this context, the Statistical Process Control (SPC) is included as a useful and commonly used tool in the analysis of the agricultural processes quality. Several authors have used the SPC, considering the variables evaluated as quality indicators, to identify nonrandom causes or special causes arising fro m the instability or variability due to the process (Toledo et al, 2013, Paixão et al, 2017Santos et al, 2017;Zerbato et al, 2017), however, there are no studies evaluating the quality of the peanut harvesting operation in different types of soil preparation.…”