Multivariate Statistical Analysis Applied to Physical Properties of Soybean Cultivars in The Design and Regulation of Post-Harvest Equipment
The present work had as aim to evaluate the similar of soybean cultivars according to physical properties as a guiding parameter for decision making in the design and regulation of post-harvest equipment using multivariate analysis. First, Pearson's correlation coefficients were estimated. Posteriorly, principal component analysis was performed to verify the interrelationship between variables and soybean cultivars. A biplot was built with the first two principal components. Finally, a boxplot was built for each variable considering the grouping presented by the analysis of main components. By principal component analysis, we identified the formation of two clusters (G1 and G2) of cultivars. Unit specific mass was the physical property that most contributed to the formation of G1, while the other physical properties contributed to the formation of G2. Soybean cultivars comprising the G1 are more similar to each other only for unit specific mass, and the cultivars allocated in group G2 are more similar for all the other properties evaluated. These results are recommended by the equipment manufacturing industry and the seed processing units to carry out projects and equipment adjustments to efficiently manage the post-harvest of soybean seeds.
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Posted 05 Jan, 2021
Received 14 Jan, 2021
Received 14 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
Invitations sent on 07 Jan, 2021
On 07 Jan, 2021
On 01 Jan, 2021
On 01 Jan, 2021
On 31 Dec, 2020
Multivariate Statistical Analysis Applied to Physical Properties of Soybean Cultivars in The Design and Regulation of Post-Harvest Equipment
Posted 05 Jan, 2021
Received 14 Jan, 2021
Received 14 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
On 07 Jan, 2021
Invitations sent on 07 Jan, 2021
On 07 Jan, 2021
On 01 Jan, 2021
On 01 Jan, 2021
On 31 Dec, 2020
The present work had as aim to evaluate the similar of soybean cultivars according to physical properties as a guiding parameter for decision making in the design and regulation of post-harvest equipment using multivariate analysis. First, Pearson's correlation coefficients were estimated. Posteriorly, principal component analysis was performed to verify the interrelationship between variables and soybean cultivars. A biplot was built with the first two principal components. Finally, a boxplot was built for each variable considering the grouping presented by the analysis of main components. By principal component analysis, we identified the formation of two clusters (G1 and G2) of cultivars. Unit specific mass was the physical property that most contributed to the formation of G1, while the other physical properties contributed to the formation of G2. Soybean cultivars comprising the G1 are more similar to each other only for unit specific mass, and the cultivars allocated in group G2 are more similar for all the other properties evaluated. These results are recommended by the equipment manufacturing industry and the seed processing units to carry out projects and equipment adjustments to efficiently manage the post-harvest of soybean seeds.
Figure 1
Figure 2
Figure 3
Figure 4