Plant-architectural and environmental predictors of seed mass of winter oilseed rape in southern Poland based on the CART trees regression model

Dacko, Mariusz; Oleksy, A.; Synowiec, Agnieszka; Klimek-Kopyra, Agnieszka; Kulig, B.; Zając, T.

doi:10.1016/j.indcrop.2022.116109

Cited by 5 publications

(1 citation statement)

References 30 publications

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“…The commonly used algorithms for decision trees are ID3, C4.5, and CART. The decision tree algorithm used in this paper is CART [19], as shown in Figure 1, with the following steps:…”

Section: Decision Treementioning

confidence: 99%

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

Nan,

Li,

Zhang

et al. 2023

ICST Transactions on Scalable Information Systems

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INTRODUCTION: The quality assessment technology of distance education in colleges and universities, as the critical technology for identifying the quality of distance education in colleges and universities, is conducive to the improvement of the quality of distance teaching and the progress of the existing means and methods of distance education, which makes the means of distance teaching in colleges and universities rich in science. OBJECTIVES: Aiming at the evaluation methods of higher education institutions, there are problems such as insufficient objectivity and comprehensiveness of the evaluation system, single process, and inadequate quantitative analysis. METHODS:Proposes a decision tree and intelligent optimization algorithm for the college distance teaching quality assessment method. Firstly, the kernel principal component analysis method is used to carry out dimensionality reduction analysis on the index system of college distance teaching quality assessment; then, the decision tree parameters are optimized through the marine predator algorithm to construct a college distance teaching quality assessment model; finally, the robustness and efficiency of the proposed method are verified through simulation experimental analysis. RESULTS: The results show that the proposed method improves the accuracy of the assessment model. CONCLUSION: The problem of insufficient objective and scientific evaluation and low precision of distance teaching quality assessment methods in colleges and universities is solved.

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“…The commonly used algorithms for decision trees are ID3, C4.5, and CART. The decision tree algorithm used in this paper is CART [19], as shown in Figure 1, with the following steps:…”

Section: Decision Treementioning

confidence: 99%

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

Nan,

Li,

Zhang

et al. 2023

ICST Transactions on Scalable Information Systems

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Thermomechanical performance of energy retaining pile influenced by surrounding utility tunnel via the regression tree model

Kong

et al. 2023

Computers and Geotechnics

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The effect of nitrogen management on seed yield and quality in traditional and canola-quality white mustard

Jankowski,

Szatkowski,

Załuski

2024

Sci Rep

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The article presents the results of a three-year field study that was conducted in Poland to evaluate the yield and quality of seeds and oil from traditional (SAM) and canola-quality white mustard (SAC) in response to different N fertilizer rates (0, 40, 80, 120, and 160 kg ha–1). Seed yields were 25% higher in SAM than SAC. The seeds of SAC contained more crude fat (by 3%) and crude fiber (by 6%) than the seeds of SAM. In turn, the seeds of SAM were a richer source of total protein (by 7%). The content of glucosinolates (GSLs) was 8–10 times lower in the seeds of SAC than SAM. The seeds of both mustard cultivars were most abundant in γ-tocopherol (γ-T) (90–94%). The seeds of SAC were characterized by a higher content of γ-T and a lower α-T/γ-T ratio than SAM seeds. White mustard oil contained mostly MUFAs (69–75%). However, C22:1 accounted for more than 50% of MUFAs in the oil SAM. In the oil SAC, the proportion of C22:1 did not exceed 6%, whereas C18:1 accounted for nearly 85% of total MUFAs. Nitrogen fertilization induced a significant increase in seed yields (by 33%), a decrease in crude fat content (by 3–4%), and an increase in total protein content (by 4%), and crude fiber content (by 7%). Nitrogen decreased GSL levels by 31% in SAM seeds. In SAC, N fertilization induced differences in the qualitative composition of GSLs, but did not affect the total GSL content of seeds. Higher N rates increased the content of α-T and γ-T, the α-T/γ-T ratio, and total T content. Nitrogen fertilization decreased the content of C18:3 in the seeds of the SAM. In SAC, the application of N decreased the content of C18, C18:1, and C18:3, and increased the biosynthesis of C18:2, C20:1, and C22:1.

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Plant-architectural and environmental predictors of seed mass of winter oilseed rape in southern Poland based on the CART trees regression model

Cited by 5 publications

References 30 publications

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

Thermomechanical performance of energy retaining pile influenced by surrounding utility tunnel via the regression tree model

The effect of nitrogen management on seed yield and quality in traditional and canola-quality white mustard

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