Influence of physical properties of sugar beet seeds on the work quality of the seeding mechanism

Findura, Pavol; Malaga-Toboła, U.; Kwaśniewski, D.; Stasiak, Mateusz; Gugała, Marek; Sikorska, Anna; Gancarz, Marek

doi:10.31545/intagr/162403

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…In addition, the sowing quality is affected not only by the speed of the seeder, but also by the relevant soil parameters and its structure, which may be changed by applying the appropriate biostimulators (Findura et al, 2022;Bredykhin et al, 2023;Krawczuk et al, 2023;Szparaga, 2023a,b). The physical properties of the seeds used during sowing are also of great importance in forecasting the quality of the crop, and they significantly affect the quality of the work of the sowing mechanism of the precision seeder (Findura et al, 2023;Krzaczek et al, 2006). The seeds should be cleaned and selected before sowing (Krzysiak et al, 2017;Marczuk et al, 2019;Krzysiak et al, 2020a,b).…”

Section: Discussionmentioning

confidence: 99%

Predicting the seeding quality of radish seeds with the use of a family of Nakagami distribution functions

Ignaciuk,

Zarajczyk,

Różańska-Boczula

et al. 2023

Int. Agrophys.

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The study evaluated the seeding quality of radish seeds cv. Saxa Polana (percentage of single seeds, double seeds and missed seeds (skips) sown with a Max Pneumatic S 156 seed drill fitted with a pneumatic seed dosing unit set at different forward speeds of a metering unit and different sowing disc speeds. The seeding quality was analysed using Nakagami distribution functions, a chi-squared goodness of fit test, linear regression functions, and the ISO 7256/1, 1984 (E) Standard. The diagrams predicting the effect of the different speeds on the percentage of singles, doubles and skips were highly consistent with the results of the seeding quality analysis based on the ISO 7256/1, 1984 (E) Standard. The authors relied on Nakagami distribution functions to develop a new method for predicting the in-row distance between seeds within the analysed range of speeds, including those which were not empirically tested speeds. The proposed method can be used to predict seeding quality at different speeds when only the selected settings of the dosing unit are taken into account in the analysis. This approach significantly shortens the research time and also decreases the relevant costs.

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