How Can the Engineering Parameters of the NIR Grader Affect the Efficiency of Seed Grading?

Tatyana P. Novikova, Clíssia Barboza Mastrangelo, Paweł Tylek, Svetlana A. Evdokimova and Arthur I. Novikov ()
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Tatyana P. Novikova: Timber Industry Faculty (A.N.), Faculty of Computer Science and Technology (T.N., S.E.), Voronezh State University of Forestry and Technologies Named after G.F. Morozov, 8 Timiryazeva Street, 394087 Voronezh, Russia
Clíssia Barboza Mastrangelo: Center for Nuclear Energy in Agriculture (CENA/USP), Piracicaba 13416-000, Sao Paulo, Brazil
Paweł Tylek: Faculty of Forestry, University of Agriculture in Krakow, Al. 29 Listopada 46, 31-425 Krakow, Poland
Svetlana A. Evdokimova: Timber Industry Faculty (A.N.), Faculty of Computer Science and Technology (T.N., S.E.), Voronezh State University of Forestry and Technologies Named after G.F. Morozov, 8 Timiryazeva Street, 394087 Voronezh, Russia
Arthur I. Novikov: Timber Industry Faculty (A.N.), Faculty of Computer Science and Technology (T.N., S.E.), Voronezh State University of Forestry and Technologies Named after G.F. Morozov, 8 Timiryazeva Street, 394087 Voronezh, Russia

Agriculture, 2022, vol. 12, issue 12, 1-17

Abstract: The automated grading of Scots pine seeds in the near-infrared wavelength region (NIR grading) is a starting point for further actions, such as coating and priming. This reduces the time and financial costs and increases the accuracy of seed viability classification compared to invasive techniques. The NIR-based wave reflected from each pine seed must be detected and processed with sufficient accuracy. To focus the reflected beam, we used fiber-optic Bragg grating, a Bragg mirror, and diffraction grating. For each focusing option based on the DOE matrix, one experiment of 20 runs ( n = 20) and three replicas ( m = 3) in each run was conducted. In each replica, we used 100 conditioned and 100 non-conditioned seeds ( N C + N NC = 200) selected randomly from five samples weighing 50 g from a seedlot weighing 1 kg extracted from cones collected from a natural tree stand. Three experiments were conducted on the NIR grading of Scots pine seeds using an optoelectronic device. An adequate DOE regression model of the grading efficiency function was obtained. The functions included the following arguments: angle of incidence of the optical beam, NIR wavelength reflected from the seed, and height of the seed pipeline. The influence of the inclination angle of the light source relative to the plane of pine seed movement on the grading quality prevails over other factors. The NIR grading of Scots pine seeds allows the separation of seeds according to the viability index, which is important, since dead petrified seeds (possibly up to 25%) may occur in the seed batch, which cannot be eliminated by either seed size or mass. The peak of NIR grading is achieved by combining the average grader engineering parameters: 968–973 nm for the wavelength and 44–46 degrees for the inclination angle of the reflected beam at a seed pipe size of 0.18–0.23 m.

Keywords: reforestation; forest seeds; Scots pine; Pinus sylvestris L.; grading; NIR grading; seed spectrometric features; conditioned seeds; non-conditioned seeds (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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