Mechanization in agriculture & Conserving of the resources
Vol. 69 (2025), Issue 2, pg(s) 41-45

MECHANIZATION IN AGRICULTURE

Automated installation and algorithmic platform for determining the quality indicators of seed potato tubers

  • 1 Almaty University of Power Engineering and Telecommunication named Gumarbek Daukeev, Almaty, Kazakhstan
  • 2 Kazakh National Agrarian Research University, Almaty, Kazakhstan
  • 3 Almaty Technological University, Almaty, Kazakhstan

Abstract

The article presents a comprehensive scientific and engineering development — an automated installation and an algorithmic platform for assessing the quality characteristics of varietal seed potato tubers. The development is aimed at solving key agroengineering problems related to increasing the accuracy, standardization and productivity of tuber analysis processes in seed production.
The methodological basis of the study is a combination of tensometric measurement of tuber mass with computer vision algorithms based on the OpenCV library in the Python programming environment. The algorithm allows for automatic and highly accurate determination of mass, linear dimensions (length, width, height), area and perimeter of the tuber, as well as calculation of derived indicators such as shape index and shape coefficient, which are important for sorting and determining varietal affiliation.
To verify the developed system, experimental studies were conducted on an automated setup using control measurements performed by traditional methods (calipers, electronic scales). The study included both mini-tubers and standard seed tubers of the Alliance potato variety. Statistical analysis of the data showed a high degree of consistency between digital and manual measurements, and also revealed a significant advantage of the automated method in terms of productivity: the analysis time for one tuber was reduced by an average of seven times.
Particular attention is paid to the compliance of the proposed method with national and international standards, in particular, the requirements of GOST 33996–2016, which guarantees the possibility of its practical application in real production conditions. The authors substantiate that the introduction of digital technologies in the process of sorting seed potatoes allows minimizing subjective errors, reducing labor costs, increasing the speed of data processing and standardizing the quality assessment process.
The scientific novelty of the work lies in the integration of algorithmic data processing with physical measurements on one platform, which allows for the implementation of a comprehensive agro-engineering system for solving problems of selection, seed production and automated sorting. The developed installation can be adapted and scaled for use with other fruit and vegetable crops, which opens up opportunities for further research and expansion of the range of applications.
The results of the study are relevant for agro-industrial enterprises, research institutes, seed farms and agricultural machinery manufacturers. The proposed system can be integrated into existing sorting and processing lines, ensuring the transition to precision agriculture and industry 4.0 technologies in the agricultural sector..

Keywords

References

  1. "GOST 33996-2016 Seed Potatoes. Technical conditions and methods for determining quality" Interstate Council for Standardization, Metrology and Certification. (minutes of October 25, 2016 No. 92-P)
  2. Goryachkin V.P. On potato sorting. Collected Works. - M.: Kolos, v. 3, 1965, pp. 190-202.
  3. Efremov S.I. Tuber shape and its importance in determining potato varieties and seed production . - Scientific notes (Oryol Pedagogical Institute), v.31, issue 11, 1965. pp.5-136.
  4. Alikhanov D.M., Shynybay Zh.S. Automation of processes for determining quality indicators and sorting potato tubers based on digital technologies. Monograph: Almaty: AUPET, 2022. – 246 p.
  5. A.E. Mukhametov , D.R. Dautkanova , N.B. Dautkanov , A.Sh. Seed potato production in Kazakhstan. Research and results. No. 2, 2023 p .
  6. Hall B.H., Lotti F. & Mairesse J. Innovation and Productivity in SMEs: Empirical Evidence for Italy // Small Business Economics. 2009. Vol. 33. P. 13-33.
  7. D. Volkov,A . Argynbayeva , D. Daurov , K. Zhapar , Zh . Abai , K. Zhambakin , M. Shamekova (2020) Accelerated production of virus-free Potato planting material using a bioreactor. Reports of the national academy of sciences of the republic of Kazakhstan. 5(333): 56-62. DOI:10.32014/2020.2518-1483.119
  8. Shamekova , M., Mendoza, M.R., Hsieh, J., Lindbo , Y.-C., RT, Omarov , RT, Scholthof , HB Tombusvirus -based vector systems to permit over-expression of genes or that serve as sensors of antiviral RNA silencing in plants. Virology, 2014, 452-453, pp . 159–165 percentile - 68, quartile ( WoS ) - Q3, index citations – 9; DOI: 10.1016/j.virol.2013.12.031
  9. Tao Y., Morrow CT, Heinemann PH, Sommer HI Fourier - based Sepa -ration Technique for Shape Grading of Potatoes Using Machine Vision // Transactions of the ASAE. – 1995. – vol. 38, No. 3. – P. 949 - 957.
  10. Pearson TC, Doster MA, Michailides TJ Automated Detection of Pistachio Defects by Machine Vision // Applied Engineering in Agriculture. – 2002. – vol.17, No. 5. – R. 729-732.
  11. Anand Kumar Pothula a, Zhao Zhang b, Renfu Lu c, Evaluation of a new apple in-field sorting system for fruit singulation, rotation and imaging Computers and Electronics in Agriculture 208 (2023) 107789 https://doi.org/10.1016/j.compag.2023.107789.
  12. Payman Moallem a,b ,*, Alireza Serajoddin c, Hossein Pourghassem d,c Computer vision-based apple grading for golden delicious apples based on surface features Information processing in agriculture 4 (2017) 33–40 https://doi.org/10.1016/j.inpa.2016.10.003 .
  13. Bashilov A.M. Electron-optical vision in agricultural production. – Moscow: Publishing house of the State Scientific Institution VIESH, 2005. – 312 p.; – Bibliography : pp. 283-295. – Index items: pp. 3-4. – 500 copies. – ISBN 5-85941-208-8.
  14. Pokidov O.V. Electron-optical device for assessing morphological parameters of potato tubers during variety support: Abstract of dissertation for the degree of Cand. Sci. (Eng.). – Moscow, 2005. – 16 p.
  15. Alikhanov Dz., Shynybay Zh ., Daskalov P., Tsonev R. Express method and divice for definition of potato tubers parameters // Bulgarian journal of agricultural science. – 2013. – vol. 19, no. 4. – P. 866-874.
  16. Automation of sorting and rejection [Electronic resource]. - Access mode: http : // www . mkoi . org /366/367/373/
  17. OpenCV step by step. Search for an object by color – RGB [Electronic resource ]. - Access mode: http://robocraft.ru/blog/computervision/365.html

Article full text

Download PDF