graduate student from 01.01.2023 to 01.01.2025
employee
VAK Russia 4.1.2
VAK Russia 4.1.3
VAK Russia 4.1.4
VAK Russia 4.1.5
VAK Russia 4.2.1
VAK Russia 4.2.2
VAK Russia 4.2.3
VAK Russia 4.2.4
VAK Russia 4.2.5
VAK Russia 4.3.3
VAK Russia 4.3.5
UDC 639.37
The objective of this study is to conduct a comparative analysis of the impact of feed distribution method on the linear-weight parameters of juvenile rainbow trout, taking into account their variability. The study subjects were rainbow trout fry reared in tanks at Fedorenko N.V., LLC. Before the study, fish from both tanks were sorted, their size and weight parameters were determined, and then re-mixed and placed in the same tanks. Feeding, both manually and automatically, was performed every hour around the clock for 33 days. Upon completion of the study, the fish were again sorted, their linear-weight parameters were measured, and their variability (Cv) was determined. The null hypothesis that the compared populations were identically distributed was tested using the nonparametric Mann-Whitney U-test. When comparing rainbow trout by weight and zoological length before the experiment, the samples (44 and 43 in size, respectively) had the same distribution with a reliability of 95 %. However, when comparing fish by the same parameters after the experiment (45 and 33 in size, respectively), the value of the T statistic (3.515 and 6.245, respectively) is greater than the tabulated value of the Student's t-test for the degree of freedom df = 76 and the significance level α = 0.05 (T(0.05,df) = 1.992). Therefore, the differences between the studied samples were significant; feeding method (manual vs. automatic feeder) significantly impacted fish body weight and length (with a 95 % confidence level). Automatic feeding had the greatest impact.
rainbow trout, trout feeding method, automatic trout feeding, trout live weight, trout body length
1. Milyanchuk N, Kuchko Ya, Ilmast N. The impact of fish farming on the Tarasmozero Lake ecosystem, Onega Lake basin. In: BIO Web of Conferences. Biologization, 2024. 2024;118:02002. DOI:https://doi.org/10.1051/bioconf/20241180200. EDN: https://elibrary.ru/UPSDTO.
2. Shmeleva LA. Automation of business processes of aquaculture production. Vestnik Altajskoj akademii economiki I prava. 2022;6(1):181-185. (In Russ.). DOI:https://doi.org/10.17513/vaael.2263.
3. Thornburg J. Feed the fish: A review of aquaculture feeders and their strategic implementation. Journal of the World Aquaculture Society. 2025; 56(2):e70016. DOI: 10.1111/ jwas.70016.
4. Jescovitch L, Ullman C, Rhodes M, et al. Effects of different feed management treatments on water quality for Pacific white shrimp Litopenaeus vannamei. Aquaculture Research. 2017;00:1-6. DOI:https://doi.org/10.1111/are.13483.
5. Ullman C, Rhodes M, Hanson T, et al. Effects of Four Different Feeding Techniques on the Pond Culture of Pacific White Shrimp, Litopenaeus vannamei. World Aquaculture Society. 2019;50(1):54-64. DOI:https://doi.org/10.1111/jwas. 12531.
6. Lu Zh, Li B, Xiaobing S, et al. Intelligent fish feeding based on machine vision: A review. Biosystems Engineering. 2023;231:133-164. DOI:https://doi.org/10.1016/j.biosystemseng.2023.05.010.
7. Thornburg J. Feed the fish: Are view of aquaculture feeders and their strategic implementation. World Aquaculture Society. 2025;56(2):e70016. DOI:https://doi.org/10.1111/jwas.70016THORNBURG.
8. Rahman M, Sumantri I. Evaluation of simple feeding technology on growth and feed efficiency of tilapia in cage aquaculture at South Kalimantan, Indonesia. Livestock Research for Rural Development. 2022;34(12):1-10.
9. Tihonov EA, Bazykin VI, Mukhanov NS. Improving the reliability and service life of the pneumatic distributor for distributing feed to cages. Resources and Technology. 2020;17(1):89-104. (In Russ.). DOI:https://doi.org/10.15393/j2.art.2020.5202. EDN: https://elibrary.ru/UXWXCE.
10. Sveshnikova EV, Romanova EM, Romanov VV, et al. Fish-breeding and biological characteristics of rainbow trout when using “Pravad” polyvalent functional feed additive. Vestnik of Ulyanovsk State Agricultural Academy. 2024;4(68):159-164. (In Russ.). DOI:https://doi.org/10.18286/1816-4501-2024-4-159-164.
11. Bavrina AP, Borisov IB. Modern rules of the application of correlation analysis. Medical Almanac. 2021;3(68):70-79. (In Russ.).
12. Karmanova EP, Makarova V.E., Murav'ja LN. Geneticheskie parametry priznakov otbora sel'skohozyaystvennyh zhivotnyh. Petrozavodsk: PetrGU; 2003. 51 p. (In Russ).
13. Lemeshko BYu. Kriterii proverki gipotez ob odnorodnosti. Rukovodstvo po primeneniju. Moscow: INFRA-M; 2021. 248 p. (In Russ.). DOI:https://doi.org/10.12737/986695.
14. Shcherbakov YuS, Tyshchenko VI. Main components analysis and comparative characteristics of female rainbow trout of three different breeds. Bulletin of KSAU. 2021;8:113-118. (In Russ). DOI:https://doi.org/10.36718/1819-4036-2021-8-113-118. EDN: https://elibrary.ru/IQCXYF.
15. Chekun EP, Tarazevich EV. Research of heterozis effect in seglets of reciprocal crosses of amber and rainbow trout. Uchjonye zapiski UO VGAVM. 2020;56(3):98-104. (In Russ.).
