ASSESSMENT OF THE INFLUENCE OF BIOMETRIC INDICATORS AND ABIOTIC FACTORS ON THE LABOR INTENSITY OF PRUNING IN AN INTENSIVE APPLE ORCHARD IN THE CONDITIONS OF СRIMEA
- Year:
- 2025
- The authors:
- Бабинцева Н. А., Кириченко В. С.
- DOI:
- 10.31360/2225-3068-2025-94-46-57
- Page numbers:
- 46 - 57
- Keywords:
- apple tree, labor costs, biometric indicators, weather conditions, correlation coefficients, variation dependence, regression
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The paper presents the results of studies on the labor intensity of pruning in apple tree plantations with the cultivars – ‘Brebern’, ‘Dzhalita’ and ‘Renet Simirenko’ on the M9 rootstock at a planting density of 2 500–5 000 trees/ha in the conditions of the foothill zone of Crimea. It was found that the labor intensity of pruning depends on the biological characteristics of the cultivar, the number of trees planted per 1 ha, the size of the crown and development of shoot-forming wood. Pruning of 11-year-old trees in the shape of a slender spindle at a planting density of 2 500 trees/ ha requires from 101.3–109.7 (‘Breburn’, ‘Dzhalita’) to 148.8 man-hours (‘Renet Simirenko’); at a density of 5 000 trees/ha, the costs increase by 2.4–2.9 times and amount to from 294.6 (‘Breburn’) to 351.6 man-hours (‘Renet Simirenko’) per 1 ha. The experimental data were processed using variation statistics methods. Based on the correlation coefficients, the dependence factors in all three cultivars that affect the labor intensity of pruning were identified: with the total increase in shoots in the crown (r = 0.54–0.87), the length of growth shoots (r = 0.46–0.80), the size of the projection and volume of the crown (r = 0.50–0.72) and with the amount of precipitation in July (r = 0.65–0.76). The significant significance of the above indicators with the density of tree planting per 1 ha was statistically confirmed: for ‘Brebern’ (r = 0.64–0.89), ‘Dzhalita’ (r = 0.67–0.91), ‘Renet Simirenko’ (r = 0.55 and r = 0.95). When forming a multifactorial model, the linear dependence function was used: У = a0 + a1X1 + a2X2 + ... + anXn. High regression coefficients allow using data to predict the labor intensity of pruning, taking into account the activity of growth processes, crown size, weather factors, and to determine the total number of hired workers for pruning, which is important to consider in technological processes growing during the period of exploitation of plantations.