Influence of seeding rates on the quantum yield of photosynthesis for some field crops - K. S. Panchenko; N. V. Ovcharova; L. V. Sokolova; M. M. Silantyeva (Труды по прикладной ботанике, генетике и селекции)
Background. Photosynthesis is one of the most important physiological processes in plants, affecting the productivity of agrocenoses. Creating conditions for crops to absorb and convert solar energy as effectively as possible can be a means of increasing their yields. The objective was to study the production processes and stress resistance of some crop species in order to optimize their cultivation technology.Materials and methods. The work was carried out in the steppe and forest-steppe zone of Altai Territory. The scheme of the experiment was conducive to studying the quantum yield of photosynthesis as a method for assessing various seeding rates in the fields of sunflower grown for seeds (‘Pioneer LE 10’) and maize grown for silage (‘Clifton’). For sunflower, the rates were 35,000, 45,000, and 55,000 seeds/ha; for maize, 40,000, 50,000, and 60,000 seeds/ha. The state of the photosynthetic apparatus in plants was analyzed using the JUNIOR-PAM fluorometer (Walz, Germany) in the main phases of plant development. results. The quantum yield of photosynthesis over the growing season of sunflower, depending on the seeding rate, was the highest during flowering and ripening (up to 0.81 relative units). The highest values of the quantum yield of photosynthesis for maize were recorded in the phases of the 2nd leaf and 6–8 leaves (0.63 and 0.64 relative units, respectively).Conclusion. The most effective development of sunflower plants, characterized by a high quantum yield of photosynthesis and high productivity, was observed at the seeding rate of 45,000 seeds/ha. The highest maize harvest for silage (1.56 t/ha) was registered under conditions favorable for this indicator at the rate of 50,000 seeds/ha. The correlation coefficient between the quantum yield of photosynthesis and crop yield was 0.7–0.8, which confirmed the dependence between those indicators and made it possible to determine the optimal sowing structure.