Peanut yield and maturation of pods in single and double row systems under different plant densities.

Abstract

The adjustment of density and arrangement of peanut plants is essential to improve radiation interception, photosynthetic rate, uniformity of pod maturation and peanut yield. In Brazil, although both the single-row and double-row systems are used for peanut cultivation, it is still not known which system is the best and whether this depends on the density of plants used and the level of soil fertility. The objective of the study will be to evaluate the effect of plant density and arrangement on the yield components, yield and maturity of peanut pods. The experiments will be carried out in a commercial peanut crop, in Regente Feijó-SP, in an area of the first year of peanut cultivation after degraded pasture (low fertility) and in an area of rotation between peanut and pasture - three years (medium fertility). The soils in the areas are classified as Red-Yellow Latosol, with a sandy texture. The experimental design will be in case blocks, in a split-plot scheme, with four replications. The treatments will be plant arrangements: single-row (0.90 cm between rows) and double-row (0.73 x 0.17 cm between rows) and plant density: 8, 10, 12 and 14 plants per meter. Peanuts will be sown in January 2023. At 15 DAE (V3) the plants will be thinned to establish plant densities. At 30 (R1), 50 (R3), 70 (R6), 90 (R7), 120 days (R8-R9) the index and leaf area (LAI) will be evaluated and three plants per plot will be collected to determine the accumulation of peanut dry matter (shoot and pods). To evaluate the yield components (number of plants per meter, number of pods per plant, number of grains per pod and weight of 1000 grains) and yield, two-meter plants from two rows of each experimental unit will be collected. On the day of harvest, a sub-sample of 200 pods will be separated to evaluate pod maturation. The statistical study will consist of variance and regression analyses, and the means of the experimental treatments will be compared by the t test (LSD) at a minimum level of 5% probability, using Sisvar statistical software.