Akademik Veri Yönetim Sistemi
New Zealand Journal of Crop and Horticultural Science, cilt.54, sa.1, 2026 (SCI-Expanded, Scopus)
Water and energy crises, increased greenhouse gas emissions, high labor costs, and labor shortages demand the shift from puddled transplanting to dry direct seeding. Inbred rice varieties can perform well under the dry direct-seeded rice (DDSR) system. This study aims to optimize the seed rate (SR) for rice cultivars in the DDSR system. Five SRs (S1 = 15, S2 = 20, S3 = 25, S4 = 30, and S5 = 35 kg/ha) and four inbred rice varieties include Basmati 515 (V1), PK 1121 Aromatic (V2), Super Basmati (V3), and Kisan Basmati (V4) were used as experimental treatments. The study was conducted over 2 years (2019–2020). The plant height (PH), panicle length (PL), filled-grain per panicle (FGPP), unfilled-grain per panicle (UFGPP), productive tiller per m2 (PT), unpro-ductive tiller per m2 (UPT), 1000-grain weight (TGW), grain yield (GY), biomass yield (BY), harvest index (HI), average grain length (AGL), average grain width (AGW), average grain thickness (AGT), broken rice (B), brown rice (BR), head rice (HR), elongation ratio (ER), and bursting (BRUS) were the response variables. The Response Surface Methodology (RSM) was used to optimize the SRs based on the GY, BY, HI, HR, and ER. The results show that the PT, UPT, TGW, and GY were highly significant (p < 0.01) in the interaction effects of year, variety, and SR. The BY, HI, AGL, AGW, AGT, B, BR, HR, ER, and BRUS were highly significant (p < 0.01) in the interaction effect of variety and SR. In the RSM model, the optimal SRs were 27, 31, 25, and 24 kg/ha for the rice varieties V1, V2, V3, and V4, respectively. The RSM model showed higher R2 (0.81–0.99) with lower RMSE, mean absolute error (MAE), and mean absolute percentage error (MAPE) values. The predicted and actual values of GY, BY, HI, HR, and ER at optimum SR of 25 kg/ha for V3 were 3.65 t/ha, 9.88 t/ha, 33.47%, 40.48%, 2.07 and 3.32 t/ha, 11.0 t/ha, 32%, 38.66% 1.94, respectively. The RSM model predicted results agreed with the actual results, as prediction errors were less than or equal to ±10%, which confirmed the model’s reliability. Moreover, the GY has a positive correlation with BY (R = 0.5370). The HR showed a negative correlation with B (R = −0.8681) and AGL (R = −0.5015). Our findings imply that managing stand growth and weeds is critical in obtaining the required yield and quality in the DDSR system with lower SRs.