Variation in photosynthetic induction between super hybrid rice and inbred super rice

Pan, Yong‐Bao; Du, Haisu; Meng, Xusheng; Guo, Shiwei

doi:10.1016/j.plaphy.2022.03.005

Cited by 5 publications

(1 citation statement)

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“…Yield components of hybrid rice were found to increase with increasing rates of N which might be due to the fact that application of N maintained the greenness of leaves in rice plants for a longer period resulting in greater photosynthetic assimilation. It was also assumed that hybrid rice cultivars have higher photosynthesis efficiency than conventional rice cultivars ( Pan et al, 2022 ). In addition to that, greater dry matter accumulation resulted from the higher tillering ability of tested hybrid rice might have caused larger sink development, and thereby improved all yield components ( Asaduzzaman et al, 2014 ).…”

Section: Discussionmentioning

confidence: 99%

Modelling nitrogen management in hybrid rice for coastal ecosystem of West Bengal, India

Sarkar

Ray

Garai

et al. 2023

PeerJ

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Hybrid rice requires adequate nitrogen (N) management in order to achieve good yields from its vegetative and reproductive development. With this backdrop, a field experiment was conducted at Regional Research Station (Coastal Saline Zone), Bidhan Chandra Krishi Viswavidyalaya, Kakdwip, West Bengal (India) to record growth and yield performance of hybrid rice (cv. PAN 2423) under varied N-fertilizer doses. A modelling approach was adopted for the first time in hybrid rice production system under coastal ecosystem of West Bengal (India). In the present study, the Agricultural Production Systems Simulator (APSIM) model was calibrated and validated for simulating a hybrid rice production system with different N rates. The APSIM based crop simulation model was found to capture the physiological changes of hybrid rice under varied N rates effectively. While studying the relationship between simulated and observed yield data, we observed that the equations developed by APSIM were significant with higher R2 values (≥0.812). However, APSIM caused an over-estimation for calibrate data but it was rectified for validated data. The RMSE of models for all the cases was less than respective SD values and the normalized RMSE values were ≤20%. Hence, it was proved to be a good rationalized modelling and the performance of APSIM was robust. On the contrary, APSIM underestimated the calibrated amount of N (kg ha−1) in storage organ of hybrid rice, which was later rectified in case of validated data. A strong correlation existed between the observed and APSIM-simulated amounts of N in storage organ of hybrid rice (R2 = 0.94** and 0.96** for the calibration and validation data sets, respectively), which indicates the robustness of the APSIM simulation study. Scenario analysis also suggests that the optimal N rate will increase from 160 to 200 kg N ha−1 for the greatest hybrid rice production in coming years under elevated CO2 levels in the atmosphere. The APSIM-Oryza crop model had successfully predicted the variation in aboveground biomass and grain yield of hybrid rice under different climatic conditions.

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Section: Discussionmentioning

confidence: 99%