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Sabampillai Mahendraraj Marisa Collins Yash Chauhan Vincent Mellor Rao C.N Rachaputi

Abstract

Temperature and photoperiod are two major environmental determinants that affect the flowering time. The information on the effect of temperature and photoperiod on flowering response in pigeonpea is limited and needs updating for new genotypes. The present study aimed to assess the reliability of the Nonlinear least square broken stick model to quantify photothermal effects in pigeonpea (Cajanus cajan (L.) Millsp.) genotypes. Data at 50 % flowering (FL) from pot, field, and temperature-controlled glasshouse experiments under eight sowing dates were analysed using regression models to describe the individual effect of temperature and photoperiod and photothermal models to quantify the combined effect. The critical photoperiod (Pce)and optimum temperature (To)predicted by the Nonlinear broken stick model for 50 % FL ranged from 12.4 - 13.4 h and 21.0 - 23.5 °C, respectively. The higher Pce reported for extra-early flowering genotype (QPL 1001) indicates that their insensitiveness to a range of photoperiod regimes compared to QPL 941 and ICP 14425 (medium duration). Further, the results also revealed that the time to 50 % FL of genotype QPL 1001 was strongly sensitive to the temperature at sub-optimal range (T < To), with warmer temperatures accelerating reproductive development. In contrast, QPL941 and ICP 14425 were sensitive to supra-optimal temperature (T > To), with flowering being delayed in warmer temperatures. The parameters (To and Pce) derived from Nonlinear least square broken stick model can be used as a proxy to identify photoperiod insensitivity in pigeopea genotypes.


 

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Keywords

Critical photoperiod, Nonlinear least square broken stick model, Optimum temperature, Photothermal model

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Section
Research Articles

How to Cite

Reliability of Nonlinear least square broken stick model in quantifying the effects of temperature and photoperiod on flowering of pigeonpea genotypes (Cajanus cajan (L.) Millsp.). (2024). Journal of Applied and Natural Science, 16(2), 508-518. https://doi.org/10.31018/jans.v16i2.4840