Prediction of leaf number by linear regression models in cassava

Estimation of leaf number currently held on the plant and degree of leaf sheding occurred was carried out in two Cassava (Manihot esculenta) morphotypes (Philippine and Nagra) at Mymensingh (24°75´N 90°50´E). Four linear regression Models were developed for estimating leaf number (LN) from length (L) of mainstem (MS) and primary branch (PB) and they were LNMS = -6.89 + 1.05LMS (Model # 1) and LNPB = -5.116 + 1.033LPB (Model # 2) for Philippine; and LNMS = -4.041 + 0.73LMS (Model # 3) and LNPB = -1.597 + 0.707LPB (Model # 4) for Nagra morphotype. New leaf number produced in the mainstem (LNMS) and primary branch (LNPB), total leaf number in the mainstem (TLMS) and primary branch (TLPB) of each morphotype were also counted for leaf abscission (LAB) prediction model and the results showed that the regression models of leaf abscission in the primary branch (LABPB) from new leaf in the primary branch (LNPB) was effective (LABPB = - 0.521 + 0.525LNPB) (Model # 6). These regression Models showed linear relationships when actual leaf number was plotted against predicted leaf number and that this confirmed accuracy of the developed Models. Moreover, Models selection indices had high predictability (high R2) with minimum error (low error mean square error and percentage deviation). The selected Models appeared accurate and rapid, but can be used for estimation of leaf production in Philippine and Nagra morphotypes of Cassava.

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Journal of the Bangladesh Agricultural University, 09, 1
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 Record created 2017-04-01, last modified 2020-10-28

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