Phakamas, Nittaya

Loading...
Thumbnail Image
Preferred name
Phakamas, Nittaya
Alternative Name
Phakamas, N.
Main Affiliation
Email
nittaya.ph@kmitl.ac.th

Settings

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Effects of chicken manure and chemical fertilizer on Growth and Yield of Japonica Rice
    (2022-01-01)
    Phopaijit, S.
    ;
    Suraphonphinit, A.
    ;
    Phakamas, N.
    Organic and inorganic nitrogen fertilizers are normally used in Indica rice (Oryza sativa L.) production system, but information on the effects of chicken manure on Japonica rice is limited. The effects of chicken manure and chemical fertilizers on growth and yield of Japonica rice were determined. Rice varieties were significantly different for most traits including plant height, crop growth rate (CGR), biomass, percentage of filled and unfilled grain, number of grains per spikelet and harvest index (HI), except for grain yield. Chemical fertilizer had the highest grain yield followed by chicken manure, non-treated control and chemical fertilizer together with chicken manure, respectively. The interaction effects between fertilizer treatment and rice variety were not significant for all characters. These rice varieties seemed to better respond to chemical fertilizer than chicken manure treatments.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Possibility to use crop models for indirect prediction of glycemic index in rice
    (2024-01-01)
    Phopaijit, S.
    ;
    Somchit, P.
    ;
    Phakamas, N.
    A process for constructing the prediction equations was developed by using simulated biomass and simulated grain yield to be estimating the glycemic index (GI) of two rice varieties, and reference GI was used as a basis for calculation of predicted GI. The CSM-CERES-Rice model was able to construct the best prediction equations, and the equation developed by using simulated biomass and simulated yield were y = 0.0003x + 59.099 and y = 0.0008x + 59.213, respectively. The equations were also used for prediction of GI values of two rice varieties applied with different methods of nitrogen application. The difference of the equations was 0.0% for both simulated biomass and simulated grain yield. The process for indirect prediction of GI is used available simulated data of biomass and grain yield to improve prediction accuracy.