Prediction Model for Organic Matter Content in Chicken Manure  during Plantfield Composting
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    Abstract:

    The objective of this study was to explore the feasibility to estimate organic m atter (OM) content in chicken manure during aerobic composting. Two types of reg ression methods were used with physicochemical properties and nearinfrared spe ctroscopy (NIRS). Single and two variable linear regressions between the values of dry matter (DM), pH value, electrical conductivity (EC) and OM content were develop ed. Results showed that it was significant in practice to estimate the OM conten t using DM value with a higher coefficient of determination (R2=081, P <0001). In addition, multiple linear regression (MLR), principle component r egression (PCR) and partial least square regression (PLS) were used to develop NIRS models for OM. It was observed that the both models of PCR and PLS were rob u st with the coefficient of determination in validation set r2=095, respe ctively. And both the ratios of standard deviation of validation set to root mea n square error of prediction (RPD) are greater than 40.

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