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  1. Zailani NIM, Hanis F, Anuar MAM
    J Equine Vet Sci, 2024 Mar;134:105018.
    PMID: 38316315 DOI: 10.1016/j.jevs.2024.105018
    This study aimed to evaluate the benefits of using sawdust, pinewood shavings, and rubber wood shavings as horse bedding materials. Nine horses were used in a repeated measure design, where each horse was provided with each of the bedding materials for two consecutive weeks. The weight, cost, mucking out time, ammonia emissions, and urine holding capacity were measured and calculated for each bedding material. Results showed that pinewood shavings had the highest urine-holding capacity, while rubber wood shavings had the lowest absorbency for urine. Pinewood shavings also had lower ammonia emissions compared to sawdust and rubber wood shavings but were significantly more expensive. Sawdust was the cheapest of the three bedding materials, but it was used in greater quantities, which required more time for mucking out. The findings from this study could be used to make informed decisions on bedding materials for stables, taking into consideration the trade-off between cost, maintenance requirements, and labor hours.
  2. Anuar MAM, Amran NA, Ruslan MSH
    ACS Omega, 2021 Feb 02;6(4):2707-2716.
    PMID: 33553888 DOI: 10.1021/acsomega.0c04897
    Oil and grease remain the dominant contaminants in the palm oil mill effluent (POME) despite the conventional treatment of POME. The removal of residual oil from palm oil-water mixture (POME model) using the progressive freezing process was investigated. An optimization technique called response surface methodology (RSM) with the design of rotatable central composite design was applied to figure out the optimum experimental variables generated by Design-Expert software (version 6.0.4. Stat-Ease, trial version). Besides, RSM also helps to investigate the interactive effects among the independent variables compared to one factor at a time. The variables involved are coolant temperature, XA (4-12 °C), freezing time, XB (20-60 min), and circulation flow, XC (200-600 rpm). The statistical analysis showed that a two-factor interaction model was developed using the obtained experimental data with a coefficient of determination (R2) value of 0.9582. From the RSM-generated model, the optimum conditions for extraction of oil from the POME model were a coolant temperature of 6 °C in 50 min freezing time with a circulation flowrate of 500 rpm. The validation of the model showed that the predicted oil yield and experimental oil yield were 92.56 and 93.20%, respectively.
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