Abstract: Background and Objective: The data from the livestock sector is useful for science-based policymaking. Data presentation will contribute positively to the development of the livestock sector in Indonesia. Feed requirements data for ruminants is essential in the livestock business. However, data on feed requirements are often lacking in presentation quality and are mostly presented in tabular or numeric. This study aims to describe the utilization of geospatial software in making map-based ruminant feed requirements data in the Integrated Cropping Calendar Information System (ICCIS) which covers all subdistricts in Indonesia. Materials and Methods: The method used in this study was descriptive. The study meticulously outlined the stages involved in generating map-based feed requirements data using geospatial software. The feed requirements status was presented with a specific color on the map. The data on feed requirements is derived from livestock population data and nutrients required by animals. Results: This study highlights the crucial role of geospatial software in presenting map-based data for assessing the requirements of ruminant feed in a given region. Integrating geospatial data of feed requirements with other sources of information such as quantity of feed resources, enables a comprehensive and accurate analysis to facilitate the decision-making for livestock management and development. Conclusion: By utilizing geospatial software, it becomes possible to provide a comprehensive and concise overview of the requirements of ruminant feed in a region, which can assist in identifying areas with feed deficits and prioritizing interventions to improve feed security. Therefore, geospatial software is essential for effectively mapping and efficiently analyzing ruminants’ feed requirements. PubDate: 31 May, 2024
Abstract: Background and Objective: Determining the total economic value in terms of direct value and indirect use value of dairy farming can be used as a consideration for formulating policies and evaluations related to environmental economic assessment and developing business areas based on the potential of local livestock resources. This study aims to estimate the total economic value of dairy cattle in four provinces on Java Island that are centers of dairy cattle production in Indonesia, including West Java, Central Java, East Java and Yogyakarta. Materials and Methods: The study uses primary and secondary data. Primary data sourced from the respondents (439 farmers) and secondary data was sourced from the books Livestock and Animal Health Statistics, Livestock in Numbers and Structure of Ruminant Livestock Costs. The analysis was carried out descriptively and quantitatively and the results of the analysis were written in table form. The total economic value was determined using the direct and indirect use value approach. Results: The direct use value calculation of the value of live dairy is IDR 11.06100 trillion/year. The added value of dairy is IDR 4.26846 trillion/year; the value of milk production is IDR 3,554,793,911.00 year and the value of manure is IDR 18,097,025,760.00/year. The indirect use value of employment opportunities is IDR 3.06849 trillion/year and the multiplier effect in terms of population is IDR 19,318,876,544.00/year. The province with the highest total economic value is East Java. Conclusion: In summary, dairy cattle assets on smallholder farms must be increased, especially milk production and the use of livestock manure. PubDate: 24 March, 2024
Abstract: Background and Objective: An optimal ratio of rumen degradable protein (RDP) and rumen undegradable protein (RUP), synchronized with energy availability and sulfur supplementation in a dairy ration, has been shown to enhance cow productivity. The research studied the influence of formaldehyde-protected soybean, corn (CO) and cassava meal (CM) non-fibre carbohydrate (NFC) and Na2SO4 supplementation on the fermentability and digestibility of dairy cattle rations. Materials and Methods: The experimental rations consisted of two types of NFC sources (CO and CM), each combined with soybean (SS), formaldehyde-protected soybean (PS) and formaldehyde-protected soybean with sulfur (PSS). Ration without soybean (WS) was used as a control. All types of rations have been tested for their fermentability, including pH, ammonia, total Volatile Fatty Acids (VFA), protozoa and rumen microbe analysis. Additionally, dry matter and organic matter digestibility (DMD and OMD) were assessed. The treatments were replicated four times. Results: The inclusion of NFC, protected soybean and sulfur supplementation in the ration did not have a significant effect (p>0.05) on pH, ammonia concentration, rumen bacteria, protozoa population and digestibility. However, the total VFA increased significantly in the CM rations combined with soybean compared to WS and CO rations. Conclusion: Adding cassava NFC, formaldehyde-protected soybean and Na2SO4 supplementation improved total VFA production while maintaining other fermentability and digestibility. PubDate: 15 March, 2024
Abstract: Background and Objective: The World Health Organization listed Campylobacter spp. as one of the most common food-borne bacterial pathogens worldwide. In the Philippines, Campylobacter contamination in chicken are well established but there is a research gap on the presence and antimicrobial resistance of Campylobacter spp., in raw carabaos’ milk. This study aims to determine the prevalence of Campylobacter spp., in the raw milk and its resistance to common antimicrobial agents. Materials and Methods: This study utilized the combination of conventional culture method and a commercial milk bacterial DNA isolation kit to detect the presence of Campylobacter coli and Campylobacter jejuni in raw milk. In both methods, Campylobacters were genotyped with primers that encode for lipid A; while antibiotic resistance was determined using primers for tetracycline (tetO) and ampicillin (blaOXA-61) resistance genes. Results: Out of 107 raw milk samples, C. coli was detected in 0.94% of the samples using conventional culture method and on 6.54% (95% CI, 3.2-12.9%) using the commercial kit. No C. jejuni were detected using both methods. No genes that encode for tetracycline and ampicillin resistance were detected but phenotypic testing showed intermediate resistance to ampicillin. During the analysis, several Campylobacter-like colonies grew on the selective media but 16S gene sequencing revealed the colonies to be Acinetobacter baumannii (59%) and Pseudomonas aeruginosa (23%). Conclusion: Results confirmed the presence of C. coli in raw carabaos milk which possess resistance against ampicillin, suggesting that a review of the milk handling protocol in backyard farms is necessary. Further, the difficulty encountered in the isolation of Campylobacters can be a source of bias and must be considered in future surveillance programs for this food-borne pathogen. PubDate: 11 April, 2024
Abstract: Background and Objective: Daily fluctuation in the supply of nutrients from fresh forage offered by dairy farmers should be detected and adjusted to guarantee a consistent supply of nutrients for dairy cows. Currently, available dried forage detection using NIRS requires sample preparation. This study aimed to develop a wet forage NIRS database and compare its accuracy with a dry database. Materials and Methods: A total of 133 NIRS spectra were collected for fresh and dried forage, including napier grass, natural grass, rice straw, corn stover and corn husk. Chemical analysis was conducted using proximate and Van Soest methods to analyse dry matter (DM), ash, crude protein (CP), crude fiber (CF), neutral (NDF) and acid (ADF) detergent fibers. The chemical data were used to calibrate the spectrums to produce the NIRS prediction model. Results: The wet spectrums varied considerably compared to dry spectrums. Higher reflectance of the dry spectrum showed higher nutrient density in the dried forage. All nutrient contents can be detected accurately using dry or wet NIRS database (R2C>0.5 and RPD>1.5). However, a dried database is still more accurate (R2C>0.78) than a wet database (R2C>0.63). However, external validation of the dry database showed a significant difference in CP and ADF with the chemical analysis (t-test PubDate: 01 May, 2024
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