scholarly journals Evaluation of Implementation Good Dairy Farming Practices (GDFP) at Ambopi Smallholder Dairy Farm, Southeast Sulawesi

2020 ◽  
Vol 465 ◽  
pp. 012055
Author(s):  
Nur Santy Asminaya ◽  
Ali Bain ◽  
Natsir Sandiah ◽  
Laode Muhsafaat ◽  
Fanny Yulia Irawan ◽  
...  
Keyword(s):  
Dairy Farm ◽  
Dairy Farming ◽  
Farming Practices ◽  
Smallholder Dairy

scholarly journals Evaluasi Aspek Teknis Pemeliharaan Sapi Perah Berdasarkan Good Dairy Farming Practices (GDFP) di Peternakan Rakyat Cibungbulang

2018 ◽  
Vol 5 (2) ◽  
pp. 79
Author(s):  
Asminaya Santy Nur ◽  
B. P. Purwanto ◽  
A. Atabany ◽  
Nurlaha Nurlaha
Keyword(s):  
Dairy Cow ◽  
Trichoderma Viride ◽  
Dairy Farm ◽  
Dairy Farming ◽  
Dry Season ◽  
Farming Practices ◽  
Technical Aspects ◽  
Feed Management ◽  
Smallholder Dairy ◽  
Cow Health

ABSTRAKPeningkatan produktivitas ternak dapat dicapai melalui perbaikan aspek teknis pemeliharaan yang meliputi perbaikan genetik, pakan, pengelolaan, perkandangan dan kesehatan ternak. Penelitian ini bertujuan untuk mengevaluasi penerapan aspek teknis pemeliharaan sapi perah berdasarkan Good Dairy Farming Practices (GDFP) pada peternakan sapi perah rakyat di Cibungbulang. Metode penelitian yang digunakan adalah survei dan pembagian kuisioner, observasi serta pengukuran langsung. Data dianalisis secara deskriptif dan disajikan dalam bentuk frekuensi tabulasi untuk menggambarkan karakteristik penerapan setiap aspek pemeliharaan sapi perah. Hasil penelitian menunjukkan bahwa pelaksanaan aspek teknis pemeliharaan sapi perah berdasarkan Good Dairy Farming Practices (GDFP) di peternakan rakyat Cibungbulang sebesar 69,75% pada musim hujan dan 67,25% pada musim kemarau. Aspek kesehatan ternak memperlihatkan nilai yang sangat rendah baik pada musim hujan maupun musim kemarau sehingga perlu mendapatkan perhatian khusus agar produktivitas ternak dapat ditingkatkan secara optimal.Kata kunci: biji kecipir, Trichoderma viride, pH, suhu, protein, serat kasarABSTRACTIncreased dairy cow productivity can be achieved through improving the technical aspects of maintenance which include genetic improvement, feed, management, housing and dairy cow health. This study was done to evaluate the application of the technical aspects of dairy cow maintenance based on the Good Dairy Farming Practices (GDFP) on smallholder dairy farm in Cibungbulang. The research method used was a survey and distribution of questionnaires, observations and direct measurements. Data were analyzed descriptively and presented in frequency tabulations to describe the characteristics and application each aspect of dairy cow maintenance. The results showed that the implementation of technical aspects of dairy cow maintenance was based on the Good Dairy Farming Practices (GDFP) at smallholder dairy farm in Cibungbulang i.e 69.75% in rainy season and 67.25% in dry season. The health aspect of dairy cow shows a very low value both in rainy and dry season so need special attention to increased productivity optimally.Keywords: dairy cow, technical aspects of maintenance, GDFP 

The role of record keeping and maintenance in enhancing decision making among smallholder dairy farmers in Gitugi Ward in Murang’a County, Kenya

2019 ◽  
Vol 36 (4) ◽  
pp. 535-545 ◽  
Author(s):  
Paul Maku Gichohi
Keyword(s):  
Decision Making ◽  
Management Practices ◽  
Basic Education ◽  
Dairy Farm ◽  
Sampling Technique ◽  
Dairy Farming ◽  
Dairy Farmers ◽  
Record Keeping ◽  
Ordinal Logistic Regression Analysis ◽  
Smallholder Dairy

Dairy farmers are expected to maintain farm records for aiding decisions making. However, the extent to which farm records inform decision making is not clear in Gitugi Ward in Murang’a County, Kenya. This study aimed to determine the role that record keeping and maintenance play in enhancing decision making of smallholder dairy farmers in that area. Descriptive survey research design was used to examine 175 smallholder dairy farmers. Simple random sampling technique was used in getting a sample size of 118 subjects. Data was collected using questionnaires and analyzed using SPSS. Ordinal logistic regression analysis was used to test the underlying proposition. Most smallholder dairy farmers have adequate experience in dairy farming and have minimum basic education, although not sufficient for making complex computations and interpretations for key decision making. The kind of decisions made based on dairy farm records statistically and significantly affect output in dairy farming businesses. Livestock Extension Officers should embark on advocacy programs, sensitization workshops, mentorship and training programs on record maintenance practices to ensure dairy farm records are preserved and utilized in supporting decision making. The findings of this study contribute to improvement of dairy farming information management practices and in making data-supported decisions among dairy farmers in Gitugi Ward, Mathioya Sub-County and in other geopolitical regions.

scholarly journals Evaluasi Aspek Teknis Pemeliharaan Sapi Perah Menuju Good Dairy Farming Practices pada Peternakan Sapi Perah Rakyat Pondok Ranggon

2016 ◽  
Vol 16 (2) ◽  
pp. 90 ◽  
Author(s):  
Anneke Anggraeni ◽  
Elmy Mariana
Keyword(s):  
Health Services ◽  
Measurement Data ◽  
Dairy Farm ◽  
Dairy Farming ◽  
Farming Practices ◽  
Dairy Farmers ◽  
Technical Aspects ◽  
Average Value ◽  
Feeding Management ◽  
Livestock Productivity

ABSTRAK. Peningkatan produktivitas ternak dapat dicapai melalui perbaikan genetik, pakan, manajemen dan modifikasi lingkungan. Penelitian ini bertujuan untuk mengevaluasi aspek teknis pemeliharaan sapi perah berdasarkan panduan Good Dairy Farming Practices (GDFP) pada manajemen pemeliharaan semi intensif di peternakan sapi perah rakyat Pondok Ranggon, Jakarta Timur. Aspek teknis pemeliharaan sapi perah yang dievaluasi meliputi aspek pemuliaan dan reproduksi, pakan, manajemen pemeliharaan, perkandangan, peralatan dan kesehatan ternak. Metode yang digunakan adalah survei, observasi dan pengukuran langsung. Data dianalisis secara deskriptif dan disajikan dalam bentuk frekuensi tabulasi untuk menggambarkan setiap karakteristik aspek pemuliaan dan reproduksi, pakan, manajemen pemeliharaan, perkandangan, peralatan dan kesehatan ternak. Hasil evaluasi aspek teknis yang dibandingkan dengan nilai rata-rata pelaksanaan GDFP di stasiun percontohan pemeliharaan sapi perah Pondok Ranggon menunjukkan bahwa pelaksanaan aspek teknis pemeliharaan sapi perah pada peternakan rakyat Pondok Ranggon termasuk dalam kategori cukup baik. Nilai rata-rata tertinggi pelaksana GDFP adalah pada aspek manajemen pemeliharaan, sementara aspek terendah adalah untuk kesehatan ternak. Kesimpulannya adalah pelaksanaan aspek teknis pemeliharaan sapi perah berdasarkan standar GDFP pada peternakan rakyat Pondok Ranggon harus ditingkatkan. (Technical aspects evaluation of dairy cow maintenance towards good dairy farming practices on pondok ranggon small holder dairy farm) ABSTRACT. Increasing livestock productivity can be achieved through genetic improvement, feeding, management and environmental modification. This study was aimed to evaluate various technical aspects in raising dairy cattle under semi intensive management at small dairy farmers in Pondok Ranggon (PR), Jakarta. Some technical aspects evaluated provided breeding, reproduction, feeding, management and health services. The methods used were by survey, observation and direct measurement. Data were analyzed descriptively then completed by tabulation frequencies to describe any characteristics of breeding decision, technical skills, daily management and health services. Evaluation on the considered technical aspects, compared to average values of Good Dairy Farming Practices (GDFP) showed that PR small dairy farmers in this study were categorized quite well. The highest average value of GDFP was for breeding and reproduction aspects, while the lowest one was for health services. It was concluded that PR small dairy farmers should be brought up for better management improvement.

Knowledge Test Development for Dairy Farmers To Measure Knowledge Level About Scientific Dairy Farming Practices

2019 ◽  
Vol 14 (04) ◽  
Author(s):  
Anupama Jena ◽  
Mahesh Chander ◽  
Sushil K. Sinha
Keyword(s):  
Item Analysis ◽  
Dairy Farming ◽  
Discrimination Index ◽  
Test Reliability ◽  
Knowledge Level ◽  
Farming Practices ◽  
Dairy Farmers ◽  
Knowledge Test ◽  
Level Of Significance ◽  
Difficulty Index

In the present study, a test was developed to measure the knowledge level of dairy farmers about scientific dairy farming. A preliminary set of 87 knowledge items was initially administered to 60 randomly selected dairy farmers for item analysis. The difficulty index and discrimination index was found out, and the items with difficulty index ranging from 30 to 80 and the discrimination index ranging from 0.30 to 0.55 were included in the final format of the knowledge test. A total of 48 items which fulfilled both the criteria were selected for the final format of knowledge test. Reliability of the test through split half method was found out to be 0.386 and the coefficient of correlation value by the test-retest method was 0.452, which was found to be significant at 1% level of significance. Hence, the knowledge test constructed was highly stable, reliable and validated for measuring what it intends to.

scholarly journals A Monitoring Study on Cattle Growth and Body Condition in Smallholder Dairy Farming System in Northern Vietnam

2006 ◽  
Vol 10 (1) ◽  
pp. 15-20 ◽  
Author(s):  
Kuniaki SUZUKI ◽  
Masaharu KANAMEDA ◽  
Shoji TACHIBANA ◽  
Takashi OGAWA ◽  
Thi Thanh Son DANG ◽  
...  
Keyword(s):  
Body Condition ◽  
Farming System ◽  
Dairy Farming ◽  
Northern Vietnam ◽  
Monitoring Study ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farming

Post Mount Merapi Eruption Recovery of Smallholder Dairy Farming: A Case Study of Disaster Management in Indonesia

2014 ◽  
pp. 129-142
Author(s):  
Mujtahidah Anggriani Ummul Muzayyanah ◽  
Suci Paramitasari Syahlani ◽  
Yuni Suranindyah ◽  
Fransiskus Trisakti Haryadi
Keyword(s):  
Disaster Management ◽  
Dairy Farming ◽  
Smallholder Dairy ◽  
Smallholder Dairy Farming

scholarly journals Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms

Animals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1690 ◽  
Author(s):  
Marianne Cockburn
Keyword(s):  
Machine Learning ◽  
Dairy Farm ◽  
Poor Performance ◽  
Dairy Farming ◽  
Training Data ◽  
Data Sources ◽  
Full Potential ◽  
Promising Tool ◽  
Public Data ◽  
Dairy Research

Dairy farmers use herd management systems, behavioral sensors, feeding lists, breeding schedules, and health records to document herd characteristics. Consequently, large amounts of dairy data are becoming available. However, a lack of data integration makes it difficult for farmers to analyze the data on their dairy farm, which indicates that these data are currently not being used to their full potential. Hence, multiple issues in dairy farming such as low longevity, poor performance, and health issues remain. We aimed to evaluate whether machine learning (ML) methods can solve some of these existing issues in dairy farming. This review summarizes peer-reviewed ML papers published in the dairy sector between 2015 and 2020. Ultimately, 97 papers from the subdomains of management, physiology, reproduction, behavior analysis, and feeding were considered in this review. The results confirm that ML algorithms have become common tools in most areas of dairy research, particularly to predict data. Despite the quantity of research available, most tested algorithms have not performed sufficiently for a reliable implementation in practice. This may be due to poor training data. The availability of data resources from multiple farms covering longer periods would be useful to improve prediction accuracies. In conclusion, ML is a promising tool in dairy research, which could be used to develop and improve decision support for farmers. As the cow is a multifactorial system, ML algorithms could analyze integrated data sources that describe and ultimately allow managing cows according to all relevant influencing factors. However, both the integration of multiple data sources and the obtainability of public data currently remain challenging.

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