Expanding the contribution of dairy goats in efficient and sustainable production systems

2014 ◽  
Vol 54 (9) ◽  
pp. 1198 ◽  
Author(s):  
J. B. Liang ◽  
C. Devendra

Goats contribute significantly to human nutrition, food security and income of resource-poor small farmers in Asia, Africa and beyond. Because of the high content of mono- and polyunsaturated fatty acids in goat milk, it is beneficial for human health resulting in it being sold at premium prices of three to nine times the price of cow milk in countries like China, Malaysia, Indonesia and Thailand. Goats play a significant role in farming systems that directly impact on the capacity of rural farmers striving for the objective of sustainable food production systems. Increasing sustainable food production, particularly of animal proteins, presents major challenges to these small farms in the face of massive demands that are driven by rapid growth of human populations and increased availability of disposable income. In the last two decades, expanding market demand for goat milk has resulted in the establishment of commercial dairy goat farms in several newly developed South-east Asian countries. Major challenges to expanding production exist, and include ways to utilise the well-adapted features inherent in goats and their potential production to benefit the small and commercial farmers alike. Increasing the knowledge base is a priority to stimulate improved production systems and, increased the income of dairy goat farmers and other people involved in the industry. The recent establishment of the Asian-Australasian Dairy Goat Network supported jointly by FAO and Universiti Putra Malaysia, and national programs of participating countries, are committed to address these objectives and facilitate much-needed improvements to sustain dairy goat production systems in Asia and beyond.

1991 ◽  
Vol 15 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Michael Brklacich ◽  
Christopher R. Bryant ◽  
Barry Smit

2014 ◽  
Vol 3 (6) ◽  
pp. 160 ◽  
Author(s):  
Mburu Monica ◽  
Mugendi Beatrice ◽  
Makhoka Anselimo ◽  
Muhoho Simon

<p>In Kenya use of exotic dairy goats in breeding programmes for smallholder production systems has become popular, but information on the milk production is scarce. A study was carried out to assess the milk yield of dairy goats reared in high potential and semi arid areas of Nyeri County. This involved 190 smallholder farmers rearing Alphine dairy goats in Nyeri County and registered with Dairy Goat association of Kenya (DGAK). Which formed 100% sampling of the population under study. The grade, feeding practices and age of the dairy goats were evaluated. The dairy goat average milk production was 1.90 litres per day, with the appendix grade in Kieni East giving the highest production of 2.69 liters per day while foundation grade in Mukurweini gave the lowest, 0.98 litres per day. The higher milk production in Kieni East, which is a semi arid area, was noted to be due to good feeding practices where 43% of the farmers used concentrates during milking and also 48% supplemented the feed with minerals. In the high potential area of Mukurweini none of the farmers used mineral supplements with only 5% using concentrates during milking. The age of the dam significantly affected the average milk production, with the onset of production being the age of 2.0 years, reaching the peak at the age of 6.5 years. Kieni East, gave the highest production of 4.2 litres at the age of 6 years. The results demonstrated that the low-input farming conditions affected the Alphine goats milk production.</p>


Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 814
Author(s):  
Riccardo Testa

Agriculture has always played a key role in feeding the world population and ensuring the development of sustainable food production systems [...]


Soil Systems ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 69
Author(s):  
John Walker Recha ◽  
Kennedy O. Olale ◽  
Andrew Sila ◽  
Gebermedihin Ambaw ◽  
Maren Radeny ◽  
...  

A novel total ensemble (TE) algorithm was developed and compared with random forest optimization (RFO), gradient boosted machines (GBM), partial least squares (PLS), Cubist and Bayesian additive regression tree (BART) algorithms to predict numerous soil health indicators in soils with diverse climate-smart land uses at different soil depths. The study investigated how land-use practices affect several soil health indicators. Good predictions using the ensemble method were obtained for total carbon (R2 = 0.87; RMSE = 0.39; RPIQ = 1.36 and RPD = 1.51), total nitrogen (R2 = 0.82; RMSE = 0.03; RPIQ = 2.00 and RPD = 1.60), and exchangeable bases, m3. Cu, m3. Fe, m3. B, m3. Mn, exchangeable Na, Ca (R2 > 0.70). The performances of algorithms were in order of TE > Cubist > BART > PLS > GBM > RFO. Soil properties differed significantly among land uses and between soil depths. In Kenya, however, soil pH was not significant, except at depths of 45–100 cm, while the Fe levels in Tanzanian grassland were significantly high at all depths. Ugandan agroforestry had a substantially high concentration of ExCa at 0–15 cm. The total ensemble method showed better predictions as compared to other algorithms. Climate-smart land-use practices to preserve soil quality can be adopted for sustainable food production systems.


Pulse Foods ◽  
2021 ◽  
pp. 487-506
Author(s):  
Anushree Priyadarshini ◽  
Brijesh K. Tiwari ◽  
Gaurav Rajauria

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