TECHNICAL COEFFICIENTS

Production parameters

Economic model building requires estimates of technical coefficients relating to mortality, fertility and parturition. Gathering such information for Indonesia is a very difficult task because of the wide diversity of agricultural producing regions and because small farmers - who generally do not keep good records - are such an important part of the livestock sector. By developed country standards, the productivity of animals is often low.

Zemmelink and Subagiyo (1992) investigated the use of metabolizable energy in East Java using data from the 1980s. They conducted a number of analyses. One of their results was that “maintenance and production of the existing herd accounts for less than half” (p196) of the metabolizable energy available, suggesting that liveweight gain could be doubled by keeping more animals to utilize the wasted materials. However, they point out that for this to happen, large amounts of supplements would be necessary because of the poor quality of the available roughage to livestock farmers in East Java. Zemmelink and Subagiyo point out that great care needs to be used in analyses of the type they carried out. They explain that data on a regional basis and by season are needed.[21] Also information on voluntary intake of feeds and animal response to different feed types would be required for a full understanding of the increased production potential.

Information on production parameters is valuable gaining an understanding the management processes of farmers. Perkins and Semali (1992) set out to investigate why Indonesian farmers sell cattle at a young age. They gathered data at the village level and found that early growth was relatively rapid, but it soon fell away. Average weight gain in the two breeds they considered - Ongole and Bali cattle - averaged only 200 g. per day after 12 months. Farmers estimated that the additional labour to raise a calf was 0.3 to 0.5 hours per day in the first two quarters of the calf development, but it then rose steadily to two hours per day to reach a plateau at 24 months. This meant that for farmers with alternate employment opportunities, it is rational for them to sell cattle young - at 9 to 18 months of age.

Data collected from farmers in West Java and reported by Bazeley, Supriantna and Banga (1992) indicated that the median calving interval on dairy farms was 684 days. This prolonged calving interval was costing farmers up to Rp. 200000 per cow per year in 1992. INI ANSREDEF (1995) also commented upon the “low calving rate, caused by prolonged calving interval” (p23) in the dairy industry. Reasons they provided included the length of time between calving and the first service; the requirement for many services per conception; and a high abortion rate.

Most of the available technical parameters are old and may not now be applicable. Officials associated with the poultry industry say that the technical parameters of that industry are similar to those obtained in high income countries. This is probably correct because such technologies are easily transferred from one country to another. Table 53 presents estimates of technical parameters for the egg and dairy industries that are based upon results obtained in the early 1980s. Table 54 data, commonly cited in discussions of Indonesia’s livestock sector, are based upon data from the 1970s. This raises doubts about the applicability of the data for the late 1990s.

Table 53. Egg & milk production parameters, Indonesia

Item		Native chicken	Layer	Duck	Dairy cattle
		(%)	(%)	(%)	(%)
Productive females in the population		30	60	60	42
Average production per head
	milk(a) (litres)				13.3
	kilograms	1.4	10.8	120
Average production per head per year by usage
	consumed	50	98	70	87.5
	spoiled	25	0.5	15	2.5
	hatched	25	1.5	15
	for calf rearing				10

Note: Data are for 1982 with the exception of the data from INI ANSREDEF (1995) which was for 1993.

Source ^(a) INI ANSREDEF (1995); Directorat Bina Program Directorat Jenderal Peternakan (1991), Buku Statistik Peternakan [Statistical Book on Livestock], p. 105.

Table 54. Percentage of livestock births per species, 1979

Livestock species	Births	Birth percentage by sex to number of births
		Male	Female
	(%)	(%)	(%)
Beef cattle	18.31	44.67	55.33
Dairy cattle	22.83	40.77	59.23
Buffalo	17.45	44.3	55.7
Horse	8.77	47.18	52.84
Goat	33.12	42.51	57.49
Sheep	36.4	41.79	58.21
Pig	70.84	50.78	49.22

Notes: Birth percentage based upon livestock numbers at beginning of year

Source: Direktorat Bina Program Direktorat Jenderal Peternakan (1990), Buku Statistik Peternakan 1990, p. 87

Table 55. Percentage of livestock mortality by species, 1979

Livestock species	Deaths	Cause of death
		Chronic	Acute	Others
	(%)	(%)	(%)	(%)
Beef cattle	2.16	21.32	54.14	24.54
Dairy cattle	4.1	45.29	54.71	na
Buffalo	4.14	27.78	56.09	16.13
Horse	3.5	23.36	56.16	20.48
Goat	3.87	21.7	50.92	27.38
Sheep	3.73	17.95	55.58	26.47
Pig	13.85	16.15	58.44	25.41

Notes: Deaths as a percentage of population at start of year

Source: Direktorat Bina Program Direktorat Jenderal Peternakan (1990), Buku Statistik Peternakan 1990, pp. 87, 84

Lebdosoekojo and Reksohadiprodjo (1982) describe the south east Asian livestock industries as being an important part of the agricultural and ecological balance, especially in the heavily populated regions. Agricultural products are used mainly by the human population and this handicaps the livestock industries, particularly the poultry, swine and dairy industries. Agroindustrial wastes are important and this means that consideration must be given to their availability, the nutritive value and efficiency of rations, relative prices, the level of technology and social acceptability. Lebdosoekojo and Reksohadiprodjo explain that feed substitutes can be classified into energy feeds, protein feeds and roughage depending upon their chemical composition.

• Energy feeds, which include crop and agroindustrial residues (CAIR), have less than 20% protein and less than 18% crude fibre or less than 35% cell wall
• Protein foods include products that contain 20% or more of protein. These can be of plant or animal origin.
• Roughage are usually all products of crop residue, and contain more than 18% crude fibre or more than 35% cell wall.

Table 56 lists the estimated production and crude protein and energy (TDN) content of crop and agro industrial residues in Indonesia on a dry matter basis.

Table 56. Estimated production and crude protein and energy (TDN) content of crop and Agroindustrial residues in Indonesia, dry matter basis, 1979

Product		Quantity	Crude protein	Total digestible nutrients
		(kt)	(%)	(%)
Energy feeds
Conventional
	rice bran	2577	10.7	81.0
	maize bran	403	14.2	90.9
	molasses	343	1.8	53.0
Nonconventional
	cassava pomace	157	2.6	89.1
	cassava peelings	5000	3.3	60.7
	gnetum gnemon pulp	na	17.4	40.1
	coffee pulp	89	18.9	47.6
	citrus pulp	6	6.5	43.6
	cocoa husk	1.5	7.4	46.5
	pineapple bran	0.05	3.5	72.0
	banana fruit waste	22.4	6.1	62.8
Protein feeds
Conventional
	copra meal	344	21.6	69.3
	peanut meal	11	40.6	52.3
	palm kernel meal	2.2	22.2	58.5
	trash fish & wastes (fish meal)	355	61.9	69.0
Non conventional
	kapok meal	na	32.8	41.6
	rubber seed	na	18.8	62.0
	leucaena seed	na	31.3	59.5
	soybean curd sludge	na	31.4	52.6
	soysauce sludge	na	27.8	80.5
	cassava leaf meal	1410	22.0	57.8
	leucaena leaf meal	na	22.3	72.5
	sesbania leaf meal	na	25.8	63.0
	snail meal	na	51.2	65.1
Roughage
Conventional
	peanut vines	1025	13.9	67.2
	maize stalk	19745	6.5	46.6
	sorghum stalk	na	6.5	41.4
	sugar cane tops	174.8	5.4	46.6
Nonconventional
	rice straw	34215	5.5	26.6
	soybean straw	na	7.7	50.7
	sweet potato leaf	555	14.6	72.4
	bagassa	1717.3	2.0	49.4
	sago waste	na	1.8	19.5

Source: Lebdosoekojo and Reksohadiprodjo (1982), p. 81

Gunawan (1995) points out that there is a large gap between maximum and actual output from parts of Indonesia’s agriculture. To support this view, he presented the data in Table 57. While rice yields are high, perhaps reflecting the priority the government has attached to this industry, most secondary crops are well below their potential yields. Obviously this has implications for the prospects of the livestock industries. Any expansion of these industries will require increased use of secondary crops as animal feed.

Table 57. Actual and percent of maximum potential productivity of some food crops in Indonesia

Crop	Actual productivity(a)	Per cent of maximum(b)
	(t.)	(%)
Paddy	4.2	85
Soybean	1.4	40
Cassava	12.1	30
Corn	2.2	30
Sweet potato	9.5	30
Ground nut	1.0	30
Mungbean	0.85	30

Notes: ^(a) CBS data, 1992; ^(b) Based on author’s projection (Memed Gunawan)