Livestock Research for Rural Development 18 (10) 2006 Guidelines to authors LRRD News

Citation of this paper

Influence of manure and inorganic fertilizer on yield and quality of Vicia villosa intercropped with Sorghum almum in Ol-joro-orok, Kenya

T P Lanyasunya, Wang H Rong*, E A Mukisira,  S A Abdulrazak** and W O Ayako

Kenya Agricutural Research Institute (KARI)/Kenya
*Yangzhou University/Jiangsu Province / P.R. China
**Animal Science Department,.Egerton University /Kenya
planyasunya@yahoo.com


Abstract

This experiment was carried out at the regional research sub-station Ol'Joro Orok in Nyandarua District over a period of 2 years. Thirty-six plots of 2 x 2 sq. m were demarcated. Vicia villosa (common vetch) and Sorghum almum (Columbus grass) were allotted at random to three (3) treatment blocks (Manure [M]; Fertilizer [F] and control [C]). Each of the forages under investigation had 6 replicates in each block. Forage height was monitored on weekly basis over 12-week period using a one metre wooden ruler. Air and total dry matter (aDM and tDM) and chemical components were determined using standard procedures. The obtained values were used to predict forage digestibility of dry matter (DDM), dry matter intake (DMI), gross energy digestibility (% GED), relative feed value (RFV), relative feed quality (RFQ) and quality index (QI) using NRC and NFTA recommended equations. At the 19th week all plots were harvested (5 cm from the ground) to determine fresh matter yield (FMY) from which dry and organic matter yields (DMY and OMY) were derived. The data were stored in MS excel and later subjected to SPSS (2000) to determine descriptive statistics. One-way ANOVA and t-test were also applied to determine treatment differences.

At 12 weeks of age, forage height ranged between 28.6 - 36.4 cm (C); 36.2 - 45.2 cm (F) and 42.3 - 47.7 cm (M) for Vicia villosa. The significant differences in height observed between C and M or F were attributed to the supplied N and the climbing anchor provided by Sorghum almum. Dry matter contents were not significantly different. Pure vetch stand under M or F registered the highest CP level (18.3 and 18.7% in DM, respectively). The same was reflected in Sorghum almum (M - 11% and F - 11.1%). Significant differences were also observed on yields. In pure stand, common vetch plots receiving either manure or inorganic fertilizer recorded 32% (8.75 or 7.5 kg m-2) higher yields compared to C (5.95 kg m-2). Under intercrop, the same treatments also recorded 33.4% (3.5 or 3.38 kg m-2) higher yields compared to C (2.33 kg m-2). However, intercropping had negative implication on FMY of common vetch (ranging 5.95 - 8.75 kg m-2 pure stand and 2.33 - 3.5 kg m-2 intercropped: 59 - 60% less). A similar trend was observed with Sorghum almum (in pure stand: C - 8.7; M - 14.3 and F - 14 kgm-2 and under intercrop: C - 8.2; M - 9.6 and F - 10.8 kg m-2). RFV, RFQ and QI values were slightly higher for M and F compared to C.

It was therefore concluded that manure or fertilizer can significantly increase Common vetch and Columbus grass yields and improve the overall quality. However, intercropping negatively impacted on branching of both crops particularly vetch thereby reducing their biomass yields.

Key words: Dry and organic matter digestibility, gross energy digestibility, inter-cropping, quality index, relative feed quality, relative feed value


Introduction

In Kenya, the dairy sub-sector is predominantly a smallholder domain (Peeler and Omore 1997; Staal et al 1999; Conelly  1998; Thorpe et al 2000). Presently, dairy production in Kenya is threatened by a myriad of constraints. Inadequate nutrition is the single most critical constraint militating against increased dairy production, especially during dry season when forage quality and quantity is low. This is largely attributed to sub-division of land resources into small uneconomic units and the subsequent decline in soil fertility (which arises from continuous nutrient mining). This has led to rapid decline in fodder crop yields and therefore lack of adequate feed and  prevalence of malnutrition-related ailments on smallholder dairy farms. This is evidenced by the reported low milk yield per cow (average 7 kg/cow/d; Lanyasunya et al 1998), high rate of infertility (65%; Lokwaleput et al 1999), mortality and stagnation of dairy cattle population growth over the last decade (CBS 1999). The challenge therefore is how to enhance milk production on these farms. This calls for judicial utilization of cheaply available feed resources, application of cost effective forage production and utilization technologies, particularly those known to enhance soil fertility to ensure feed self-sufficiency throughout the year. Vicia sativa and Vicia villosa have widely been used to improve soil fertility and protein supplements for ruminants. Their excellent compatibility with cereals (such as Zea mays) when under sown is well recognized. They are however both less utilized in Kenya. One reason is that they are less known among smallholder farmers. It is strongly believed that their integration in the smallholder farming systems will offer an alternative to less cold tolerant but very popular forages such as Pennisetum purpureum (Napier grass). They have the potential of enhancing the quality of crop residues during the dry season.

The current study was conducted to determine the influence of age (growth stage) and secondary sources of nitrogen (N) on dry matter yield (DMY) and nutritive values of vetches and Columbus grass grown either as pure stand or intercrop. The goal was to find ways of enhancing feed availability through integration of cost effective fodder production and soil fertility improvement strategies into dairy farming systems particularly in the cooler, frost-prone dairying areas such as Nyandarua district.

The study area

Ol'Joro Orok division is relatively small and largely dominated by smallholder resource-poor farmers owning between 2.9 to 6.0 ha farms. Approximately half of the area is grazing land, with most of the farmers' income coming from dairy cows herds of between 3 and 10 heads (mix breed). Arable farming is based on maize, beans, potatoes and vegetables. Due to declining farm size, the production of wheat, barley and pyrethrum, which were previously the main crops, have decreased. The area has a hilly topography with altitudes around 2,400 meters above sea level. According to Jaetzold and Schmidt (1983), the area is classified as Upper Highland Wheat Pyrethrum Zone. Two major soil types are found in the area; moderately well drained, dark reddish-brown Luvisols ranging from 0.80 to 1.80 m depth, and extremely deep (> 1.80 m), well drained, red to reddish-brown nitisols (Kenya Soil Survey 1982). The soils of the area have a moderate to low fertility. Water-holding capacity is moderate with moderate to good soil work-ability (Jaetzold and Schmidt 1983). The subtropical highland climate of the area is influenced by its proximity to the equator and its altitude (Ojany and Ogendo 1973). Mean annual rainfall is around 980 mm, with rain falling throughout the year and peaks in April and July/August.


Materials and methods

This experiment was carried out (November 2002 to August 2004) in the forage experimental unit at the regional research sub-station Ol'Joro Orok in Nyandarua district. Ol'Joro Orok is a sub-station for the National Animal Husbandry Research Centre (NAHRC)/Naivasha. Thirty-six plots, of 2 x 2 sq. m, were demarcated and prepared (seedbed, shedding, fertilization) for establishment of the test forages: Vicia villosa (referred to in Kenya as common vetch) and Sorghum almum (Columbus grass) which were planted as pure stands or as mixtures in three blocks. The plots in each block were allotted at random to three (3) treatments (Manure [M]; Fertilizer [F] and Control [C]) with four replicates each per block (Figure 1)..

Experimental lay-out

Vicia sativa


Rep 1

Control

Manure

Fertilizer



Rep 2

Manure

Control

Fertilizer



Rep 3

Fertilizer

Manure

Control



Rep 4

Control

Fertilizer

Manure


Sorghum almum


Rep 1

Fertilizer

Manure

Control



Rep 2

Manure

Control

Fertilizer



Rep 3

Fertilizer

Manure

Control



Rep 4

Control

Fertilizer

Manure


Mixture


Rep 1

Manure

Control

Fertilizer



Rep 2

Fertilizer

Control

Manure



Rep 3

Fertilizer

Manure

Control



Rep 4

Control

Fertilizer

Manure


NB:    30 cm wide guard rows between plots and 60 cm wide between Replicatess

One to 5 day old dry sheep manure bulked in a heap outside the kraal and covered with a polythene sheet to minimize effects of either rain, winds or sunshine was used, Diammonium phosphate, (NH4)2HPO4 (DAP: 18 - 46 - 0) and Calcium Ammonium Nitrate CAN (50% N) fertilizers were used to fertilize the soil at the rate of 50 kg/acre (Snijders 1995) which translated to 49.5 g/4 m2.

In the absence of rainfall, moderate soil moisture level was maintained manually through a watering can. Watering was done once after every 3 days for the first 2 weeks and once after 5 days thereafter. All plots received equal amount of water.

Sampling for chemical analysis commenced 4 weeks after planting. Samples were harvested 5 cm from the ground. They were chopped using hand operated chuff cutter to small pieces (2 cm long), mixed thoroughly and 2 composite samples (500 gm each) were taken from each test forage plot for laboratory analysis. DM on fresh herbage was determined by drying the samples at 65o C for 24 h. These samples were then milled and residual moisture determined by drying at 105o C for 24 h, before  subjecting the samples to chemical analysis.

Ash content was determined by ashing in a muffle furnace at 550o C for 3 h (Abdulrazak and Fujihara 1999). Crude protein content was analyzed by the Kjeldahl method (%N x 6.25). Acid detergent fibre (ADF), neutral detergent fibre (NDF) and acid detergent lignin (ADL) were determined according to Van Soest et al (1991) and AOAC (1988). Hemicellulose and cellulose were determined as described by Abdulrazak and Fujihara (1999). Mineral profiles were determined according to Varma (1991) and Fick et al (1999).

The obtained values were used to predict forage digestibility (DDM), intake (DMI), gross energy digestibility (%GED), relative feed value (RFV), relative feed quality (RFQ) and quality index (QI). Digestible dry matter (DDM) was calculated from ADF using the equation defined by Grant (1994). At the end of the trial fresh matter yield (FMY) was determined by harvesting the whole herbage in each plot at 5 cm above the ground. The harvested herbage was immediately weighed using field-weighing balance (50 kg). The data collected for 9 weeks (4 - 12) were used to demonstrate variation in growth among treatments.

The data were stored in MS Excel (2000) and later subjected to SPSS (2003) to determine descriptive statistics. One-way ANOVA and t-test were also applied to investigate the statistical differences between treatments.


Results

The results showing the influence of treatment on DM, OM, chemical composition, Yield (tonnes/ha), DDM, GED and quality (RFV; RFQ and IQ) of Vicia villosa intercropped with Sorghum almum harvested at the age of 18 weeks, are presented in table 1 and 2.


Table 1.  Influence of manure and inorganic fertilizer on chemical composition of Vicia villosa intercropped with Sorghum almum harvested at the age of 18 weeks

 Components

Vicia sativa pure stand

Vicia sativa in Sorghum almum  mixture

Control

Manure

Fertilizer

Control

Manure

Fertilizer

Dry matter, %

22.7

26.1

24.2

24.6

26.7

24.5

As % of DM            

Organic matter

82.8

84.8

82.8

83.6

82.1

81.7

Crude Protein

16.6

18.3

18.7

15.4

16.2

16.9

Neutral detergent fibre

57.4

56.8

54.3

56.6

57.2

58.2

Acid detergent fibre

47.2

43.8

43.6

48.5

47.8

46.3

Acid detergent lignin

12

12.2

10

10.9

8.6

10.1

Hemicellulose

10.3

13

10.7

8.1

9.8

11.9

Cellulose

41.3

31.6

33.6

37.6

38.8

36.2

Ash

8.2

6.8

8

6.9

8.9

9.4

 



Table 2.  Influence of manure and inorganic fertilizer on yield and quality of Vicia villosa intercropped with Sorghum almum harvested at the age of 18 weeks

Components

Vicia sativa  pure stand

Vicia sativa in Sorghum almum  mixture

Control

Manure

Fertilizer

Control

Manure

Fertilizer

Average fresh weight yield, kgm-2

5.95

8.75

7.5

2.33

3.5

3.38

Av. total dry matter yield, kgDMm-2

1.23

2.09

1.65

0.52

0.85

0.76

Av. organic matter yield, kgOMm-2

1.12

1.93

1.51

0.48

0.76

0.69

Digestible dry matter, % DDM

52.1

54.8

54.9

51.1

51.7

52.8

Est. Fresh matter yield, Ton. FMha-1

59.5

87.5

75

23.3

35

33.8

Est. Dry matter yield, Ton. DMha-1

13.5

22.8

18.2

5.7

9.3

8.3

Est. Org. matter yield, Ton. OMha-1

11.2

19.3

15.1

4.8

8.5

7.6

Dig. Dry matter yield, Ton. DDMha-1

7.03

12.49

9.99

2.9

4.81

4.38

Gross energy digestibility, %

48.5

49.6

49.7

48.1

48.4

48.8

Relative feed value, RFV

84.4

89.6

94.1

84.0

84.2

84.3

Relative Feed Quality, RFQ

79.7

84.9

89.1

79.2

79.8

79.7

Quality Index, QI

1.09

1.16

1.21

1.09

1.1

1.09

ha = hectare (1 ha = 10 000 m2); DDM = Digestible Dry Matter = 88.9 - (.779 x %ADF) (Bath and Marble 1989; Grant 1994); DMI = Dry Matter Intake = 120 / %NDF; RFV = DDM x DMI / 1.29 (Moore and Undersander 2002; Jeranyama and Garcia 2004); RFQ = (DMI, % of BW) * (TDN, % of DM) / 1.23. ((Moore et al. 1996; Moore and Undersander 2002; Jeranyama and Garcia 2004); QI = .0125 * RFQ + .097 (Moore and Undersander 2002; Jeranyama and Garcia 2004); GED = 57.1 + 0.150CP – 0.234ADL (Haj-Ayed et al 2000); TDN = 82.38 - (0.7515 x ADF) (Bath and Marble 1989; Putnam and de Peters 1997)


The DM,  OM and cell wall components were not different among treatments (P>0.05). A slight elevation in %CP was however observed in pure Vicia villosa stand under M and F treatments. Large differences in yield were observed between Vicia villosa pure stand and that intercropped with Sorghum almum (Table 2). Fresh matter yield (FMY; kgm-2 or tonha-1) in Vicia villosa pure stand were higher than that of Vicia villosa in Sorghum almum mixture (Table 2) (P<0.01). Though not significantly different, slight elevations were noted in the derived values (DDM, GED, RFV, RFQ, QI for M and F treatments. This was similarly reflected in estimated Dry matter yield (Ton. DMha-1) and Organic matter yield (Ton. OMha-1; P<0.05). Generally DM, OM and cell wall component were not significantly different for Sorghum almum under the 3 treatments (Table 3; P>0.05).


Table 3.   Influence of manure and inorganic fertilizer on chemical composition of Sorghum almum in pure stand or intercropped with Vicia villosa harvested at the age of 18 weeks

Components

Sorghum almum pure stand

Sorghum almum  in Vicia sativa mixture

Control

Manure

Fertilizer

Control

Manure

Fertilizer

Dry matter, %

20.9

19.1

19.3

21.5

18.3

18.8

As % of DM            

Organic matter

84.6

85.2

84.4

84.5

85.8

85.3

Crude Protein

8.7

11

11.1

9.6

10.4

10.8

Neutral detergent fibre

70

66.7

67.1

69.7

68.0

68.1

Acid detergent fibre

38.1

31.7

35.4

32.3

34.9

37.9

Acid detergent lignin

6.9

7.7

6.7

5.9

5.8

6.2

Hemicellulose

31.9

35

31.7

37.4

33.1

30.2

Cellulose

31.2

24

28.7

26.4

29.1

31.7

Ash

6.7

5.4

7.3

6.9

6.1

6.1


Slightly higher crude protein content was observed for M and F treatments. Mean heights of Sorghum almum under M and F were evidently higher compared to C.  The mean fresh matter yields for M and F within pure stand blocks were significantly higher compared to C (Table. 4).


Table 4.  Influence of manure and inorganic fertilizer on yield and quality of Sorghum almum in pure stand or intercropped with Vicia villosa harvested at the age of 18 weeks

Components

Sorghum almum pure stand

Sorghum  almum  in Vicia sativa mixture

Control

Manure

Fertilizer

Control

Manure

Fertilizer

Total fresh weight yield, kgm-2

8.7

14.3

14

8.2

9.6

10.8

Av. total dry matter yield, kgDMm-2

1.67

2.47

2.48

1.61

1.63

1.86

Av. total Organic matter yield, kgOMm-2

1.41

2.11

2.09

1.36

1.40

1.59

Digestible dry matter, % DDM

59.2

64.2

61.3

63.7

61.7

59.4

Est. Fresh matter yield, Ton.FMha-1

87

143

140

82

96

108

Est. dry matter yield, Ton.DMha-1

16.7

24.7

24.8

16.1

16.3

18.6

Est. Total Organic matter yield, TonOMha-1

14.1

21.1

20.9

13.6

14.0

15.9

Est.  Dig. Dry matter yield, Ton.DDMha-1

8.4

13.6

12.8

8.7

8.6

9.4

Gross energy digestibility, %

56.79

56.95

57.20

57.16

57.30

57.27

Relative feed value, RFV

184.2

223.8

217.7

206.4

211.2

208.8

Relative Feed Quality (RFQ)

175.4

214.1

207.8

197.4

201.6

198.8

Quality Index (QI)

2.29

2.77

2.69

2.56

2.62

2.58

DMI = -2.318 + .442*CP -.0100*CP2 - .0638*TDN + .000922*TDN2+ .180*ADF - .00196*ADF2 - .00529*CP*ADF (Moore and Kunkle 1999 model recommended for grasses); DMI = DM intake, % of BW; TDN = total digestible nutrients, % of DM;)



Discussion

Both Vicia villosa and Sorghum almum under intercrop performed poorly in terms of fresh matter yields. Since the same seed and fertilizer rates were applied to all plots, the only factor attributed to the low yield was the non-complementary effect they seemed to have on each other. It was observed that Sorghum almum grew faster and more vigorously hence providing a shading effect to Vicia villosa at a critical leaf and branching stage. Vicia villosa on the other hand seemed to have a negative effect on Sorghum almum's early tillering. The obtained RVF, RFG and QI values for Sorghum almum were higher compared to those for Vicia villosa. This was attributed their differences in cell wall components. Some of the NFTA and NRC recommended equations used to derive quality indices for forage feeds, particularly in cooler areas, were used in the current study with a purpose of establishing the feeding value of the forages under investigation. Relative feed value index (RFV) is an index used to ranks cool season legumes, grasses and mixtures by potential digestible dry matter intake (Rohweder 1984; Mertens 1985). It enables allocation of forages to the proper livestock class with a given level of expected performance. RFV is calculated from digestible dry matter and dry matter intake. Quality index (QI) was developed as an overall index of forage quality. Relative Feed Quality (RFQ) is an improved version of RFV. It is an estimate of voluntary intake of available energy when forage is fed as the sole source of energy and protein. It adds measures for fiber digestibility as well as quantity. The intake component is DMI as a percentage of BW, as in RFV, and the available energy component is TDN (% of DM), as in QI. Digestible dry matter is an estimate of the total digestibility of the feed and is calculated from acid detergent fiber. Dry matter intake is an estimate of the amount of feed an animal will consume in percent of body. The developers of the models recommend that these equations with DDM, DMI, and RFV calculations are applicable to legume, legume-grass and cool season grass fresh forages, hays and hay-lages. It was on this basis that they were adapted in the current study. Application of either manure or fertilizer increased the RFV, RFQ and QI suggesting an increase in quality. This was slightly below the starting point according the RFV scale. According to RFV scale, RFV below 100 is considered lower than basic starting point, which is RFV 100. High producing dairy cows require a feed with RFV above 130.


Conclusion


References

AOAC (Association of Official analytical chemistry) 1988 Official method of analyses 15th Edition, AOAC. Washington, D.C. USA.

Abdulrazak S A and Fujihara T 1999 Animal Nutrition: A Laboratory manual. Kashiwagi printing Co. Japan. pp 32 - 39.

Bath D L and Marble V L 1989 Testing alfalfa for its feeding value (University of California leaflet 21457) http://alfalfa.ucdavis.edu/quality/TestingAlfalfa.pdf

Conelly W T 1998 Colonial era livestock development policy: Introduction of improved dairy cattle in high-potential farming areas of Kenya. World Development 26: 1733-1748.

CBS (Central Bureau of Statistics) Statistical abstract 1999 CBS, Office of the President and Ministry of Planning and National Development, Nairobi, Kenya.

Duke J A 1981 The gene revolution. Paper 1. p. 89-150. In: Office of Technology Assessment, Background papers for innovative biological technologies for lesser developed countries. USGPO. Washington.

Fick K R, McDowell L R, Miles P H, Wilkinson N S, Funk J D and Conrad J H 1999 Methods of mineral analysis for plant and animal tissues. 2nd Edition, University of Florida. Gainsville. USA.

Grant R 1994 Feeding and Nutrition. University of Nebraska - Lincoln. Institute of Agriculture and Natural Resources. Cooperative Extension Services. USA.

Haj-Ayed M, González J, Caballero R and Alvir M R 2000 Nutritive value of on-farm vetch-oat hays. Voluntary intake and nutrient digestibility. Annales de Zootechnie 49: 381-389

Jaetzold R and Schmidt H 1983 Farm Management Handbook of Kenya, vol.2, Part B (Central Kenya), Ministry of Agriculture, Nairobi, Kenya.

Jeranyama P and Garcia A D 2004 Understanding Relative Feed Value (RFV) and Relative Forage Quality (RFQ). Cooperative Extension service. College of agriculture and biological sciences. South Dakota state University. USA. pp 1-3. http://agbiopubs.sdstate.edu/articles/exex8149.pdf

Kenya Soil Survey 1982 Exploratory Soil Map and Agroclimatic Map of Kenya. Kenya Soil Survey, Nairobi, Kenya.

Lanyasunya T P, Wekesa F W, Osinga A and de Jong R 1998 On-farm testing of improved calf rearing technologies in Naivasha, Kenya. Proceedings of the 2nd International symposium of the African Association of Farming Systems, Research-Extension an Training (AAFSRET), 21 - 23 August 1996, Ouagadougou, Burkina Faso. pp 529 - 541.

Lokwaleput I K, Siamba D N and de Jong R 1999 Improved cow fertility through appropriate management practices on-farm in Koibatek and Nakuru Districts. In: R de Jong and E A Mukisira (Editors). Testing of livestock technologies on smallholder mixed farms in Kenya. Pp. 85 - 103.

Mertens D 1985 Effect of fiber on feed quality for dairy cows. In Proceedings of the Minnesota Nutrition Conference. pp 204-224.

Moore J E, Burns J C and Fisher D S 1996 Multiple regression equations for predicting Relative Feed Value of grass hays. pp 135 - 139. In: M J Williams (Editor) Proceedings of the American Forage and Grassland Conference, Vancouver, BC. AFGC, Georgetown. TX. USA.

Moore J E and Kunkle W E 1999 Evaluation of equations or establishing voluntary intake of forages and forage-based diets. Journal of Animal Science (Supplement 1): 204

Moore J E and Undersander D J 2002 Relative Forage Quality: An alternative to relative feed value and quality index. In: Proceedings of the 13th Annual Florida Ruminant Nutrition Symposium, January 10 - 11, University of Florida, Gainsville. pp 16 - 32. http://www.animal.ufl.edu/dairy/2002ruminantconference/moore.pdf

Ojany F F and Ogendo R B 1973 Kenya - A study in physical and human geography. Longman, Nairobi, Kenya.

Peeler E J and Omore A 1997 Manual of livestock Production Systems in Kenya. 2nd Edition. KARI (Kenya Agricultural Research Institute), Nairobi, Kenya. pp 138.

Putnam D D and DePeters E 1997 Progress in standardizing hay testing in California. California Hay Testing Consortium Report (1995-96). Agricultural experiment station. University of California, Davis. USA. http://www.agronomy.ucdavis.edu/agronomy/apr/apr255.pdf

Rohweder D A 1984 Estimating forage hay quality. In National Alfalfa Hay Quality Testing Workshop. pp 31-37 Chicago, IL. March 22-23.

SPSS (Stastistical Programs for Social Scientists) 2003 Apache software foundation. USA.

Staal S J, Kruska R, Balteweck I, Kenyanjui M, Wokabi A, Njubi Thornton P, and Thorpe W 1999 Combined household and GIS analysis of smallholder production systems: An application to intensifying smallholder dairy systems in central Kenya. Paper presented at the 3rd international symposium of Systems Approaches for Agricultural Development (SAAD-III) held in Lima, Peru, 8-10th November 1999, National Agrarian University, La Molina, Lima, Peru.

Snijders P J 1995 Influence of manure on dry matter yields of Napier, Sweet potato vines and Desmodium in Zero grazing system. NAHRC. Naivasha, Kenya.

Thorpe W, Muriuki H G, Omore A, Owango M O and Staal S 2000 Dairy development in Kenya: The past, the present and the future. Paper presented at the annual symposium of the Animal Production Society of Kenya, Nairobi, Kenya, 22-23 March 2000.

Van Soest P J, Robertson J B and Lewis B A 1991 Method for dietary fibre, Neutral detergent fibre and non starch polysaccharides in relation to animal nutrition. Journal of Dairy Science. 74: 3588 - 3597. http://jds.fass.org/cgi/reprint/74/10/3583

Varma A 1991 Handbook of inductively coupled plasma atomic emission spectroscopy. CRC press, Boca Raton Florida. pp 380.

Weiss W P 1998 Estimating the available energy content of feeds for dairy cattle. Journal of Dairy Science. 81: 830 - 839.


Received 14 April 2005; Accepted 14 March 2006; Published 4 October 2006

Go to top