Livestock Research for Rural Development 18 (12) 2006 Guidelines to authors LRRD News

Citation of this paper

Bio-economic analysis of expenditure on inputs and output value from crops and grade dairy cattle sub systems in Vihiga, Kenya

P M Ongadi, R G Wahome*, J W Wakhungu*, L O Okitoi and K Otieno

Kenya Agricultural Research Institute - Kakamega, Kenya; P.O Box 169, Kakamega
ongadimp@yahoo.com
*Animal Production Department, University of Nairobi, Kenya; P.O. Box 29053, Nairobi

Abstract

This study analyzed expenditure on inputs and output value from crops and grade dairy cattle sub-systems and contribution to grade dairy cattle owning households' farm incomes in Vihiga. Information was collected through a pre-tested structured questionnaire, administered to a purposive sample of 236 grade dairy cattle owning households from April to August 2005.

Grade dairy cattle production systems significantly influenced (P<0.05) total household expenditure on inputs and output value for the grade dairy cattle sub-system and tea crop for the crops sub-system. On the contrary, grade dairy cattle breed types had no substantial influence (P>0.05) on total household expenditure on inputs and output value from both grade dairy cattle and crops sub-systems. Further, both grade dairy cattle production systems and breed types had little influence (P>0.05) on gross margins of the two sub systems. The cash output - input ratios for grade dairy cattle and crops sub systems in the four production systems were similar and above 1.9. There was little interaction (P>0.05) between production systems and breed types. Generally, grade dairy cattle contributed 70% of the total grade dairy cattle owning households' farm income while crops contributed 30% highlighting its importance in mixed small scale farming systems.

Key Words: Crops and grade dairy cattle sub-systems, expenditure on inputs, output values


Introduction

Dairy farming in the mixed small scale farming systems of Western Kenya ranks second to maize and beans in contribution to household incomes and food security (Wangia 1998). However, recent studies (Waithaka et al 2002) indicate that production and profitability indices are lower than could have been realized from the favourable climatic conditions and relatively high genetic potential of the grade dairy cattle in the area. The challenge is whether the dairy cattle represent a burden on the system (McDowell and Hilderbrand 1980; Udo et al 1992; Chilonda et al 2000), consuming resources that could be used to increase crop productivity or whether the mixed small scale farmer utilizes the animals to improve outputs of the mixed farm system (Utiger et al 2000; Zemmelink et al 1999).

There requires systematic analysis of expenditure on inputs and output value from grade dairy cattle and crops sub-systems (Phung and Koops 2003; Hella et al 2001; Patil and Udo 1997; Lanyasunya et al 2005; Widodo et al 1994a,b) in the existing grade dairy cattle production systems of Vihiga, Kenya. In addition, information is required to support grade dairy enterprise development due to the changing farming systems, increased demand for dairy products (de Jong 1996; Delgado et al 2001; Nicholson et al 2001) and opportunities or increased financial incentives for investment in dairy cattle enterprises (Islam 1995; Morton and Mathewman 1996). The purpose of this study therefore, was to quantify and analyze expenditure on inputs and output value from crops and grade dairy cattle sub-systems and thereby determine their respective contribution to grade dairy cattle owning households' farm incomes.


Materials and methods

Study area

The study was undertaken in Vihiga District, Western Kenya, which is a high agricultural potential area predominantly (95%) in the upper midland one (UM1) agro-ecological zone, with an altitude ranging between 1300 to 1800 metres above sea level, average temperatures of 20.30C and well drained soils that comprise dystric acrisols and humic nitrosols (Jaetzold and Schmidt 1983). The area receives bimodal rainfall that ranges from 1,800 to 2,000 mm per year.

Description of grade dairy cattle production systems

Waithaka et al (2002) characterized dairy cattle production systems in Western Kenya as being: Grazing only (free grazing or tethered), Mainly grazing with some stall-feeding, Mainly stall-feeding with some grazing and Stall-feeding only (zero-grazing) based on the level of intensification and feeding systems. In intensive grade dairy cattle production systems (Stall feeding only and Mainly stall feeding with some grazing), animals are mainly stall fed ('cut-and-carry') with napier grass as the basal feed resource. While in extensive grade dairy cattle production systems (Grazing only and Mainly grazing with some stall feeding), animals are mainly grazed on natural pastures.

Data collection and analysis

A purposive sample of 236 grade dairy cattle owning households were interviewed using a pre-tested structured questionnaire from April to August 2005 to collect information on expenditure inputs such as feeds and supplements; drugs and vaccines; replacement stock and breeding services for the grade dairy sub-system. From the crops sub-system, information was collected on expenditure on inputs such as seed, fertilizer, land preparation, tea production and manure. Similarly, information on output values from both the grade dairy and crop sub-systems was also captured separately. The data were entered into MS EXCEL spreadsheet and gross margins for two sub-systems calculated directly by subtracting total expenditure on inputs from total output value.

Expenditure on inputs and output value expressed in KES for the grade dairy cattle sub system were calculated per cow per year and per household per year for the crops sub system (Phung  and Koops 2003). Descriptive statistics and ANOVA were determined from the General Linear Model procedure (Angela  and Daniel 1999) from the SPSS package (Version 10.0) based on the model:

Υjkl = µ + Pj +Bk + ℮jkl

Where:

Y = parameters under test (Expenditure on inputs such as feeds, drugs and vaccines, replacement stock, breeding services, seed, manure, tea production, land preparation and output value such as milk, manure, breeding stock, tea, maize, beans, horticulture etc from crops and grade dairy cattle sub systems)
µ = the underlying constant in each observation
Pj = effect of the grade dairy cattle production system (Grazing only - free grazing or tethered; Mainly grazing with some stall feeding; Mainly stall feeding with some grazing and Stall feeding only - zero grazing) on expenditure on inputs and output value for the two sub systems
Bk = Effect of the grade dairy cattle breed types (Holstein-Friesian pure, Holstein-Friesian cross, Ayrshire pure, Ayrshire cross, Jersey cross, Guernsey pure and Guernsey cross) on expenditure on inputs and output value from the two sub systems
ejkl = error ND(0,δ2)


Results and discussion

Expenditure on inputs in the grade dairy cattle sub-system
Feeds

Expenditure incurred on feeds such as dairy meal, napier grass and minerals largely depended (P<0.05) on the grade dairy cattle production system and less (P>0.05) on the breed type (Table 1).


Table 1.  Influence of grade dairy cattle production systems and breed types on expenditure on inputs and output value per cow per year from the grade dairy cattle sub system in Vihiga

Parameter

EMS, 000

Production systems

Breed type

MS, 000

F value

MS, 000

F value

Expenditure on grade dairy cattle inputs/cow/year

Dairy meal

6718

3194

4.76*

40023

0.60

Hay/straw

300

27

0.10

1

0.004

Minerals

124

460

3.71*

97

0.79

Napier grass

19899

93528

4.70*

153532

0.77

Molasses

29

14

0.47

19

0.64

Maize stover

131

262

1.10

62

0.47

Accaricide/dipping

161

473

2.93*

85

0.53

Vaccination

3

2

0.77

6

1.94

Drugs/antihelminthics

128

162

1.27

32

0.25

Heifers

39500

12500

0.03

85000

2.15

Cows

6525

4500

0.74

32358

5.28

AI

70

240

3.43*

16

0.24

Bull service

6

32

5.19*

6

0.96

Dairy labour

20436

114782

5.62*

21250

1.04

Total dairy expenditure

993268

407282

4.37*

42895

0.46

Grade dairy cattle output value/cow/year

Milk

170092

371001

2.18

216305

1.27

Heifers

35221

80392

2.28

70534

2.00

Female calves

5360

15759

2.94

7915

1.48

Young bulls

12971

30535

2.35

41939

3.23

Culls

59091

65491

1.11

22433

0.38

Manure

338

704

2.08

161

0.48

Total output value

492000

2098775

4.27*

201024

0.41

Gross margin

98432

107935

1.10

166110

1.69

* Means significantly different (P<0.05)


As indicated in Table 2, households that reared their grade dairy cattle under intensive production systems (Stall feeding only and Mainly stall feeding with some grazing) incurred significantly higher (P<0.05) expenditure per cow per year on dairy meal, minerals and napier grass, as opposed to those that reared them under extensive production systems (Mainly grazing with some stall feeding and Grazing only). There was slightly more expenditure on maize stover in extensive production systems than in intensive production systems (Table 2).


Table 2.   Means and standard errors of expenditure on inputs and output value (KES) for the grade dairy cattle sub system under the different grade dairy cattle production systems

Parameter

Grazing only

Mainly grazing + some stall feeding

Mainly stall feeding + some grazing

Stall feeding only

Expenditure/cow/year

Dairy meal

1691a 282

1917a 212

3552b 330

3525b 298

Hay/straw

-

-

-

583 159

Minerals

291a 36

375ab 50

523b 37

515b 44

Napier grass

2375a 537

2968a 480

4099ab 446

6415b 690

Molasses

-

-

233 51

322 64

Maize stover

1250b 50

876ab 84

687a 100

614a 68

Accaricide/dipping

434a 54

512ab 47

694b 42

693b 48

Vaccination

-

94 12

130 14

108 10

Drugs/antihelminthics

649  88

482 48

603 56

505 33

Heifers

-

-

13500 1500

16500 3284

Cows

-

12000

15100 2272

13667 4631

AI

455 94

418 61

540 65

420 34

Bull service

186 25

226 10

191 10

160 8

Dairy labour

5812a 818

8357ab 548

10874b 995

13200c 1420

Total dairy expenditure

8521a 1056

12013ab 2606

14549b 859

15170b 1286

Revenue (Output value)/cow/year

Milk

19659a 1447

23787ab 1271

29267b 2857

25259ab 1658

Heifers

-

8600 510

14360 2969

11636 2391

Female calves

-

4333  601

6300 943

6867 1435

Young bulls

11250 2750

-

8300 850

10777 1543

Culls

-

10500 3500

9083 1307

17300 2809

Manure

-

1086 97

1106 145

735 125

Total output value

21374a 1623

25964ab 1308

30392b 2499

27001ab 1731

Gross margin

11416 969

11832 1182

18379 978

12853 1562

Cash output-input ratio

2.5

2.2

2.0

1.9

* Means with different letters in a row were significantly different (P<0.05)


Expenditure on other feed stuffs like molasses, hay/straw and forage legumes was very minimal under all the four grade dairy cattle production systems. Grade dairy cattle owning households were confronted with consistent pressure on land and hence animal feeds, necessiting intensification of management systems through adoption of intensive production systems (Stall feeding only and Mainly stall feeding with some grazing) and greater use of purchased forages and supplements as similarly observed by Bebe (2003). Also consistent with observations by Zemmelink (1999), grade dairy cattle owning households because of smaller farms apparently gave priority to growing food crops and reduced the area of forage crops as well as cash crops, explaining higher expenditures on napier grass.

Veterinary services

Expenditure incurred per cow per year on tick control (accaricide/dipping) was dependent (P<0.05) on the grade dairy cattle production system (Table1). While expenditure incurred on vaccination and drugs/antihelminthics was least dependent (P>0.05) on the grade dairy cattle production system. Grade dairy cattle breed types had little influence (P>0.05) on all expenditures incurred on veterinary services (Table 1). As indicated in Table 2, households that reared their grade dairy cattle under Stall feeding only and Mainly stall feeding with some grazing production systems incurred slightly higher expenditure on accaricide/dipping (KES 693.1 and 693.9 respectively) as opposed to those that reared them under Grazing only and Mainly grazing with some stall feeding (KES 433.8 and 512.0 respectively). Farmers who reared their animals intensively attached more value to their stock resulting into more allocation of their resources to tick control. Expenditure on vaccination and drugs/antihelminthics was similar under the four production systems.

Breeding services

Expenditure incurred by grade dairy cattle owning households per cow per year on artificial insemination (AI) and bull service were least dependent (P>0.05) on grade dairy cattle production systems and breed types (Table 1). Use of Artificial insemination (AI) in Vihiga was, however, low as prices paid for AI services depended on the sire selected and transport costs incurred by the provider for each insemination (regardless of repeats), and in most cases were not affordable to the average small scale dairy farmer. On the contrary, bull services due to lower costs for each successful service were affordable to most small scale dairy farmers hence widely used for breeding in the area (Table 2).

Labour

Expenditure incurred by grade dairy cattle owning households on hired labour for dairying activities per cow per year was dependent (P<0.05) on the production system and less (P>0.05) on the breed type (Table 1). Farmers who intensively managed their grade dairy cattle (Stall feeding only and Mainly stall feeding with some grazing) incurred higher expenditure on hired labour for dairying activities (KES 13,200.0 and 10,873.6 respectively) as indicated in Table 2. Low expenditure on labour for dairying activities was incurred in Grazing only production system (KES 5812.5). This finding was supported by Waithaka et al (2002) and Staal et al (2001) that for the intensified stall feeding systems (Zero grazing and Mainly stall feeding with some grazing), labour (hired and/or casual) was necessary to carry out 'cut and carry' feeding activities (labour intensive), while in the extensive systems where animals are mainly grazed is required for herding. Hired labour for dairying activities on these farms was used partly on cropping activities.

Breeding stock

Both the grade dairy cattle production systems and breed types had little influence (P>0.05) on expenditure incurred by grade dairy cattle owning households for purchasing the breeding stock (calves, heifers, cows and bulls) as indicated in Table 1. This implied that acquisition of breeding stock was not based on knowledge of appropriate breed types, production or management systems. However, as indicated in Table 2, more heifers and cows were purchased in the intensive production systems (Stall feeding only and Mainly stall feeding with some grazing). As Bebe (2003) reports, high reproductive wastage and high turnover of females under intensive systems is such that they are unable to maintain a sufficient number of heifers for replacing cows leaving the herd without external supply of replacement. Hence farmers practicing intensive systems purchase more replacement animals than those practicing extensive systems.

Output value from the grade dairy cattle sub system

Grade dairy cattle breed types had little influence (P>0.05) on the output value from the grade dairy cattle sub system (Table 1). However, total output value per cow per year (KES) to grade dairy cattle owning households from grade dairy cattle in general and from milk were significantly influenced (P<0.05) by the production system. Output value was higher in the intensive production systems (Stall feeding only and Mainly stall feeding with some grazing) unlike in the extensive production systems (Grazing only and Mainly grazing with some grazing). As indicated in Table 2, output value from grade dairy cattle in general and from milk in Mainly stall feeding with some grazing production system was KES 30392.0 and 29267.0 respectively, while in Grazing only production system was KES 21374.1 and 19658.7 respectively.

Grade dairy cattle off-take (heifers, female calves, young bulls and culls) and sale of manure depended less (P>0.05) on both the grade dairy production system and breed type (Table 1). Gross margin from the grade dairy cattle sub system was least influenced (P>0.05) by both the grade dairy cattle production system and breed types (Table 1). The cash output - input ratios in the four grade dairy cattle production systems were above 1.9 (Table 2), implying that irrespective of the grade dairy cattle production system, grade dairy cattle owning households received about KES 2 for every KES 1 invested in the grade dairy cattle sub system. These positive returns from the grade dairy cattle sub system suggested a solid base for profitable grade dairy cattle production by mixed small scale farmers under the different grade dairy cattle production systems.

Expenditure on inputs in the crops sub-system

Grade dairy cattle production systems and breed types had little influence (P>0.05) on expenditure incurred by grade dairy cattle owning households on inputs for crop production (Table 3).


Table 3.  Influence of grade dairy cattle production systems and breed types on expenditure on inputs and output value per household per year from the crops sub system in Vihiga

Parameter

EMS (000)

Production systems

Breed type

MS, 000

F value

MS, 000

F value

Expenditure on crops inputs/household/year

Maize seed

531

520

0.98

288

0.54

Bean seed

214

151

0.71

198

0.93

DAP fertilizer

491

523

1.07

621

1.26

CAN fertilizer

541

437

0.81

353

0.65

Manure

205

3646

17.79*

106

0.52

Land preparation

1583

378

0.24

1631

1.03

Tea production inputs

6368

15392

2.42

5273

0.83

Total crops expenditure

21282

64769

3.04*

3652

0.17

Crops output value/household/year

Tea income

67315

369125

5.48*

63132

0.94

Horticultural crops

4678

2095

0.45

5637

1.21

Maize

45339

448379

0.99

53263

1.18

Beans

6034

701

0.12

7263

1.20

Vegetables

588

1002

1.71

1089

1.85

Total crops output value

136918

284364

2.08

95218

0.70

Gross margin

73396

138789

1.89

71365

0.97

* Means significantly different (P<0.05)


Expenditure on inputs into tea production (labour and fertilizer), though least influenced by the grade dairy cattle production system, was slightly higher in the intensive production systems than in the extensive production systems (Table 4). This is because in intensive systems, there was more output value from the grade dairy cattle sub system resulting into more surplus cash to be injected into tea production, similar to findings by Salasya (2005). Expenditure on inputs for other crops production under the different grade dairy cattle production systems was similar (P>0.05).


Table 4.  Means and standard errors of expenditure on inputs and output value (KES) for the crops sub system under the different grade dairy cattle production systems

Parameter

Grazing only

Mainly grazing + some stall feeding

Mainly stall feeding + some grazing

Stall feeding only

Expenditure/household/year

Maize seed

960 91

1270 139

982 88

1025 81

Bean seed

660 87

729 102

713 59

812 93

DAP fertilizer

1141 204

1180 117

987 80

1245 92

CAN fertilizer

1170 93

1115 145

1014 101

1336 132

Manure

1112a 143

1545a 126

1120a 91

2168b 110

Land preparation

1871 280

1853 221

1729 155

1868 147

Tea production inputs

4000 1091

5417 450

4500 398

6378 526

Total crops expenditure

8121 179

8505 753

5718 420

7359 567

Revenue (Output value)/household/year

Tea income

12392a 2549

15157a 1336

17134ab 1301

23521b 1774

Horticultural crops

2889 250

3707 618

3073 513

2497 308

Maize

8812 1421

5393 912

7044 740

7836 979

Beans

3150 429

3097 424

3123 355

2943 347

Vegetables

1800

1349 201

1249 136

1591 149

Total crops output value

17123 843

16781 1622

13613 1016

17892 1512

Gross margin

9002 858

8276 1067

7895 782

10533 1110

Cash output-input ratio

2.1

2.0

2.4

2.4

* Means with different letters in a row were significantly different (P<0.05)


Output value from the crops sub system

Grade dairy cattle production systems significantly influenced (P<0.05) the output value from tea and less (P>0.05) the other crops (Table 3). Revenue from tea in the Stall feeding only production system was KES 23521.3, while in Grazing only production system was KES 12392.0 (Table 4). Grade dairy cattle breed types had little influence (P>0.05) on the output value from the crops sub system (Table 3). Total output value and gross margin from the crops sub system depended less (P>0.05) on grade dairy cattle production systems. Tea provided more revenue within the crops sub system for these grade dairy cattle owning households under the different grade dairy cattle production systems (Table 4). The cash output - input ratios for the crops sub system under the different grade dairy cattle production systems were similar but above 2.0, implying that grade dairy cattle owning households received KES 2 for every KES 1 invested in the crops sub system.


Conclusions


Acknowledgements

The first author was supported by a scholarship from KARI/IDA World Bank NARP II Project. The authors acknowledge the support of Director KARI; Chairman, Department of Animal Production - University of Nairobi and Centre Director, KARI-Kakamega for this study.


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Received 22 August; Accepted 4 October 2006; Published 6 December 2006

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