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:

Υ_jkl = µ + P_j +B_k + ℮_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
P_j = 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
B_k = 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
e_jkl = error ND(0,δ_℮²)

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
Parameter	EMS, ‘000	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	1691^a ± 282	1917^a ± 212	3552^b ± 330	3525^b ± 298
Hay/straw	-	-	-	583 ± 159
Minerals	291^a ± 36	375^ab ± 50	523^b ± 37	515^b ± 44
Napier grass	2375^a ± 537	2968^a ± 480	4099^ab ± 446	6415^b ± 690
Molasses	-	-	233 ± 51	322 ± 64
Maize stover	1250^b ± 50	876^ab ± 84	687^a ± 100	614^a ± 68
Accaricide/dipping	434^a ± 54	512^ab ± 47	694^b ± 42	693^b ± 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	5812^a ± 818	8357^ab ± 548	10874^b ± 995	13200^c ± 1420
Total dairy expenditure	8521^a ± 1056	12013^ab ± 2606	14549^b ± 859	15170^b ± 1286
Revenue (Output value)/cow/year
Milk	19659^a ± 1447	23787^ab ± 1271	29267^b ± 2857	25259^ab ± 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	21374^a ± 1623	25964^ab ± 1308	30392^b ± 2499	27001^ab ± 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
Parameter	EMS (‘000)	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	1112^a ± 143	1545^a ± 126	1120^a ± 91	2168^b ± 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	12392^a ± 2549	15157^a ± 1336	17134^ab ± 1301	23521^b ± 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

There was surplus of output value over expenditure on inputs for both the grade dairy cattle and crops sub systems, an indication that farmers were making profit across the different grade dairy cattle production systems in Vihiga.
In general, there was more surplus from the grade dairy cattle sub system than from the crops sub system across the different grade dairy cattle production systems.
The grade dairy cattle sub system contributed about 70% (KES 21937 per cow per year) to the incomes of the small scale mixed grade dairy cattle owning households and the crops sub system contributed 30% (KES 9204 per household per year), though the cash output-input ratios for the two sub systems were similar.

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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