الفهرس 
REVIEW OF LITERATUREOnly 14 pages are availabe for public view
Abstract
SUMMARY AND CONCLUSION
A cross sectional survey was conducted in two governorates namely El-Beheira and Qena. The survey covered 100 smallholders (50 farms for each aforementioned governorate) under mixed farming system (crop-livestock). Data was collected through semi-structured interviews with questionnaire including the following: herd size and herd structure, herd production (daily milk yield, total milk yield, milk yield in 150 days, lactation length and calving interval), cropping pattern (cropping area and crop production) over the year and animal feeding system in winter season (from Nov to May) and summer season (from Jun to Oct). The objectives of the study were to (1) characterize the mixed farming system (crop-livestock) by using the systems approach. (2) find out the optimum combination of inputs from farm forage and cash crops to minimize animal feeding costs and consequently increasing farm profitability.
Cluster analysis was used to classify the data by Two-Step Cluster procedure of SPSS software (SPSS, 2010). The software divided the data into 3 clusters named “El-Beheira”, “Qena” and “Mix” according to 14 input variables (governorate, the number of total animals, the number of total milking heads, the number of buffalo, the number of crossbred cows, the number of local cows, the total cultivated area, berseem area, wheat area, rice area, corn area, darawa area, alfalfa area and sugarcane area). The cluster quality was good (more than 0.5). The clusters that obtained by SPSS program were statistically analyzed by the least squares procedure of the general linear model (GLM) of SAS program (SAS, 2004).
Computational model (Bio-economical) was developed to illustrate the consequences of feed management on farm profitability in Egypt under mixed farming system (Crops-livestock). The model consists of four sub-models: the herd model, the nutrient requirement model according to NRC (2001), the cultivated area to achieve an optimum diet formulation model, and the whole farm profitability model. Consequently, the whole farm profitability model determined the best diet that covers the animal nutrient requirements with lowest cost. Different scenarios were generated based on multiple parameters such as the animal herd and the available crops in the farm. The model equations have to achieve farm objectives functions that reduce feeding cost and maximize farm profitability from livestock and cash crops.
The results obtained could be summarized as follows:
1. Mixed (crop-livestock) farming system characteristics by cluster analysis
The data was divided into 3 clusters (“El-Beheira”, “Qena”, and “Mix”) according to14 input variables. The cluster quality was good (more than 0.5).
1.1 Herd size and herd composition
Qena cluster recorded the highest significant (P<0.05) herd size (26 animals) as compared to El-Beheira cluster (13 animals). The difference average number in total milking heads was not significant between the two clusters. There were three types of dairy cows differentiated in El-Beheira and Qena clusters , buffalo (31% in El-Beheira and 35% in Qena ), crossbred cows (54 and 27% in El-Beheira and Qena , respectively) and local cow (15% in El-Beheira and 38% in Qena ). The average numbers of buffalo and local cows in Qena cluster were significantly (P<0.05) higher than El-Beheira cluster while, for crossbreds the difference was not significant in the aforementioned clusters.
The highest significant (P<0.05) number of milking heads of buffalo (2) and crossbred cows (3) was observed in El-Beheira cluster comparable to Qena cluster being 1 and 2 heads, respectively. On the other hand, Qena cluster has the highest significant number of local cow (2 heads) compared to El-Beheira cluster (1 head).
The average number of calves and heifers for buffalo and local cows were significantly (P<0.05) higher in Qena cluster than El-Beheira cluster. While, there was no statistically significant difference for the number of calves and heifers of crossbred cow between the two clusters.
1.2 Daily milk yield (DMY)
There were no significant differences between the two clusters (El-Beheira and Qena)regarding the average of daily milk yield for buffalo, crossbred and local cows.
1.3 Total milk yield (TMY)
The average of the total milk yield (TMY) per lactation for buffalo (1800 kg) and crossbred cows (2428 kg) were significantly (P<0.05) higher in El-Beheira cluster than that in Qena cluster.
1.4 Milk yield in 150 days (M150)
The highest significant (P<0.05) value of the average milk yield in 150 days for crossbred cows was observed in El-Beheira cluster (1571 kg/ head), and the low value for the aforementioned animal was detected in Qena cluster being 1395 kg /head.
1.5 Lactation length (LL)
El-Beheira cluster had the longest lactation period per buffalo and crossbred cows being 217 and 226 days, respectively, while those in Qena cluster had the shortest lactation period for the aforementioned animals being 195 and 199 days, respectively. All the previous differences were statistically significant (P<0.05).
1.6 Calving interval (CI)
Calving interval average (CI) for crossbred cows was significantly (P<0.05) longer in Qena cluster (14 months) than El-Beheira cluster (13 months). Nevertheless, there were no significant differences in calving interval for buffalo and local cows in the two clusters.
1.7 Cropping pattern
The total cultivated area was significantly (P<0.05) higher in Qena cluster than El-Beheira cluster. In winter, wheat and berseem represented the highest cultivation percentage 46 % and 42 %, respectively in El-Beheira cluster and the same trend was observed in Qena cluster. The average of Berseem cultivated area was significantly (P<0.05) higher in El-Beheira cluster (48 kirats) than Qena cluster (23 kirats). Bean and sugar beet were cultivated only in El-Beheira cluster and its percentages in the total cultivated area and all over the year were 7% and 4%, respectively.
In summer, corn and darawa were cultivated in the two clusters however, rice and cotton were cultivated only in El-Beheira cluster. Corn represented the main summer crop in the two studied clusters. Rice and cotton represented the second main summer crop only in El-Beheira cluster with a significant (P<0.05) difference. While in Qena cluster, darawa was the second main summer crop and it was significantly (P<0.05) higher than that in El-Beheira cluster. Corn scored the highest percentage in El-Beheira (36%) as compared to Qena (25%), while Darawa percentage was higher in Qena (8%) than El-Beheira (2%). Annual crops (sugarcane and alfalfa) appeared only in Qena cluster.
1.8 Animal feeding
The feeding system of the dairy animals in winter and summer seasons depends mainly on green forage. In winter, Berseem was the main green forage in the two clusters represented about 726 kg/day and 730 kg /day in El-Behiera and Qena clusters, respectively. In summer season, Darawa was the main green forage in El-Beheira (248 kg/day) and Qena (519 kg/day) clusters. Corn silage was the second main green forage in El-Beheira cluster (102 kg/day). Corn silage and hay were used with larger amount in El-Beheira cluster (128 kg/day) than Qena cluster (27 kg/day) as conserved diet. Corn stalk was used with lower amount in El-Beheira than Qena being 7 kg/day vs. 78 kg/day, respectively. Alfalfa was used as green forage during the two seasons and sugar tops during the summer season only in Qena cluster. Straws were commonly used all over the year as roughage feed and almost in equal quantities in the two clusters. Concentrated feed amount in winter and summer seasons under Qena cluster (78 and 134 kg/day) was larger than El-Beheira cluster (41 and69 kg/day).
2. Scenarios
Four scenarios were proposed by the model for each cluster (El-Beheira and Qena): first Scenario calculated the actual feeding situation from the case study without any change as base run (B SI for El-Beheira and Q SI for Qena), second scenario (B SII for El-Beheira and Q SII for Qena) proposed to cover animal feeding requirements of the same herd in 1st scenario from the same available feed resources according to NRC (2001), third scenario (B SIII for El-Beheira and Q SIII for Qena) proposed to cover animal feeding requirements by replacing darawa with sorghum that multi cuts crop and richer than darawa in nutrients content and fourth scenario (B SIV for El-Beheira and Q SIV for Qena) operating on the available feeding package quantities or reallocated farm feed resources for the same herd. The common feed was used by the model in summer and winter seasons (300 days) while, two months were considered as transitional period between two seasons, where irregular animal feeding regime is adopted. This study showed that there were over feeding in feedstuffs quantity intake over the year in the study area, however there was a shortage in protein about 32% and 16% in El-Beheira and Qena case study in the summer season, respectively.
The results showed that Berseem cultivated area can be increased by 11% and 12% of total planted area in B SII and B SIII, respectively, compared to base run scenario for El-Beheira governorate (B SI). Also, the results showed that Berseem cultivated area could be increased by 45% and 41% of total planted area in Q SII and Q SIII, respectively, compared to Q SI as base run scenario for Qena governorate. Increasing Berseem cultivated area resulted in a pronounce increase in Berseem hay to be used in summer season to cover the animal feeding requirements of protein.
Using available feeding packages and reallocated farm resources in scenario IV reduced feeding costs in winter and summer seasons in El-Beheira by 52.7% and 4.2% and in Qena by 52.3% and 20.9%, respectively.
The highest gross margin was achieved by scenario IV followed by scenarios SIII and SII in both case study of El-Beheira and Qena.
CONCLUSION AND RECOMMENDATION
The present study has shown the impotence of using computational model (bio-economic model) as useful tool to assess the impact of using available feeding packages in increasing farm profitability. Farmers need to give more attention to use available feed resources efficiently to cover animals feeding according to their requirements. Some innovation packages are used in the studied area by some farmers.
It can be concluded that using available feeding packages or reallocating animal feeding resources can reduce feeding costs. Using of appropriate nutritional packages such as corn silage and berseem hay will reduce the shortage of feed. Scenario IV will achieve the highest increase in the farm profitability followed by scenario III and scenario II.
Some farms that have more cultivated area can increase berseem area in winter to cover animal protein requirement in summer feeding in form of hay. Cultivating new varieties of green forage that have more yield than traditional ones will help farmers to save areas to cultivate cash crops. A great attention should be given to increase the farmers’ awareness about the optimum nutrition of animals and the adequate use of the available feed resources. Ensuring the relation between farmers and researchers in research institutes is highly recommended. Systems approach studies dictate a vital role of farmers to ensure sustainability.
Further experimental studies are still needed to test this computational model under different production systems and to get more accurate estimates.