A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms

Todde, Giuseppe; Murgia, Lelia; Caria, Maria; Pazzona, Antonio Luigi

doi:10.1016/j.egyr.2016.05.006

Cited by 45 publications

(27 citation statements)

References 11 publications

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“…It summarized the great number of variables existed in a sample of 963 of buffalo dairy farms. It partitioned them into three clusters to minimize the variance among farms of the same cluster and maximizing the variance among clusters (Todde et al, 2016). From the result, it is concluded that C1 incorporated 53% of the buffalo number kept under the sampled farms, while, the rest, 20% and 27%, were included in C2 and C3, respectively.…”

Section: Discussionmentioning

confidence: 99%

Classifying and Characterizing Buffalo Farming Systems in the Egyptian Nile Delta Using Cluster Analysis

Abdel-Salam

Fahim

2018

Journal of Animal and Poultry Production

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The objective of the study was to classify and characterize the buffalo farming systems in the Delta region of Egypt using multivariate statistical analysis approach. A survey was conducted on 963 buffalo holders to classify and characterize dairy buffalo farming systems in the region of Delta Egypt. Data of 9665 heads of buffalo were used. Two multivariate statistical techniques, the principal component analysis (PCA) followed by the cluster analysis (CA) were applied to all the variables of the survey. A three different buffalo groups resulted; cluster 1(C1) :included 34% of the farms keeping 5132 heads of buffaloes. Itis characterized by large average for both farmland area (4.9 feddan) and buffalo herd size(15.6 heads). Production and reproduction performance of buffaloes was the best (milk yield, 2608kg; lactation period,258 days; and number of services/conception, 1.5). Cluster 2 (C2): included 35% of farms with1905 heads of buffaloes. It included the smallest average farmland area (3.1 feddan) and the fewest average buffalo herd size (5.6 heads).Cluster 3 (C3): included 31%of farms which kept 2628 heads of buffaloes. It was marked with intermediate values of farmland area, buffalo herd size and productive and reproductive performance of buffaloes that filled between those of C1 and 2.In all clusters, buffaloes were traditionally managed; hand milked and naturally bred. After taking their needs, farmers sell surplus raw milk and dairy products through informal markets. Efficient or regular milk marketing channels were completely absent. Access of veterinary and extension services was not sufficient and inefficient.

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Section: Discussionmentioning

confidence: 99%

Classifying and Characterizing Buffalo Farming Systems in the Egyptian Nile Delta Using Cluster Analysis

Abdel-Salam

Fahim

2018

Journal of Animal and Poultry Production

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“…PCA has been used in Europe, Asia and Africa in the past to classify and differentiate types of smallholder farmers and also to define their development (Alvarez-Lopez et al, 2008;Rao et al, 2014;Robels et al, 2008;Todde et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Dynamics and adaptation of agricultural farming systems in the boost of cotton cropping in southern Mali

Dembele¹,

Bett²,

Mutai³

et al. 2017

Afr. J. Agric. Res.

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Integration of crop and livestock production systems constitutes an important engine for agricultural development and enhancement of smallholder farmers' livelihoods in the least developed countries. For the last forty years, the Malian cotton sub-sector has recorded mixed growth trends, having been initially successful before declining and then catching up. The growth dynamics in the cotton subsector has permitted smallholder farmers to endow and improve their living condition. The purpose of this study was to establish smallholder farmers' dynamics of integrating crop and livestock production systems as well as classification of the systems and their trajectories. The study was carried out in different agro-ecological zones in Southern Mali. A multistage sampling technique was used to select the area of study. Stratified random sampling technique was then used to select 134 smallholder farming households from three villages. A panel datasets was used from the Malian Company of Textile Development (CMDT) from 1961 to 2014 and 1974 to 2014. Based on explanatory structure variables, principal component analysis (PCA) and ascending hierarchical classification (AHC) were used to distinguish smallholder farmers' dynamics as well as classify them into different classes or groups. Five types of smallholder were distinguished. Type 1 was super large families representing 14% of the total smallholder farmers. Type 2 consists of large families, and constituted of 28% of the smallholder farmers. Type 3 consists of medium-sized families which represented 28% of the total smallholder farmers. Type 4 and type 5 were small and young families with 19 and 11% of smallholder farmers respectively. Notably, small family farming was low in Southern Mali, and so some agricultural options can be developed such as the milk and meat value chains among others.

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“…For these reasons, it is necessary that the dairy industry improves competitiveness by adopting innovative production processes and improving animal welfare. Improvement and miniaturization of sensors along with continuing costs reduction encourage the implementation of new technologies in dairy farms, allowing increases in their efficiency and productiveness [5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of automated in-line precision dairy farming technology implementation in three dairy farms in Italy

Caria

Todde

Pazzona

2019

Front. Agr. Sci. Eng.

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In recent decades, dairy farms have been exposed to wide variation in profit levels due to a considerable variability of milk price, and energy and feed costs. Consequently, it is necessary for the dairy industry to improve efficiency and productivity by adopting innovative technologies. The automated inparlour milk analysis and separation is mainly useful to produce low or high quality milk and to monitor the animal health status. Milk with high levels of protein and fat contents may reduce the intensity of standardization during cheesemaking process, reducing production costs. The study aimed to evaluate the efficiency of real-time milk separation during milking and the performance of the milking machine after implementation of AfiMilk MCS. In addition, the economic aspects were assessed. The separation of milk required the existing milking parlors to be equipped with an additional milkline to allow channeling milk with low and high coagulation properties into two different cooling tanks. The results showed that the high coagulation milk fraction, compared to the bulk milk, increased in fat (from 18% to 43%) and protein (from 3% to 7%) concentration. The technology tested has given promising results showing reliability and efficiency in milk separation in real time with affordable implementation costs.

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A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms

Cited by 45 publications

References 11 publications

Classifying and Characterizing Buffalo Farming Systems in the Egyptian Nile Delta Using Cluster Analysis

Classifying and Characterizing Buffalo Farming Systems in the Egyptian Nile Delta Using Cluster Analysis

Dynamics and adaptation of agricultural farming systems in the boost of cotton cropping in southern Mali

Evaluation of automated in-line precision dairy farming technology implementation in three dairy farms in Italy

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