Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression

Massimo Cellesi,Jessica Serdino,Giustino Gaspa,Fabio Correddu,Corrado Dimauro,Nicolò Pietro Paolo Macciotta,Maria Grazia Manca

doi:10.3390/ani9090663

Massimo Cellesi, Jessica Serdino + Show 5 more

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https://doi.org/10.3390/ani9090663

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Abstract

Simple SummaryConsidered that all sheep milk in Italy is destined for cheese processing, traits describing rennet coagulation aptitude should be among the most important selection goals for dairy breeds. To reduce the costs and logistics related to the large-scale recording of these traits, mid-infrared (MIR) spectroscopy could be conveniently used to generate reliable predictions without any additional cost. The aims of this research were to predict the milk coagulation properties (MCP) and individual cheese yield (ILCY) in sheep by MIR spectrometry using partial least squares regression (PLS), and to compare different data pre-treatment procedures. The prediction results observed in the present study, although moderate, suggest the possibility of adding novel phenotypes (e.g., MCP and ILCY) in breeding schemes for dairy sheep breeds. Mid-infrared spectroscopy coupled with PLS regression could allow the prediction of phenotypes at the population level without additional costs.The objectives of this study were (i) the prediction of sheep milk coagulation properties (MCP) and individual laboratory cheese yield (ILCY) from mid-infrared (MIR) spectra by using partial least squares (PLS) regression, and (ii) the comparison of different data pre-treatments on prediction accuracy. Individual milk samples of 970 Sarda breed ewes were analyzed for rennet coagulation time (RCT), curd-firming time (k20), and curd firmness (a30) using the Formagraph instrument; ILCY was measured by micro-manufacturing assays. An Furier-transform Infrared (FTIR) milk-analyzer was used for the estimation of the milk gross composition and the recording of MIR spectrum. The dataset (n = 859, after the exclusion of 111 noncoagulating samples) was divided into two sub-datasets: the data of 700 ewes were used to estimate prediction model parameters, and the data of 159 ewes were used to validate the model. Four prediction scenarios were compared in the validation, differing for the use of whole or reduced MIR spectrum and the use of raw or corrected data (locally weighted scatterplot smoothing). PLS prediction statistics were moderate. The use of the reduced MIR spectrum yielded the best results for the considered traits, whereas the data correction improved the prediction ability only when the whole MIR spectrum was used. In conclusion, PLS achieves good accuracy of prediction, in particular for ILCY and RCT, and it may enable increasing the number of traits to be included in breeding programs for dairy sheep without additional costs and logistics.

Highlights

Sheep cheese (680,302 tonnes) represents about 3% of the total world cheese production [1].Mediterranean countries, where a large proportion of dairy sheep are farmed [2], produce about 45%of the world’s sheep cheese [3]
As far as milk coagulation properties (MCP) are concerned, the average rennet coagulation time (RCT) is similar to the values observed in the Sarda [30,31] and Spanish [32,33]
The average individual laboratory cheese yield (ILCY) is quite large: higher than values observed in Churra ewes [13], but quite similar to those reported in Merino ewes [35]

Summary

Introduction

Sheep cheese (680,302 tonnes) represents about 3% of the total world cheese production [1].Mediterranean countries, where a large proportion of dairy sheep are farmed [2], produce about 45%of the world’s sheep cheese [3]. Sheep cheese (680,302 tonnes) represents about 3% of the total world cheese production [1]. Mediterranean countries, where a large proportion of dairy sheep are farmed [2], produce about 45%. Is the fifth world producer in terms of quantity (7.5%), and it accounts for 36% of the world sheep cheese trade [4]. The Sarda breed, consisting of about 3.3 million heads, represents 60% of the Italian dairy sheep stock, and accounts for 80% of the total sheep milk produced in Italy [4]. All the milk is destined to cheese production with the manufacturing of three Protected Designation of Origin cheeses: Pecorino. The current breeding goals for the Sarda breed (220,268 ewes recorded in 2014) [6] are total lactation milk yield and scrapie resistance. Milk fat and protein contents are measured routinely only on first and second lactation ewes on a limited number of official tests

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