Evaluation of the contribution of 16 European beef production systems to food security

peer-reviewedContext Livestock production, and more particularly ruminants, is criticized for its low conversion efficiency of natural resources into edible food. Objective The objectives of this paper are to propose an evaluation of the contribution to food security of different European cattle farms through three criteria: 1) food production assessed by the amount of human-edible protein (HEP) and energy (HEE) produced at farm level, 2) feed-food competition at the beef production scale estimated in terms of net human-edible protein and energy and in terms of land used, and 3) food affordability assessed by the production cost of meat, protein and energy. Methods The analysis is based on 16 representative beef production systems in France, Belgium, Ireland, Italy and Germany and covers cow-calf systems, finishing systems, dairy and mixed dairy- finishing systems, with or without cash crops. Results and conclusions The results show that, at the farm level, systems producing both beef and milk or cereals have higher HEP and HEE production per hectare (up to 370 kg of HEP and 60,000 106J.ha−1) than specialized beef systems (up to 50 kg of HEP and 1600 106J.ha−1) and have lower production costs (approximately €6 kg−1 of HEP in mixed beef system and €29 kg−1 of HEP in a specialized cow-calf-fattener system). Beef systems are almost all HEE net consumers. Results are more variable concerning net HEP efficiency. The cow-calf enterprises are mostly net producers of HEP but, in order to produce human edible meat, these systems need to be combined with finishing systems that are mostly net consumers of HEP. In most cases, cow-calf-finishing systems are net consumers of HEP (between 0.6 and 0.7) but grass-based systems using very little concentrates or systems using co-products not edible by humans are net HEP producers. The grass-based systems use more land area per kilogram of carcass but a major part of this area is non-tilled land, thus these systems are not in direct competition with human food production. The lowest meat production costs are the finishing systems producing the most live weight per livestock unit (LU) per year and dairy systems in lowland which share the costs between milk and meat. Significance Although most of HEE and HEP efficient farms typically have higher meat production costs, some grassland based systems stand out positively for all indicators. These results pave the way for improvements of the contribution of beef production systems to food security. Graphical abstract Net Human Edible Protein and Energy Efficiencies of meat production (M_HEP_eff and M_HEE_eff)

Building consensus on water use assessment of livestock production systems and supply chains: outcome and recommendations from the FAO LEAP Partnership

The FAO Livestock Environmental Assessment and Performance (LEAP) Partnership organised a Technical Advisory Group (TAG) to develop reference guidelines on water footprinting for livestock production systems and supply chains. The mandate of the TAG was to i) provide recommendations to monitor the environmental performance of feed and livestock supply chains over time so that progress towards improvement targets can be measured, ii) be applicable for feed and water demand of small ruminants, poultry, large ruminants and pig supply chains, iii) build on, and go beyond, the existing FAO LEAP guidelines and iv) pursue alignment with relevant international standards, specifically ISO 14040 (2006)/ISO 14044 (2006), and ISO 14046 (2014). The recommended guidelines on livestock water use address both impact assessment (water scarcity footprint as defined by ISO 14046, 2014) and water productivity (water use efficiency). While most aspects of livestock water use assessment have been proposed or discussed independently elsewhere, the TAG reviewed and connected these concepts and information in relation with each other and made recommendations towards comprehensive assessment of water use in livestock production systems and supply chains. The approaches to assess the quantity of water used for livestock systems are addressed and the specific assessment methods for water productivity and water scarcity are recommended. Water productivity assessment is further advanced by its quantification and reporting with fractions of green and blue water consumed. This allows the assessment of the environmental performance related to water use of a livestock-related system by assessing potential environmental impacts of anthropogenic water consumption (only “blue water”); as well as the assessment of overall water productivity of the system (including “green” and “blue water” consumption). A consistent combination of water productivity and water scarcity footprint metrics provides a complete picture both in terms of potential productivity improvements of the water consumption as well as minimizing potential environmental impacts related to water scarcity. This process resulted for the first time in an international consensus on water use assessment, including both the life-cycle assessment community with the water scarcity footprint and the water management community with water productivity metrics. Despite the main focus on feed and livestock production systems, the outcomes of this LEAP TAG are also applicable to many other agriculture sector

A biometric-based system for unsupervised anomaly behaviour detection at the pawn shop

This article shows a system performing re-identification and description of people entering different stores of the same franchise by means of Face Recognition, Gait Analysis, and Soft Biometrics techniques. Additionally, an anomaly detection analysis is conducted to identify suspicious behavioral patterns.It has been tested on an ad-hoc dataset of a set of pawn shops of a local franchise.The registered users paths have been human labelled as ‘normal’ or ‘abnormal’ achieving a precision of 100%, recall of 72.72%, and an average accuracy of 96.39%.The system is able to report anomalies to support decisions in a context of a security monitoring system

Robotic milking and milk quality: effects on the cheese-making properties of milk

Robotic milking systems (RMS) modify dairy herd management and therefore some aspects of production. The mainresults from scientific literature on RMS and cheese-making properties have been reported. The decrease in fat content,as a consequence of the increased milking frequency, is generally confirmed. The lack of specific studies on creamingproperties of milk from robotic milking experiences and with different milking frequencies has been highlighted.Indications on clotting features were obtained with a different milking frequency in a traditional milking parlour; theseresults showed an improvement in the casein index of milk from three daily milkings. A reduction of casein exposure tothe plasminogen-plasmin complex activity in the mammary gland between two consecutive milkings seems to explainthis result. The effect of RMS on milk quality for cheese-making purposes was first evaluated in a two-year monitoringstudy in a herd representative of Po Valley dairy farms. Preliminary results from laboratory tests on bulk milk samplesindicate that milk from RMS seems suitable for cheese-making processes

Automation in dairy cattle milking: experimental results and considerations

The results of two experimental programs financed to the Istituto Sperimentale per la Zootecnia are presented. The objective of the two Italian programs was the verify if automatic milking is a suitable practice for Italian dairy system. Results are summarised and compared to those obtained in other international projects. Results refer to animal behaviour, milk yield, milk quality an animal welfare. In a trial comparing cows milked with an automatic milking system and cows milked in a milking parlour, we observed that when the temperature and humidity are very high cows reduce their activity, have lower milking frequency and milk yield than in cold seasons. In comparison to milking parlour, automatic milking system did not increase milk yield which was affected significantly by season, stage of lactation, parity, season per treatment and parity per treatment. The causes of the negative results obtained by this group and by other international groups are discussed. We also presented the results obtained in four trials thereby four appetizers or flavourings were tested to improve efficiency of automatic milking system. Comparing the two milking systems, automatic milking determined a worsening of milk quality, but from these data is not possible to exclude the possibility to use automatic milking for Grana Padano and Parmigiano Reggiano-type cheeses. Animal welfare is not negatively influenced by automatic milking system, which has the potentiality to improve the control and care of cows

A comparative study of shallow learning and deep transfer learning techniques for accurate fingerprints vitality detection

This work inspects deep learning architectures and shallow learning techniques to determine whether the image of a fingerprint is real (Live) or not (Fake). It is known that Deep Learning techniques deliver, in general, good accuracies being able to automatically extract relevant patterns, at the same time, it is also known that these algorithms require large amounts of data. For this reason, transfer learning aims to transfer the knowledge learnt over a huge dataset to a new, smaller dataset. In this work, because of the limited size of the LivDet2019 dataset, three well known deep learning architectures such as Inception V3, ResNet50 and NASNet Large have been modified to perform transfer learning from the huge imagenet dataset to the smaller LivDet2019. The hypothesis at the very basis of this work is that the deep learning architectures trained on the huge imagenet dataset would learn to extract relevant patterns like lines, shapes, curves, jump between curves, etc... Later, the extracted knowledge, is fine-tuned on the LivDet2019 dataset to recognize fingerprint minuities as a non-linear combination of the previously learned patterns. For sake of completeness, state of art shallow learning image descriptors, finetuned for fingerprint recognition, such as Binarized Statistical Image Features (BSIF), Local Phase Quantization (LPQ) and Weber Local Descriptor (WLD) are used for extracting features from the LivDet2019 dataset. The classification on each of these extracted features is performed both with a linear and non-linear (gaussian) support vector machine. Accuracies suggest that both shallow learning and deep learning techniques are on par with the accuracies of reviewed works and thus transfer learning in fingerprint liveness detection is a feasible strategy that deserve attention and future research with the aim of increasing fingerprint detection accuracies

Effect of average daily gain on body size, metabolism, and milk production of Italian Holstein heifers raised on two different planes of nutrition and calving at two different ages

The aim of the present experiment was to verify if average daily gain (ADG) can affect body growth and development, fat deposition, metabolic profile and, by interacting with age at first calving (AFC), also milk production in first lactation. A total of 141 Italian Friesian heifers, in two experimental herds, were allotted to 2 feeding regimens formulated for a moderate (M, 0.7 kg/d) or an accelerated (H, 0.9 kg/d) ADG diet from 5 to 15 mo of age. Half of the heifers on M were programmed to be bred at 15 mo (ME), and half at 18 mo (ML) of age; heifers on H were programmed to be bred at 15 mo of age (HE). Every 28 d, body weight (BW), wither height (WH), hip height (HH), body length (BL), and hearth girth (HG) were measured; in those moments and each week from \u201314 to 70 d after calving (only in one herd), the body condition score was evaluated. In one herd only, metabolic profile was assessed at 9 and 15 mo of age. Growth curve parameters were estimated for BW, HH, BL, and HG for each heifer. Metabolic profiles from both ages (9 and 15 mo) were processed by Principal Components Analysis. At first calving, milk production and composition were recorded. The BW of M heifers grew slower (0.74 vs. 0.83 kg/d) than H heifers, and this difference was reflected also in a faster HG gain in H than M heifers (0.176 vs 0.165 cm/d). The BCS of heifers fed on H diet grew faster than that of heifers fed on M diet by 9 mo of age. At this age, plasma concentration of urea, Ca, Na, albumin, and \uf067-glutamyl transferase activity were greater in H than in M heifers. At 15 mo of age, plasma concentration of bilirubin and alkaline phosphatase activity were lower in H heifers than M heifers. At 9 mo, plasma urea concentration was correlated with HH and HG curve parameters. At 15 mo, plasma glucose concentration was correlated with BW curve parameters. Plasma ceruloplasmin concentration was correlated with HH curve parameters at both ages, and with BW curve parameters at 15 mo. The main results from the PCA on metabolic profile in the growing heifers have shown that PC1 was mainly composed of total protein, albumin, Na, Cp, glucose, Ca, and globulin. This component was correlated with the parameters of the growth functions for BW, HH, and HG. Experimental diet and AFC per se did not affect milk production in first lactation, but there was a difference of about 15 d among groups for what concerns the time at which the peak milk production occurred

Effects of automatic milking system on some plasma parameters related to oxidative status in primiparous dairy cows.

Due gruppi di bovine primipare sono stati confrontati nei primi 154 giorni di lattazione, per valutare gli effetti del differente sistema di mungitura (sala tradizionale vs. sistema automatico) sui parametri dello stato ossidativo nel plasma. Le analisi sul plasma hanno riguardato: metaboliti reattivi dell\u2019ossigeno (ROMs); gruppi tiolici totali (SHp); proteine totali; albumine; ceruloplasmina. Non vi sono state differenze significative nello stato ossidativo delle bovine in funzione del sistema di mungitura adottato. Sia ROMs che SHp hanno manifestato differenze significative in funzione della settimana di lattazione considerata, con una significativa tendenza all\u2019aumento per SHp nel passaggio da 7 a 154 giorni di lattazione. Anche il rapporto SHp:albumine \ue8 aumentato con il procedere della lattazione nel periodo considerato. Il livello plasmatico della ceruloplasmina \ue8 risultato positivamente correlato al livello di ROMs (r=0,498; P<0,001)

Relationship between growth and metabolic parameters of Holstein heifers fed different nutritional regime

In two experimental herds 141 replacement heifers were reared with the aim of investigating the relationships between growth from 5 to 18 mo of age and metabolic parameters. The heifers of both herds were fed on a moderate ADG (MADG: 0.7 kg/d) or on an accelerated ADG (AADG: 0.9 kg/d) diet. Heifers\u2019 BW, BCS, wither height (WH), hip height (HH), body length (BL), and hearth girth (HG) were recorded every 28 days. At 9 and 15 mo of age a blood sample was drawn for analysing metabolic profile. Data from body measurements were processed by analysis of variance and growth curve analysis, using Laird\u2019s form of Gompertz curve. Metabolic profiles were processed by Principal Components Analysis (PCA), followed by Pearson\u2019s correlation analysis between growth curve coefficients and PCs. The AADG heifers had greater actual ADG (0.83 vs 0.74 kg, P<0.001) and greater daily increase of HG (1.76 vs 1.65 mm, P<0.005) than MADG heifers. From 9 to 18 mo of age, BCS of AADG heifers diet was greater than BCS of MADG heifers (P<0.05). From the comparison of growth curve parameters between ADG groups, only the initial growth rate of HG was affected by diet, and no effect was found on maturation rate. The PCA showed a PC1 mainly composed of total protein and albumin (9 and 15 mo), Na and ceruplasmin (9 mo), glucose and Ca (15 mo). This component was positively correlated (P<0.05) with the maturation rate of the growth functions for BW, WH, HH, and HG