Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-22T19:17:57.390Z Has data issue: false hasContentIssue false

Effect of low and high concentrate supplementation on health and welfare indicators in different breeds in small-scale mountain dairy farms

Published online by Cambridge University Press:  09 June 2021

Laura Flach
Affiliation:
Faculty of Science and Technology, Universitätsplatz 5, 39100 Bolzano, Italy
Sarah Kühl
Affiliation:
Faculty of Science and Technology, Universitätsplatz 5, 39100 Bolzano, Italy
Christian Lambertz
Affiliation:
Faculty of Science and Technology, Universitätsplatz 5, 39100 Bolzano, Italy
Erica DeMonte
Affiliation:
Faculty of Science and Technology, Universitätsplatz 5, 39100 Bolzano, Italy
Matthias Gauly*
Affiliation:
Faculty of Science and Technology, Universitätsplatz 5, 39100 Bolzano, Italy
*
Author for correspondence: Matthias Gauly, Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

We investigated and compared the effects of low and high concentrate supplementation in terms of animal welfare, health and reproductive performance in two different dairy cow breeds on small-scale mountain farms. 64 South Tyrolean dairy farms were evaluated using an on-farm assessment for animal-based and resource-based welfare indicators, data from test day records, and a questionnaire for the farmer. Farms were divided into four groups: low input Tyrolean Grey (L-TG), low input Brown Swiss (L-BS), high input Tyrolean Grey (H-TG) and high input Brown Swiss (H-BS). Effects of intensity level, breed and their interaction were calculated and analyzed statistically. The predominant husbandry system across all groups was tie-stall. The average energy-corrected milk yield increased with increasing concentrate level, with L-TG showing the lowest and H-BS showing the highest milk yield. Age at first calving was lowest in H-BS when compared to all other systems, while numbers of lactations were higher in L-TG compared to H-BS. Feed efficiency (percentage of milk out of roughage) was significantly higher in L-TG and L-BS when compared to H-TG and H-BS. L-BS showed the poorest results for most of the welfare indicators such as lean cows, lesions and percentage of dirty animals. In conclusion, a higher concentrate level in diets does not lead automatically to lower animal welfare for dairy cows in alpine regions. Indeed, keeping high yielding breeds in extensive systems seems to be challenging. The dual-purpose breed TG showed some clear advantages in that calving interval was lower and the number of lactations greater.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation

In recent years, livestock production is being increasingly criticized and consumers demand more animal welfare-friendly systems (Cardoso et al., Reference Cardoso, Hötzel, Weary, Robbins and von Keyserlingk2016). Broom (Reference Broom1996) defined animal welfare as the success of an individual in coping with its environment. According to the Farm Animal Welfare Council (1979), the welfare of an animal should always be considered in the light of the ‘Five Freedoms’, namely freedom from hunger and thirst, freedom from discomfort, freedom from pain, injury and disease, freedom to express normal behavior and freedom from anxiety and stress. Consumers often associate extensive, small-scale, and pasture-based farming systems with benefits when compared to intensive, large-scale dairy production (Fearne and Lavelle, Reference Fearne and Lavelle1996; Weinrich et al., Reference Weinrich, Kühl, Zühlsdorf and Spiller2014). In mountain areas, small-scale dairy farms are still in the majority. South Tyrol (Northern Italy) can be considered as an example for a mountainous region with a traditional dairy production characterized by part-time farmers, small herd sizes and tie stalls (Südtiroler Sennereiverband, 2017). Even though the milk price is higher than in most other European regions (Autonome Provinz Bozen-Südtirol, 2017), farmers here and in other mountain regions face very high expenses for machines and concentrates (Tasser et al., Reference Tasser, Schermer, Siegl and Tappeiner2012) as well as high labor costs (Poulopoulou et al., Reference Poulopoulou, Nock, Steinmayer, Lambertz and Gauly2018). Thus, the economic situation is the main challenge for traditional, small-scale farms (MacDonald et al., Reference MacDonald, McBride, O'Donoghue, Nehring, Sandretto and Mosheim2007). Changing production conditions, especially the selection of high-yielding dairy breeds during the past decades (Autonome Provinz Bozen-Südtirol, 2017) may already indicate that farmers try to compensate their high expenses with an intensification of milk production. Intensification in dairy systems is complex and mainly associated with higher milk yields, as well as changes in farm size and stocking density (Clay et al., Reference Clay, Garnett and Lorimer2020). However, in mountain areas, the opportunity to change farm size and stocking density are very limited and thus increasing the total amount of milk production per cow and farm is usually only possible by using higher-yielding breeds or increasing concentrate levels.

Some authors already reported an impact of concentrate supplementation on health and welfare. The prevalence and severity of lameness was higher in dairy cows fed with high compared with low amounts of concentrate (11 v. 7 kg/cow/d: Manson and Leaver, Reference Manson and Leaver1988). Other studies did not find an impact on fertility traits (Horan et al., Reference Horan, Mee, Rath, O'Connor and Dillon2004; Delaby et al., Reference Delaby, Faverdin, Michel, Disenhaus and Peyraud2009; Horn et al., Reference Horn, Steinwidder, Pfister, Gasteiner, Vestergaard, Larsen and Zollitsch2014). Spiekers et al. (Reference Spiekers, Klünter, Potthast and Pfeffer1991) also did not observe an effect regarding the number of veterinary treatments, reproductive performance or culling. A further study (Leiber et al., Reference Leiber, Schenk, Maeschli, Ivemeyer, Zeitz, Moakes and Walkenhorst2017) monitored different groups of organic dairy farms, which reduced the amount of concentrate to a certain level (between 0 and 1.14 kg concentrate/cow/d), over a six-year period. Although milk yield decreased during the experiment in all groups that reduced the amount of concentrate fed, this was not significant. Furthermore, milk protein, somatic cell count, fat protein ratio, average number of lactations, calving intervals and frequency of veterinarian treatments did not differ by group and year (Leiber et al., Reference Leiber, Schenk, Maeschli, Ivemeyer, Zeitz, Moakes and Walkenhorst2017). However, the use of large amounts of concentrates can have a negative impact on animal welfare, especially due to the associated intensification of milk production (Koeck et al., Reference Koeck, Loker, Miglior, Kelton, Jamrozik and Schenkel2014). At the same time, it can be problematic to meet the energy requirements of high-yielding animals when feeding a grass-based diet (Charlton et al., Reference Charlton, Rutter, East and Sinclair2011).

To our knowledge, the combination of the level of concentrate feed and the used breed is rarely considered when studying the welfare of dairy cows. Therefore, the objective of this study was to investigate the influence of high v. low concentrate feeding as well as the influence of breed (lower yielding Tyrolean Grey v. higher yielding Brown Swiss) and their interactions on animal- and resource-based welfare indicators as well as health and reproduction parameters.

Materials and methods

Study area and farms

The study region South Tyrol, with a total area of 7400.43 km2, is situated in the very northern part of Italy. The province is dominated by a continental climate and, because of its inner-alpine location, little precipitation with on average 667 mm yearly in the capital Bolzano. However, the climatic conditions widely vary between valley and mountainous areas (Adler, Reference Adler2015). Only 14% of its land area is below an altitude of 1000 m above sea level (a.s.l.), 49% between 1000 and 2000 m a.s.l. and 37% above 2000 m a.s.l. (Autonome Provinz Bozen-Südtirol, 2017).

In this study, 64 small-scale dairy farms were included. These farms were selected through the Dairy Association of South Tyrol and breeder's associations. The selection criteria was a farm location above 700 m a.s.l and a herd size of 7–20 dairy cows of either the breed Tyrolean Grey (TG) or Brown Swiss (BS). The participation of the farms was voluntary.

Selected farms were classified based on the amount of concentrates fed and breed of cow into four groups: L-TG, ≤3.5 kg concentrate/day/cow Tyrolean Grey; L-BS: ≤4.5 kg concentrate/day/cow Brown Swiss; H-TG, ≥6.0 kg concentrate/day/cow and H-BS, 7.5 kg concentrate/fodder/day/cow. All farms used a dairy concentrate with contents of crude protein between 16 and 21%. In addition all cows received hay ad libitum.

Data collection

Data for resource and animal-based measurements were collected during farm visits, which took place during the winter housing period from October to May. The Welfare Quality Protocol is mainly addressed to large and intensive farms with loose housing barns (Welfare Quality®, 2009) thus, it was adjusted with recommendations by the European Food Safety Authority (EFSA). This protocol is provided for small-scale dairy farms characterized by local or dual-purpose breeds, less than 75 lactating dairy cows and family farms (EFSA, 2015), which was the case for all farms represented in this study.

Each farm was visited once by two assessors. One of them assessed the animal and resource-based measures and the second interviewed the farmer to collect data on management measures. Animal and resource-based measures were assessed in the barn by one observer using the combined protocol from Welfare Quality® and EFSA recommendations. During the interview, the farmer was asked to complete a questionnaire including questions about management practices (days on pasture, amount and type of concentrate supplementation) and business (full- or part-time, direct marketing or cooperatives, number of employees). Most of the questions were closed with a defined selection of response options. However, the questions about farm structures such as the size of farm areas, length of grazing period, the amount of the different feed components, and the type of concentrate feed were open to allow exact answers.

Assessment of animal-based measures

A total of 798 cows on 64 farms were assessed between October 2017 and May 2018 with each farm being visited once for this assessment and all cows being assessed whilst in the barn. On-farm assessment on one farm took between 3 and 4 h. An overview of the animal-based measures and the assessment method is given in online Supplementary Table S1.

Assessment of health and reproductive performance

Further information was gathered using the milk data from test day records for a three-year period from October 2014 to October 2017 and data from artificial insemination. Detailed information about the health and reproductive classifications and evaluations at farm level can be found in online Supplementary Table S2.

Assessment of resource-based measures

Resource-based measures were assessed between October 2017 and May 2018 during farm visits. Resource-based measures comprised type of husbandry system, number of water points, cleanliness and function of water points, dimensions of the lying area, cleanliness of the lying area, air quality and the presence of electric cow trainers (online Supplementary Table S3). Electric cow trainers typically consist of a metal rod placed a few centimeters above the cow's back. When a cow arches her back to defecate while standing in the front of the barn, she comes into contact with the electric cow trainer and receives an electric shock. This is to teach the animals to step backward before urinating and defecating to avoid such shocks and thus keep the stalls clean (Oltenacu et al., Reference Oltenacu, Hultgren and Algers1998). The use of electric cow trainers is limited to tie stalls.

In addition, hay samples from the first cut were collected on the farm. A bulk sample of approximately 4 kg was mixed on every farm, by collecting five individual samples. Proximate analysis was done according to Kirchgeßner (Reference Kirchgeßner2008). The amount of milk produced from roughage was calculated by using the formula (Weiß, Reference Weiß2001):

$$\left({\;\displaystyle{{{\rm 7\;MJ\;NEL}} \over {{\rm kg\;concentrate}}} \times \displaystyle{{{\rm concentrate\;in\;tons\;}} \over {{\rm cow\;and\;year}}}\;\times 100\;} \right)-\;\left({\displaystyle{{( {\rm 7\;MJ\;NEL/kg\;concentrate}) \;\times \;( {\rm concentrate\;in\;tons\;/cow\;and\;year}) \;} \over {3.2}}} \right)\;\times 100\;$$

Statistical analysis

Using SAS 9.4 (Statistical Analysis Systems, Cary, North Carolina, USA), the Kolmogorov-Smirnov test for normal distribution was applied, with values lower than 0.05 indicating abnormal distribution. For some of the variables, the log transformation was required to ensure homogeneity of variance. The fixed effects of either level of intensification (low- v. high-input) and breed (BS v. TG), as well as the interaction between the level of intensification and the breed were tested for animal and resource-based measures, and also for health and reproductive performance measures by applying the procedure PROC MIXED. The model used was;

$$Y_{ijk} = {\rm \mu} + a_i{\rm} + b_j{\rm} + a_i{\rm \ast }b_j{\rm} + f_k{\rm} + e_{ijk}$$

where Yijk is the dependent variable (welfare indicator), μ is the overall mean, ai is the fixed effect of the intensity level i (i = low-input; high-input), bj is the fixed effect of the breed j (j = Tyrolean Grey; Brown Swiss), ai*bj is the fixed effect of the interaction between intensity level and breed, fk is the random effect of the farm k (k = 1; 2; 3;….; 64) and eijk is the random error term. Effect of year for health and reproductive performance indicators was excluded from the final model, as it showed no significant influence. Data are expressed as means with standard deviation.

The overall significance was tested with an F-Test. When an overall significant effect of the assessment was detected, post hoc pairwise comparisons for the groups (L-TG, L-BS, H-TG, H-BS) were performed using the Bonferroni test. Frequency distributions were compared by Fisher's exact test. Significance was accepted for P values <0.05. Measures with zero prevalence were excluded. For the calculation of correlations between variables, the procedure proc corr was performed using the Pearson correlation test.

Results

Farm characteristics

Farm data are given in Table 1. All farms were managed as family businesses and sold their milk through cooperatives, and all were located at 1000-meter above sea level or greater. Except for the group L-BS, the majority of farmers worked exclusively on their farms without external employment. In this study, energy corrected milk (ECM)/cow and year increased with increasing concentrate level. The predominant husbandry system was tie-stall for all groups, even though 42% of the H-BS farms had a loose housing system. Days of pasture decreased with an increasing concentrate level with L-TG being highest to H-BS being lowest.

Table 1. Farm characteristics of the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use

Values are mean ± standard deviation. L is low concentrate allowance and H is high concentrate allowance, TG is Tyrolean Grey breed and BS is Brown Swiss breed.

a Meter above sea level.

b Energy corrected milk yield, adjusted to 3.5% fat and 3.2% protein.

Animal based measures

Results for animal-based measures showing a significant difference are given in Table 2, and the full dataset is in online Supplementary File S4. For the prevalence of lean cows, significant differences were observed, with a higher prevalence in the group L-BS than in L-TG and H-TG. Both fixed effects, breed and intensity level showed a significance.

Table 2. Animal based measures for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use, restricted to parameters exhibiting significant differences

Values are mean ± standard deviation. L is low concentrate allowance and H is high concentrate allowance, TG is Tyrolean Grey breed and BS is Brown Swiss breed.

a Cows with a BCS ≤2 were considered as too lean. Within a row, values that do not share a common superscript differ at P < 0.05.

The percentage of cows with dirty flank and/or upper leg, dirty hind leg as well as dirty udder was significantly higher in L-BS than in H-TG and H-BS. For all three parameters, a significance for the effect of intensity level could be observed, as well as for the effect of breed regarding the parameter dirty hind leg. Additionally, correlations between dirty flank/upper leg and dirty hind leg (P < 0.001, r = 0.73), dirty flank/upper leg and dirty udder (P < 0.001, r = 0.78) and dirty hind leg and dirty udder (P < 0.001, r = 0.63) were found. In terms of hairless patches, a significant difference was found between the groups of L-BS and H-TG, with a higher prevalence of hairless patches in L-BS. Additionally, a significance for the effect of the breed was found, with a lower percentage of cows with hairless patches for TG.

No significant differences between groups were observed for the percentage of animals with lesions, open shoulder, ocular discharge, vulvar discharge, nasal discharge, hampered respiration, diarrhea, incorrect lying down behavior or lame animals (online Supplementary Table S4).

Health and reproductive performance

Age at first calving was significantly lower in H-BS compared to all other groups (Table 3). Cows of the group L-BS had longer calving intervals compared to the other groups. The highest percentage of cows with a cell count ≥ 400 000 was found in the group L-BS, which differs significantly compared to H-TG. In both TG groups, the percentage of cows with a fat-protein-quotient <1 was significantly higher than in the BS groups. The number of lactations was found to be significantly higher in L-TG than in H-BS. Furthermore, there was a negative correlation between age of first calving and numbers of lactations (P < 0.001, r = −0.40). For dystocia, a significant effect of the intensity level was observed, with higher levels for both low-input compared to the high-input systems.

Table 3. Health and reproductive parameters for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use, restricted to parameters exhibiting significant differences

Within a row, values that do not share a common superscript differ at P < 0.05.

The full health and reproductive performance dataset is given in online Supplementary Table S5. No significant differences between groups could be observed for insemination index, lifetime production and animals with a milk urea >300 mg/l.

Resource-based measures

These data are shown in Table 4. No significant differences between the groups were found for dirty water points, length and width of lying area, the presence of an electric cow trainer or the energy content of hay. For forage performance, significantly higher amounts were observed for both low-input systems (48.6 and 43.3% for L-TG and L-BS, respectively) compared to high-input systems (26.9 and 29.8% for H-TG and H-BS, respectively).

Table 4. Resource based measures for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use

Values are mean ± standard deviation. L is low concentrate allowance and H is high concentrate allowance, TG is Tyrolean Grey breed and BS is Brown Swiss breed.

a Fisher's exact test.

Within a row, values that do not share a common superscript differ at P < 0.05.

Discussion

Farm characteristics

The comparison of the four farm groups showed that the groups differ for some management issues. The extensive farms were more frequently managed part-time and loose housing systems were found predominantly on farms using the high yielding breed BS and feeding higher amounts of concentrate. This is in line with results by Mattiello et al. (Reference Mattiello, Klotz, Baroli, Minero, Ferrante and Canali2009) who also state that tie-stalls are most common in alpine areas. Furthermore, the duration that cows were kept on pasture was lower for BS farms and those feeding higher amounts of concentrate. According to Zendri et al. (Reference Zendri, Ramanzin, Bittante and Sturaro2016), local breeds such as TG are more appropriate for alpine pastures and need less energy compared to high yielding breeds, which might be the reason why TG farms had a higher number of days on pasture. These differences are important confounding factors for the results regarding the cow's welfare, health and reproductive performance. Existing studies already reveal that the husbandry system (Regula et al., Reference Regula, Danuser, Spycher and Wechsler2004), as well as the number of days on pasture (Corazzin et al., Reference Corazzin, Piasentier, Dovier and Bovolenta2010), influence animal welfare and health issues.

Animal-based measures

The percentage of cows considered as too lean was higher than recorded in another study that focused mainly on a comparison of animal welfare parameters between tie-stalls (2.24%) and loose-housing (5.07%) (Ostojić-Andrić et al., Reference Ostojić-Andrić, Hristov, Novaković, Pantelić, Petrović, Zlatanović and Nikšić2011). Mattiello et al. (Reference Mattiello, Klotz, Baroli, Minero, Ferrante and Canali2009) shows very similar results to ours with 13.7% of lactating cows being classified as too lean. The high percentage of cows considered as too lean in the group L-BS might be due to the fact that the high yielding breed BS is not compatible with an extensive feeding system. This might also explain the significant results for both effects, breed and intensity level within the group comparison. Zollitsch et al. (Reference Zollitsch, Ferris, Sairanen and Steinwidder2016) states that high-yielding dairy cows have been selected under high-concentrate input conditions, while dual-purpose breeds, like TG, are more adapted to the harsh environment of mountain areas. Thus, for individual animals in the group L-BS freedom from hunger cannot be ensured.

For the cleanliness of animals, other studies already found explanatory variables: one of the most important among bedding material and husbandry techniques is the stall dimension (Chaplin et al., Reference Chaplin, Tierney, Stockwell, Logue and Kelly2000; Cook, Reference Cook2002; Hauge et al., Reference Hauge, Kielland, Ringdal, Skjerve and Nafstad2012). The fact that the length of the lying area is decisive for the cleanliness of cows indicates that stalls should be appropriate for the breed, which might be problematic for the breed BS in old tie-stalls and thus explain the high numbers of animals classified as dirty in this study.

Regarding the percentage of animals with hairless patches, Mattiello et al. (Reference Mattiello, Battini, Andreoli and Barbieri2011) reports a higher percentage than our findings for BS with 20.8% and a similar percentage to our findings for TG with 2.4%. However, we visited most of the farms during autumn when 60.3% of the farmers allow their dairy cows excess to pasture. A beneficial effect of pasture on reducing injuries due to the absence of constraining housing equipment and thus fewer collisions, is already reported by other studies (Corazzin et al., Reference Corazzin, Piasentier, Dovier and Bovolenta2010; Zuliani et al., Reference Zuliani, Romanzin, Corazzin, Salvador, Abrahantes and Bovolenta2017). The higher percentage of animals with hairless patches in the group L-BS might be explained by their large frame leading to more collisions with housing equipment than in smaller breeds like TG, when kept in tie-stalls. This is in accordance with Mattiello et al. (Reference Mattiello, Battini, Andreoli and Barbieri2011) and Katzenberger et al. (Reference Katzenberger, Rauch, Erhard, Reese and Gauly2020) who report that local breeds showed lesser animal welfare problems than high producing dairy cows when kept in alpine tie-stalls. However, the keeping of dairy cows in tie-stalls is very restrictive and the freedom to express normal behavior is, regardless of the kept breed, strongly limited.

Health and reproductive performance

Our finding that age at first calving is lowest in the H-BS group is in wide agreement with the finding that intensive farms with high-yielding breeds tend to have a lower age at first calving (Knaus, Reference Knaus2009). However, we found that the calving interval was highest for the group L-BS. The lower calving interval for TG is in agreement with the findings of Bieber et al. (Reference Bieber, Wallenbeck, Leiber, Fuerst-Waltl, Winckler, Gullstrand, Walczak and Spengler Neff2019) who report that local breeds have an up to 20 d shorter calving interval and a lower insemination index than high yielding breeds. it is almost inevitable that part-time farmers, who represented the majority in the L-BS group, would have spent less time in the stable and thus were more likely to miss the right time for artificial insemination which increases the calving interval. Another possible explanation is the fact that L-BS have the highest percentage of cows considered as too lean, which might indicate less energy and thus a poorer reproductive state of the herd, which is in accordance with several other studies (Pryce et al., Reference Pryce, Coffey, Brotherstone and Woolliams2002; Roche et al., Reference Roche, Macdonald, Burke, Lee and Berry2007).

The finding of increased numbers of high cell count cows in group L-BS correlates with the measures of dirty flank/upper leg, dirty hind leg and dirty udder which were also highest in this group. Several studies already report a high correlation between the cleanliness of cows and somatic cell count (Ward et al., Reference Ward, Hughes, Faull, Cripps, Sutherland and Sutherst2002; Ellis et al., Reference Ellis, Innocent, Mihm, Cripps, McLean, Howard and Grove-White2007; Sant'Anna and da Costa, Reference Sant'Anna and da Costa2011).

We found a higher percentage of cows with a fat:protein ratio (FPR) <1 for group TG. This should be interpreted with caution as typical values for this breed are around 3.76% fat and 3.39% protein in milk (Südtiroler Rinderzuchtverband, 2017). This, of course, leads to a smaller FPR compared to BS cows that have a fat content of around 4.15% and a protein content of around 3.56% (Brown Swiss breeding association of South Tyrol, 2017). However, there is no data available on the association between clinical acidosis and an FPR <1 in local breeds, therefore, it remains unclear if an FPR <1 is a valid indicator for risk of acidosis in TG. Another difference we found between the groups was the frequency of dystocia with a significant effect for the intensity level. An explanation might be that extensive farmers tended to use semen from other breeds (mostly Blue Belgian) more often in order to sell calves for meat production (36% v. 20%). Crossbreeding with beef breeds is known to be associated with increased risks of dystocia (Mee, Reference Mee1990; Fourichon et al., Reference Fourichon, Beaudeau, Bareille and Seegers2001).

In this study a longer productive livespan was found for the breed TG when compared to BS. This is in accordance with the findings of Bieber et al. (Reference Bieber, Wallenbeck, Leiber, Fuerst-Waltl, Winckler, Gullstrand, Walczak and Spengler Neff2019) and indicates that an increase in lactation performance is accompanied by a decreasing tendency of longevity, which was already stated by Essl (Reference Essl1982). These results might be partly explained by antagonistic genetic correlations between high yield and productive life (Pritchard et al., Reference Pritchard, Coffey, Mrode and Wall2013). However, this effect might be confounded with the intensity level of the system, as reported by Leiber et al. (Reference Leiber, Schenk, Maeschli, Ivemeyer, Zeitz, Moakes and Walkenhorst2017). Longevity is an important trait for low-input systems as a shorter productive life span means that rearing investments have to be paid off in a shorter period of time (Bergeå et al., Reference Bergeå, Roth, Emanuelson and Agenäs2016). Furthermore, Horn et al. (Reference Horn, Steinwidder, Pfister, Gasteiner, Vestergaard, Larsen and Zollitsch2014) found in organic dairy systems in Austria that cows reached their maximum annual milk yield in their fifth lactation.

Resource-based measures

The fact that no differences between groups were found for length and width of lying area implies that tie-stall dimension is not adapted to keep tall framed dairy cows like BS. Mattiello et al. (Reference Mattiello, Battini, Andreoli and Barbieri2011) found a mean stall length of 175 cm but significant differences in stall width with 113 cm for BS and 121 cm for TG. Further, they concluded that dairy cow's breed significantly affects welfare in tie-stalls (with high-yielding breeds showing poorer welfare than dual-purpose breeds) and this might in part be due to stall dimensions. Across all groups the presence of an electric cow trainer was common, although the negative effects of the use of an electric cow trainer are well known. These include risk of silent heat, clinical mastitis and culling (Oltenacu et al., Reference Oltenacu, Hultgren and Algers1998). While Zurbrigg et al. (Reference Zurbrigg, Kelton, Anderson and Millman2005) states that the presence of an electric cow trainer is associated with more animals considered as dirty, Bergsten and Pettersson (Reference Bergsten and Pettersson1992) report that cows housed in tie-stalls with electric cow trainers are cleaner. In line with the latter, in this study the group of H-TG had the most electric cow trainers and the least animals considered as dirty.

Further findings were that the collected hay samples showed low values for first-cut energy content (5.2 MJ/kg DM compared to >6.0 MJ/kg DM proposed by Resch et al., Reference Resch, Buchgraber, Pötsch, Wiedner, Tiefenthaler, Fasching and Meusburger2010). This might be a problem during lactation especially for high-yielding breeds. Poetsch (Reference Poetsch2007) recommends that low input systems have to improve their forage quality, if external resources like concentrates should be reduced. This was not, however, the case in this study, as no significant differences for the net energy could be observed between intensity levels. In addition, forage performance was higher for extensive farms but lower than it is recommended. In extensive systems, 80% of milk yield should be derived from forage feeding and in intensive feeding at least 50% (Kiefer et al., Reference Kiefer, Over and Bahrs2015).

The hypothesis that a high v. low concentrate supplementation has different effects on two dairy cow breeds in terms of animal welfare, health and reproductive performance can be confirmed for some indicators. Thus, BS cows showed poorer animal welfare, health and reproductive performance for some of the assessed indicators when fed with low amounts compared with BS cows fed with high amounts of concentrated feed. For TG no differences between the intensity levels could be observed. Since confounding factors (husbandry system, management practices) cannot be ruled out, further investigations are necessary.

Limitations of the study

The objective of this study was to assess cow welfare in low and high-input systems depending on the breed. However, the comparison between the groups shows some weaknesses due to the uneven distribution of some important management factors that might have an influence on animal welfare. In addition, only one observer measured the animal-based indicators on the farm. For some parameters, it is suspected that some resource-based variables other than the breed and feed-intake are more important. However, the results from the group comparison show that most of the animal-based measures indicate poorer animal welfare for the group L-BS and better animal welfare for the group H-TG. This suggests that high-yielding breeds might not fit into an extensive mountain system. Nevertheless, these results should be interpreted with caution because of the confounding factors just mentioned. Other studies also indicate that management practices and housing conditions have a decisive influence on animal welfare (Gieseke et al., Reference Gieseke, Lambertz and Gauly2018). Nevertheless, our results show that the breed should be adapted to the feeding and housing system, otherwise animal welfare might be compromised.

In conclusion, the results of the group comparison show that intensification through a higher concentrate level in diets does not lead to lower animal welfare for dairy cows in alpine regions. Rather, keeping high-yielding breeds in extensive systems seems to be challenging. This might not only be due to reduced labor effort in low input systems, but also because of the below average roughage quality in alpine regions, which makes it difficult to meet the energy requirements of high-yielding cows with a low concentrate supplementation. The dual-purpose breed TG showed some clear advantages in that calving interval was lower and the number of lactations greater.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0022029921000273.

Acknowledgement

The authors would like to thank the province of South Tyrol, which supported this study within the action plan Mountain Agriculture. Furthermore, the authors thank the Sennereiverband Südtirol for their support as well as all the farmers, who participated in this study

References

Adler, S (2015) Das Klima von Tirol-Südtirol-Belluno: Vergangenheit-Gegenwart-Zukunft. [The climate from Tirol-Südtirol-Belluno: past – present – future] Zentralanstalt für Meteorologie und GeodynamikGoogle Scholar
Autonome Provinz Bozen-Südtirol (2017) Agrar-und Forstbericht 2017 [Agricultural and Forestry Report 2017]. AthesiaGoogle Scholar
Bergeå, H, Roth, A, Emanuelson, U and Agenäs, S (2016) Farmer awareness of cow longevity and implications for decision-making at farm level. Acta Agriculturae Scandinavica, Section A—Animal Science 66, 2534.CrossRefGoogle Scholar
Bergsten, C and Pettersson, B (1992) The cleanliness of cows tied in stalls and the health of their hooves as influenced by the use of electric trainers. Preventive Veterinary Medicine 13, 229238.Google Scholar
Bieber, A, Wallenbeck, A, Leiber, F, Fuerst-Waltl, B, Winckler, C, Gullstrand, P, Walczak, J and Spengler Neff, A (2019) Production level, fertility, health traits, and longevity in local and commercial dairy breeds under organic production conditions in Austria, Switzerland, Poland, and Sweden. Journal of Dairy Science 102, 53305341.CrossRefGoogle ScholarPubMed
Broom, DM (1996) Animal welfare defined in terms of attempts to cope with the environment. Acta Agriculturae Scandinavica Section A-Animal Science 27, 2228.Google Scholar
Cardoso, CS, Hötzel, MJ, Weary, DM, Robbins, JA and von Keyserlingk, MA (2016) Imagining the ideal dairy farm. Journal of Dairy Science 99, 16631671.CrossRefGoogle ScholarPubMed
Chaplin, SJ, Tierney, G, Stockwell, C, Logue, DN and Kelly, M (2000) An evaluation of mattresses and mats in two dairy units. Applied Animal Behaviour Science 66, 263272.Google Scholar
Charlton, GL, Rutter, SM, East, M and Sinclair, LA (2011) Effects of providing total mixed rations indoors and on pasture on the behavior of lactating dairy cattle and their preference to be indoors or on pasture. Journal of Dairy Science 94, 38753884.Google ScholarPubMed
Clay, N, Garnett, T and Lorimer, J (2020) Dairy intensification: drivers, impacts and alternatives. Ambio 49, 3548.CrossRefGoogle ScholarPubMed
Cook, NB (2002) The influence of barn design on dairy cow hygiene, lameness and udder health. Proc. of the 35 th Ann. Conv. Amer. Assoc. Bov. Pract., Madison, WI. Amer. Assoc. Bov. Pract., Rome, GA, pp. 97103Google Scholar
Corazzin, ME, Piasentier, E, Dovier, S and Bovolenta, S (2010) Effect of summer grazing on welfare of dairy cows reared in mountain tie-stall barns. Italian Journal of Animal Science 9, 304312.Google Scholar
Delaby, L, Faverdin, P, Michel, G, Disenhaus, C and Peyraud, JL (2009) Effect of different feeding strategies on lactation performance of Holstein and Normande dairy cows. Animal: An International Journal of Animal Bioscience 3, 891905.Google ScholarPubMed
Ellis, KA, Innocent, GT, Mihm, M, Cripps, P, McLean, WG, Howard, CV and Grove-White, D (2007) Dairy cow cleanliness and milk quality on organic and conventional farms in the UK. Journal of Dairy Research 74, 302310.CrossRefGoogle ScholarPubMed
Essl, A (1982) Investigations on a breeding strategy for high lifetime production in dairy cows. First communication: basic considerations and results of model calculations. Züchtungskunde 54, 267275.Google Scholar
European Food Safety Authority (2015) Scientific opinion on the assessment of dairy cow welfare in small-scale farming systems. EFSA Journal 13, 4137.Google Scholar
Farm Animal Welfare Council (1979) Five Freedoms. First Press Notice., 5/12MAFF.69–478.Google Scholar
Fearne, A and Lavelle, D (1996) Perceptions of food “quality” and the power of marketing communication: results of consumer research on a branded-egg concept. Journal of Product & Brand Management 5, 2942.CrossRefGoogle Scholar
Fourichon, C, Beaudeau, F, Bareille, N and Seegers, H (2001) Incidence of health disorders in dairy farming systems in western France. Livestock Production Science 68, 157170.CrossRefGoogle Scholar
Gieseke, D, Lambertz, C and Gauly, M (2018) Relationship between herd size and measures of animal welfare on dairy cattle farms with freestall housing in Germany. Journal of Dairy Science 101, 73977411.CrossRefGoogle ScholarPubMed
Hauge, SJ, Kielland, C, Ringdal, G, Skjerve, E and Nafstad, O (2012) Factors associated with cattle cleanliness on Norwegian dairy farms. Journal of Dairy Science 95, 24852496.CrossRefGoogle ScholarPubMed
Horan, B, Mee, JF, Rath, M, O'Connor, P and Dillon, P (2004) The effect of strain of Holstein-Friesian cow and feeding system on reproductive performance in seasonal-calving milk production systems. Animal Science 79, 453467.CrossRefGoogle Scholar
Horn, M, Steinwidder, A, Pfister, R, Gasteiner, J, Vestergaard, M, Larsen, T and Zollitsch, W (2014) Do different cow types respond differently to a reduction of concentrate supplementation in an alpine low-input dairy system? Livestock Science 170, 7283.CrossRefGoogle Scholar
Katzenberger, K, Rauch, E, Erhard, M, Reese, S and Gauly, M (2020) Evaluating the need for an animal welfare assurance programme in South Tyrolean dairy farming. Italian Journal of Animal Science 19, 11471157.CrossRefGoogle Scholar
Kiefer, L, Over, R and Bahrs, E (2015) Weniger (Kraftfutter) ist manchmal mehr (Gewinn)–ein Plädoyer für hohe Grundfutterleistungen in der ökologischen Milchproduktion. [Less (concentrated feed) is sometimes more (profit)-a plea for high roughage performance in organic milk production].Google Scholar
Kirchgeßner, M (2008) Tierernährung: Leitfaden für Studium, Beratung und Praxis. [Animal nutrition: Guide for study, advice and practice] 12. Auflage. DLG-Verl. Frankfurt am Main.Google Scholar
Knaus, W (2009) Dairy cows trapped between performance demands and adaptability. Journal of the Science of Food and Agriculture 89, 11071114.Google Scholar
Koeck, A, Loker, S, Miglior, F, Kelton, DF, Jamrozik, J and Schenkel, FS (2014) Genetic relationships of clinical mastitis, cystic ovaries, and lameness with milk yield and somatic cell score in first-lactation Canadian Holsteins. Journal of Dairy Science 97, 58065813.CrossRefGoogle ScholarPubMed
Leiber, F, Schenk, IK, Maeschli, A, Ivemeyer, S, Zeitz, JO, Moakes, S and Walkenhorst, M (2017) Implications of feed concentrate reduction in organic grassland-based dairy systems: a long-term on-farm study. Animal: An International Journal of Animal Bioscience 11, 2051.CrossRefGoogle ScholarPubMed
MacDonald, JM, McBride, WD, O'Donoghue, E, Nehring, RF, Sandretto, C and Mosheim, R 2007 Profits, costs, and the changing structure of dairy farming. USDA-ERS Economic Research Report 47.Google Scholar
Manson, J and Leaver, E (1988) The influence of concentrate amount on locomotion and clinical lameness in dairy cattle. Animal Science 47, 185190.Google Scholar
Mattiello, S, Klotz, C, Baroli, D, Minero, M, Ferrante, V and Canali, E (2009) Welfare problems in alpine dairy cattle farms in Alto Adige (Eastern Italian Alps). Italian Journal of Animal Science 2, 628630.CrossRefGoogle Scholar
Mattiello, S, Battini, M, Andreoli, E and Barbieri, S (2011) Breed differences affecting dairy cattle welfare in traditional alpine tie-stall husbandry systems. Journal of Dairy Science 94, 24032407.CrossRefGoogle ScholarPubMed
Mee, JF (1990) Crossbreeding in the dairy herd – coping with calving problems. Irish Grassland and Animal Production Association Journal 24, 2431.Google Scholar
Oltenacu, PA, Hultgren, J and Algers, B (1998) Associations between use of electric cow-trainers and clinical diseases, reproductive performance and culling in Swedish dairy cattle. Preventive Veterinary Medicine 37, 7790.CrossRefGoogle ScholarPubMed
Ostojić-Andrić, D, Hristov, S, Novaković, Ž, Pantelić, V, Petrović, MM, Zlatanović, Z and Nikšić, D (2011) Dairy cows welfare quality in loose vs tie housing system. Biotechnology in Animal Husbandry 27, 975984.Google Scholar
Poetsch, EM (2007) Low input farming systems: an opportunity to develop sustainable agriculture LIFS & livestock production – grassland and dairy farming in Austria. JRC Summer University Ranco Italy, pp. 3338.Google Scholar
Poulopoulou, I, Nock, MC, Steinmayer, S, Lambertz, C and Gauly, M (2018) How can working time analysis contribute to the production efficiency of dairy farms in mountain regions? Italian Journal of Animal Science 17, 489498.CrossRefGoogle Scholar
Pritchard, T, Coffey, M, Mrode, R and Wall, E (2013) Genetic parameters for production, health, fertility and longevity traits in dairy cows. Animal: an International Journal of Animal Bioscience 7, 34.CrossRefGoogle ScholarPubMed
Pryce, JE, Coffey, MP, Brotherstone, SH and Woolliams, JA (2002) Genetic relationships between calving interval and body condition score conditional on milk yield. Journal of Dairy Science 85, 15901595.CrossRefGoogle ScholarPubMed
Regula, G, Danuser, J, Spycher, B and Wechsler, B (2004) Health and welfare of dairy cows in different husbandry systems in Switzerland. Preventive Veterinary Medicine 66, 247264.CrossRefGoogle ScholarPubMed
Resch, R, Buchgraber, K, Pötsch, E, Wiedner, G, Tiefenthaler, F, Fasching, C and Meusburger, C (2010) Abschlussbericht Heuqualität [Final report hay quality], Landesforschungszentrum Raumberg Gumpenstein.Google Scholar
Roche, JR, Macdonald, KA, Burke, CR, Lee, JM and Berry, DP (2007) Associations among body condition score, body weight, and reproductive performance in seasonal-calving dairy cattle. Journal of Dairy Science 90, 376391.CrossRefGoogle ScholarPubMed
Sant'Anna, AC and da Costa, MP (2011) The relationship between dairy cow hygiene and somatic cell count in milk. Journal of Dairy Science 94, 38353844.Google ScholarPubMed
Spiekers, H, Klünter, AM, Potthast, V and Pfeffer, E (1991) Effects of different concentrate levels on milk yield, feed intake, live weight change, health and reproduction in dairy cows. Livestock Production Science 28, 89105.Google Scholar
Südtiroler Rinderzuchtverband (2017) [accessed 08/14/2020]. Available at http://www.rinderzuchtverband.it/organisation.html.Google Scholar
Südtiroler Sennereiverband (2017) Nachhaltigkeitsbericht [Sustainability report]. [accessed 08/14/2020] Available at https://www.suedtirolermilch.com/images/files/Nachhaltigkeitsbericht_DE-DS-low.pdf.Google Scholar
Tasser, E, Schermer, M, Siegl, G and Tappeiner, U (2012) Wir Landschaftsmacher: vom Sein und Werden der Kulturlandschaft in Nord-, Ost-und Südtirol [We landscape designers: about being and becoming the cultural landscape in North, East and South Tyrol]. AthesiaGoogle Scholar
Ward, WR, Hughes, JW, Faull, WB, Cripps, PJ, Sutherland, JP and Sutherst, JE (2002) Observational study of temperature, moisture, pH and bacteria in straw bedding, and faecal consistency, cleanliness and mastitis in cows in four dairy herds. Veterinary Record 151, 199206.CrossRefGoogle ScholarPubMed
Weinrich, R, Kühl, S, Zühlsdorf, A and Spiller, A (2014) Consumer attitudes in Germany towards different dairy housing systems and their implications for the marketing of pasture raised milk. International Food and Agribusiness Management Review 17, 205.Google Scholar
Weiß, J (2001) Grundfutterleistung einheitlich berechnen [Calculate roughage performance uniformly]. Milchpraxis 39, 114114.Google Scholar
Welfare Quality® (2009) Welfare Quality® assessment protocol for cattle. Welfare Quality® Consortium, Lelystad, NetherlandsGoogle Scholar
Zendri, F, Ramanzin, M, Bittante, G and Sturaro, E (2016) Transhumance of dairy cows to highland summer pastures interacts with breed to influence body condition, milk yield and quality. Italian Journal of Animal Science 15, 481491.Google Scholar
Zollitsch, W, Ferris, C, Sairanen, A and Steinwidder, A (2016) Breeding cows suitable for low-input and organic dairy systems [accessed 06/24/2020] http://jukuri.luke.fi/han-dle/10024/534957Google Scholar
Zuliani, A, Romanzin, A, Corazzin, M, Salvador, S, Abrahantes, JC and Bovolenta, S (2017) Welfare assessment in traditional mountain dairy farms: above and beyond resource-based measures. Animal Welfare 26, 203211.CrossRefGoogle Scholar
Zurbrigg, K, Kelton, D, Anderson, N and Millman, S (2005) Tie-stall design and its relationship to lameness, injury, and cleanliness on 317 Ontario dairy farms. Journal of Dairy Science 88, 32013210.Google ScholarPubMed
Figure 0

Table 1. Farm characteristics of the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use

Figure 1

Table 2. Animal based measures for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use, restricted to parameters exhibiting significant differences

Figure 2

Table 3. Health and reproductive parameters for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use, restricted to parameters exhibiting significant differences

Figure 3

Table 4. Resource based measures for the 64 small-scale mountain dairy farms, divided into the groups L-TG, L-BS, H-TG and H-BS depending on breed and concentrate use

Supplementary material: PDF

Flach et al. supplementary material

Tables S1-S5

Download Flach et al. supplementary material(PDF)
PDF 209.5 KB