Case Study on the Impact of Water Resources in Beef Production: Corn vs. Triticale Silage in the Diet of Limousine × Podolian Young Bulls
by
, , , and
Carlo Cosentino
1
,
Rosanna Paolino
1,*,
Francesco Adduci
1,
Simona Tarricone
2,*,
Corrado Pacelli
1,
Emilio Sabia
1 and
Pierangelo Freschi
1
1
School of Agricultural, Forestry, Food and Environmental Sciences (SAFE), University of Basilicata, 85100 Potenza, Italy
2
Department of Soil, Plant and Food Science, University of Bari Aldo Moro, 70125 Bari, Italy
*
Authors to whom correspondence should be addressed.
Animals 2023, 13(21), 3355; https://doi.org/10.3390/ani13213355
Submission received: 6 October 2023
/
Revised: 24 October 2023
/
Accepted: 27 October 2023
/
Published: 29 October 2023
(This article belongs to the Section Animal Nutrition)
Abstract
:Simple Summary
Agriculture accounts for 92% of the global freshwater footprint (WF), of which more than a quarter is used in livestock production for feed, mixing feed, watering animals and agricultural activities. This study shows that replacing maize silage with triticale silage in the diet of beef calves results in a relevant reduction in water consumption per cattle per day, without changing growth performance. It also shows how feed choice can help improve the water balance of livestock production, and thus reduce the pressure that the sector puts on water resources.
Abstract
In this study, we have included the water footprint (WF) in the process of optimizing animal feed rations. The global footprint of cattle production accounts for the largest share (33%) of the global water footprint of livestock production. Using two homogeneous groups of Limousine × Podolian young bulls, two different diets were compared: corn silage feeding (CSF), with a corn silage-based diet; and triticale silage feeding (TSF), with a triticale silage-based diet. Silage constituted about 41% and 46% of the feed composition (for CSF and TSF, respectively). Diets were characterised by the same energy and protein content. Despite the lower WF in the TSF group than in the CSF group (7726 vs. 8571 L/day/calf respectively), no significant differences were found in animal performances (i.e., daily weight gain and final weight), feed conversion or income over feed costs. These results show that simple production decisions can have a significant impact on water resource. Therefore, the use of triticale silage should be further promoted, especially in world regions with limited water resources where low WF feed formulation is more strategic than elsewhere.
1. Introduction
Our dependence on water resources will increase significantly in the future, posing problems for future food security and environmental sustainability [1,2,3]. The European Green Deal and its Farm to Fork Strategy [4] aim to develop a sustainable food system along the whole value chain, from primary production to final consumption. Quantifying the water footprint (WF) of food consumption in the European Union and setting reduction targets are key topics of this strategy. The relationship between the freshwater resource and human productive activities, the Water Footprint Assessment (WFA), was developed to assess the amount of water consumed and water polluted. This concept was introduced by Hoekstra [5] and elaborated and validated by Chapagain and Hoekstra [6]. Cattle farming represents the largest share (33%) of the global livestock WF of production, followed by pigs (19%), dairy cows (19%) and poultry (11%), the latter which appears to be the most efficient sector in the use of natural resources, requiring 11 times less feed (in dry matter) than beef production [7,8,9]. Animal feeding, together with animal health and welfare assessment [10,11], plays a fundamental role in the economic and technical efficiency of animal production. Feeding accounts for about 60% of total costs in livestock farming and much of the water consumption in the livestock sector is used to produce feed [12,13,14,15,16,17]. Livestock feed production, which is a non-negligible cause of water pollution, takes up 70% of available agricultural land, including 33% of arable land and 8% of blue water used by humans [18]. Given the dual pressures of water scarcity and human nutrient needs, the basis for a sustainable supply of ruminant products is to clarify the consumption of water resources and the efficiency of water use in relation to the production of ruminant products, as well as the efficiency of nutrient conversion [19]. The use of irrigated maize has increased from 29% to 63% between 2004 and 2014 [20]. This has led to an increasing share of water resources being used for irrigation [21], steadily increasing the water footprint required for livestock feeding [22]. Compared to other cereals, triticale is more resistant to drought and disease, is suitable for low-input cultivation due to its low need for pesticides and can be grown on rather marginal land. With regard to the palatability and metabolizable energy of this grain, these aspects are mentioned as limiting factors for the use of triticale in the diet of monogastric animals only [23,24]. Against this background, the present study investigated the effect of replacing maize silage with triticale silage in the diet of Limousine × Podolian young bulls.
2. Materials and Methods
The trial was conducted on a farm in the Basilicata region, Italy, at an altitude of 600 m a.s.l. with forty 8-month-old Limousine × Podolian young bulls. Podolian cattle are an autochthonous breed belonging to the Hungarian Grey Steppe group and are reared in southern Italy [25,26], mainly in extensive management [27]. They are often crossed with specialized breeds to maximise meat production. During the experimental period, the animals, aged 230 ± 11 days, were kept in two different boxes with straw bedding (8.5 m2/head) in the same barn. Their initial average weight (mean ± SE) was 347.4 ± 0.741 kg in group 1 and 341.3 ± 0.636 kg in group 2. The manure management system used on the farm is liquid/slurry, where the manure is stored in the excreted form or with a minimal addition of water either in tanks or earthen ponds outside the barn, usually for a period of less than one year.
2.1. Diet Composition and Feeding
Two different diets were used: corn silage feed (CSF) for group 1 (n = 20) and triticale silage feed (TSF) for group 2 (n = 20). Triticale has a biological cycle that develops during the cold season (maize microtherm) and prefers high temperatures at the end of its cycle, therefore the WF is lower than maize, which shows an opposite behaviour in terms of heat and water requirements. The diets were formulated to be isoenergetic (0.90 UFV kg DM, 1 UFV 1820 kcal net energy) [28], with the same concentration of crude protein, crude fibre and starch as well as the same feed cost.
Feeding was administered using the total mixed ration (TMR) method [29,30] according to the composition given in Table 1. The TMR was sampled monthly and the chemical analysis of the TMR was performed according to the methods described in the scientific literature [31]. Using a NIRSYSTEM 5000 (Foss, Hillerød, Denmark) the following parameters were analysed: dry matter (DM), crude protein (CP), crude fibre (CF), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), ether extract (EE), ash and starch. The percentage of energy and PDI requirements of cattle were calculated according to the method proposed by Garcia et al. [32]. TMR was administered ad libitum to each group. Feed intake and feed refusal were measured every 14 days for each experimental group. There were no individual measurements of feed intake as the young bulls of each group were housed in the same box. The average feed intake for the group was calculated every 14 days according to the following relationship:
Average daily feed intake (g/d) = (Total feed administered − Total feed refusal)/20
2.2. Live Weight and Daily Weight Gain
Live weight (LW) was measured every 14 days (approximately 6 h after administration of the daily ration) and average daily gain (ADG) in each period was calculated.
2.3. Feed Conversion Ratio and Income over Feed Cost
The assessment of the technical and economic feed rations given to each group during the experimental period was conducted by calculating, in each interval of 14 days, feed conversion ratio (FCR) and income over feed cost (IOFC). FCR is defined as consumed kg DM/kg LW produced and is used to evaluate the effects of feed quality, environment and management practices on production efficiency in cattle rearing and fattening [33]. The IOFC measures the difference between the production meat value and the feed cost and was calculated according to the following formula proposed by Bailey et al. [34]:
where PLW is the farm-gate price of calf live weight (EUR/kg), DWG is the daily weight gain (kg/d), and DFC is the daily feed cost (EUR/head).
IOFC = PLW × DWG − DFC
2.4. Water Footprint Estimation
The WF of the live weight gain was calculated by adding feed WF (water for feed production), feed mix WF (water for feed mix), drinking WF (water intake) and service WF (water for cleaning the pen) according to the following formula [6,35]:
WFA meat = WF feed + WF feed mixing + WF drinking + WF service
Green, blue and grey water were estimated during the experimental period for indirect and direct water footprint and live weight gain in kg. The green water footprint refers to soil moisture generated by evaporation of precipitation and used for crop production or moisture present in the product. The blue water footprint refers to evaporated surface or groundwater that enters the product or is reused elsewhere. The grey water footprint is defined as the amount of freshwater required to assimilate the pollutant load based on existing water quality standards [36]. Data from the literature were used to calculate the indirect water footprint of the feed used for both forages [7], while the other fractions (watering, mixing and service) were assessed on the farm using a mechanical water metre. The water used for mixing the animal feed was added to the blue water component in the feed ration.
2.5. Statistical Analysis
One-way ANOVA was applied to determine the effect of diet using R software (R Core Version 3.6.1, Vienna, Austria) [37]. Data are expressed as mean ± SE and differences between groups were tested by Student’s t-test.
3. Results and Discussions
The present study investigated the effects of replacing maize silage with triticale silage in the diet of Limousine × Podolian young bulls on animal performance and on the total water footprint required for livestock feeding.
No significant differences were found between the groups in the daily intake of DM. The intake of DM throughout the trial period was 8.00 kg/day for the SF group and 7.80 kg/day for the AF (Table 2).
The CSF and TSF groups achieved 596.43 and 585.91 kg LW and 1365 and 1341 kg/day DWG, respectively (Table 3). No significant differences were found between the two groups in terms of final LW and DWG.
Over the entire experimental period, FCR was 5.896 for the SF group and 5.857 for the AF group (Table 4).
Moeinoddini et al. [23] compared triticale- and corn-based diets in Holstein calves and found no effect on feed efficiency. In addition, their dietary treatment did not affect heart girth and body length. However, withers height and hip at weaning increased in calves fed triticale compared to the other diet. In the USA, Hill and Utley [38] compared three feedlot rations in finishing steers, consisting of corn only, corn/triticale and triticale only. The evaluation of steer performance and carcass quality traits showed no significant difference between treatment effects. The above-mentioned studies on calves are consistent with our research, which shows no differences in feed efficiency between triticale and corn feeds. In studies conducted on large numbers of animals, to understand functionality in beef production (e.g., muscularity and body condition score), predictive models like Legendre polynomials would be profitable [39].
The main concerns regarding the use of triticale in feed is due to the high potential for ergot contamination, which can have a negative impact on health and performance if, according to Shumann et al. [40], the growing bull feed contains up to 2.25 g of ergot or more than 400 µg of ergot alkaloid per kg DM. Other authors [41,42] point out that the focus should be on alkaloid concentration rather than ergot content, as the percentage of alkaloids in the different ergot sclerotia varies greatly [41,42].
Considering the whole experimental period, the income over feed cost (PLW = 3.50 EUR/kg LW; DFC = 0.420 EUR/kg DM × DM daily intake) was EUR 1.418/day in both groups over the whole experimental period (Table 5). Furthermore, the fixed costs associated with feed production and utilisation, such as silos, fencing, buildings and machinery, are an additional consideration when costing feed [43]. Given that feed costs represent such a large proportion of total costs, it is clear that effective management of feeding strategy decisions can contribute significantly to the economic sustainability and profitability of livestock farms [44].
The average water footprint of the ADG calculated over the whole experimental period was 6221.29 L in the CSF group and 5703.60 L in the TSF group. Therefore, the WF difference per kg LWG was 517.70 L between the two groups (Figure 1). The daily average intake of green, blue and grey water in the groups CSF and TSF was 76.09%, 13.59% and 10.32% and 82.45%, 6.37% and 11.18%, respectively. Gerbens-Leenes et al. [13], in a study on WF industrial beef production in four countries, reported values (L/kg LW) in the interval 4000–5000 in the NL and the USA, and close to 9000 in Brazil and 13,000 in China. This study also illustrated that choosing feed ingredients and sourcing wisely, and particularly substituting crops with co-products or crop residues, will help to improve the WP of livestock products, thus reducing the pressure the sector puts on scarce water resources. The highest total WF for beef production was evidenced in Brazil by Palhares et al. [45] with values ranging from 9249 to 23,521 L/kg LW. In another study in Arcadia Valley (MO, USA), Eady et al. [46] compared two rearing systems in beef cattle production, a farm with 634 cows delivering weaners and a farm with 720 cows delivering finished cattle; green water use ranged from 7400 to 12,700 L/kg LW depending on the class of livestock, with on-farm blue water use of 51–96 L/kg liveweight and off-farm blue water use of 0.1–59 L/kg LW.
The percentage of WF in the consumed feed components observed during the trial period was similar to the data reported by Chapagain and Hoekstra [35] for industrially bred cattle. As shown in Table 6, the percentage of WF feed was higher in the CSF group than in the TSF group (8471 vs. 7726), as there was a relevant water saving (745 L per bovine per day) in the TSF group.
According to Mekonnen and Hoekstra [7], feed consumption accounts for the largest share of water consumption in livestock production (98.83% and 98.70% in our study in TSF and AF, respectively), while the share of drinking, industrial and mixed water is quite low for both types of feed administration (<3%). Mourad et al. [47] observed a mean percentage of water allocation for WF of 98.3% in the central and northeastern region of Africa. Given the many variables involved in determining WF, it has been suggested by various authors [45,48] that general recommendations cannot be made on a large scale, e.g., to formulate policy recommendations, but only for individual operations. Furthermore, Broom [49], in a study that considered land use and conserved water data from different parts of the world, showed the large impact of farming systems on water resource use and the need to consider all systems when considering the impact of beef or other products on the global environment.
4. Conclusions
The sustainable management of agricultural and farming systems and tracking the impacts they cause is a complex task, and all the more so in a changing climate. The use of triticale silage in the diet instead of corn, when properly optimised, showed a lower water footprint in meat production, while maintaining the same technical and economic efficiency as feeding corn silage to cattle. These results confirm the possibility of including the water footprint parameter in ration optimisation and show that simple production decisions can have a significant impact on the consumption of water resources and on the sustainability of beef production. This study used data collected at the regional level, the use of which, rather than national average data for food ingredient production characteristics, provides a more accurate estimate of water resource impacts on beef production. One criticism of the present study could be that it was conducted for a single beef production system. The organization of primary data from individual studies into databases and expanding WF studies for the beef product will contribute to a better understanding of how water efficiency can be improved in this sector through a bottom-up approach.
Author Contributions
Conceptualization, C.C., F.A. and P.F.; methodology, F.A.; software, R.P.; validation, C.C. and S.T.; formal analysis, C.C.; investigation, R.P., E.S. and F.A.; resources, C.C.; data curation, S.T., C.P. and E.S.; writing—original draft preparation, R.P.; writing—review and editing, F.A. and S.T.; visualization, S.T.; supervision, C.C., C.P. and P.F.; project administration, C.C.; funding acquisition, C.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Ethic Committee Name: ORGANISMO PREPOSTO AL BENESSERE ANIMALE; Approval Code:OpBA 10_2023_UNIBAS; Approval Date: 9 October 2023.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data are available on request.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Alcamo, J.; Döll, P.; Henrichs, T.; Kaspar, F.; Lehner, B.; Rösch, T.; Siebert, S. Development and testing of the Water GAP 2 global model of water use and availability. Hydrol. Sci. J. 2003, 48, 317–337. [Google Scholar] [CrossRef]
- Rosegrant, M.W.; Ringler, C.; Zhu, T. Water for Agriculture: Maintaining Food Security under Growing Scarcity. Annu. Rev. Environ. Resour. 2009, 34, 205–222. [Google Scholar] [CrossRef]
- Rosegrant, M.W.; Cai, X.; Cline, S.A. Global Water Outlook to 2025. Averting an Impending Crisis; International Food Policy Research Institute: Washington, DC, USA, 2002; pp. 12–24. Available online: https://core.ac.uk/Download/Pdf/6289055.Pdf (accessed on 28 May 2023).
- Wesseler, J. The EU ’s Farm-to-Fork Strategy: An Assessment from the Perspective of Agricultural Economics. Appl. Econ. Perspect. Policy 2022, 44, 1826–1843. [Google Scholar] [CrossRef]
- Hoekstra, A.Y. Virtual Water Trade: Proceedings of the International Expert Meeting on Virtual Water Trade; Value of Water Research Report Series No. 12; UNESCO-IHE: Delft, The Netherlands, 2022; Available online: www.waterfootprint.org/reports/report12.pdf (accessed on 17 September 2023).
- Chapagain, A.K.; Hoekstra, A.Y. Virtual Water Flows Between Nations in Relation to Trade in Livestock and Livestock Products; Value of Water Research Report; UNESCO-IHE: Delft, The Netherlands, 2003; pp. 11–30. Available online: https://www.waterfootprint.org/resources/Report13.pdf (accessed on 14 April 2023).
- Mekonnen, M.M.; Hoekstra, A.Y. A Global Assessment of the Water Footprint of Farm Animal Products. Ecosystems 2012, 15, 401–415. [Google Scholar] [CrossRef]
- Mekonnen, M.M.; Neale, C.M.U.; Ray, C.; Erickson, G.E.; Hoekstra, A.Y. Water Productivity in Meat and Milk Production in the US from 1960 to 2016. Environ. Int. 2019, 132, 105084. [Google Scholar] [CrossRef]
- Mottet, A.; De Haan, C.; Falcucci, A.; Tempio, G.; Opio, C.; Gerber, P. Livestock: On Our Plates or Eating at Our Table? A New Analysis of the Feed/Food Debate. Glob. Food Secur. 2017, 14, 1–8. [Google Scholar] [CrossRef]
- Masebo, N.T.; Marliani, G.; Cavallini, D.; Accorsi, P.A.; Di Pietro, M.; Beltrame, A.; Gentile, A.; Jacinto, J.G.P. Health and Welfare Assessment of Beef Cattle during the Adaptation Period in a Specialized Commercial Fattening Unit. Res. Vet. Sci. 2023, 158, 50–55. [Google Scholar] [CrossRef] [PubMed]
- Vinassa, M.; Cavallini, D.; Galaverna, D.; Baragli, P.; Raspa, F.; Nery, J.; Valle, E. Palatability Assessment in Horses in Relation to Lateralization and Temperament. Appl. Anim. Behav. Sci. 2020, 232, 105110. [Google Scholar] [CrossRef]
- De Fraiture, C.; Wichelns, D.; Rockström, J.; Kemp-Benedict, E.; Eriyagama, N.; Gordon, L.J.; Hanjra, M.A.; Hoogeveen, J.; Huber-Lee, A.; Karlberg, L. Looking Ahead to 2050: Scenarios of Alternative Investment Approaches. In Water for Food, Water for Life: A Comprehensive Assessment of Water Management in Agriculture; Molden, D., Ed.; Earthscan: London, UK; International Water Management Institute (IWMI): Colombo, Sri Lanka, 2007; pp. 91–145. Available online: https://hdl.handle.net/10568/36869 (accessed on 14 April 2023).
- Gerbens-Leenes, P.W.; Mekonnen, M.M.; Hoekstra, A.Y. The Water Footprint of Poultry, Pork and Beef: A Comparative Study in Different Countries and Production Systems. Water Resour. Ind. 2013, 1–2, 25–36. [Google Scholar] [CrossRef]
- Ridoutt, B.G.; Sanguansri, P.; Nolan, M.; Marks, N. Meat Consumption and Water Scarcity: Beware of Generalizations. J. Clean. Prod. 2012, 28, 127–133. [Google Scholar] [CrossRef]
- Adduci, F.; Labella, C.; Musto, M.; D’Adamo, C.; Freschi, P.; Cosentino, C. Use of Technical and Economical Parameters for Evaluating Dairy Cow Ration Efficiency. Ital. J. Agron. 2015, 10, 202–207. [Google Scholar] [CrossRef]
- Campiotti, M. Sistemi Pratici per Fare Più Reddito in Stalla; L’Informatore Agrario: Verona, Italy, 2005. [Google Scholar]
- Cosentino, C.; Adduci, F.; Musto, M.; Paolino, R.; Freschi, P.; Pecora, G.; Valentini, C. Low vs High “Water Footprint Assessment” Diet in Milk Production: A Comparison between Triticale and Corn Silage Based Diets. Emir. J. Food Agric. 2015, 27, 312. [Google Scholar] [CrossRef]
- FAO. Livestock’s Long Shadow: Environmental Issues and Options; FAO: Rome, Italy, 2006; Available online: https://www.fao.org/3/A0701e/A0701e00.Htm (accessed on 29 September 2023).
- Zhang, H.; Zhuo, L.; Xie, D.; Liu, Y.; Gao, J.; Wang, W.; Li, M.; Wu, A.; Wu, P. Water Footprints and Efficiencies of Ruminant Animals and Products in China over 2008–2017. J. Clean. Prod. 2022, 379, 134624. [Google Scholar] [CrossRef]
- OECD. Endocrine Disrupting Chemicals in Freshwater: Monitoring and Regulating Water Quality; OECD Studies on Water; OECD: Paris, France, 2023; ISBN 978-92-64-53751-4. [Google Scholar]
- FAO. Turkey. Water Along the Food Chain. Towards Water-Smart Agrifood Policies: The Case of Red Meat Processing. Country Highlights. FAO Investment Centre; FAO: Rome, Italy, 2016; ISBN 978-92-5-109360-3. [Google Scholar]
- Chaves, A.R.D.; Moraes, L.G.; Montaño, A.S.; Da Cunha, F.F.; Theodoro, G.D.F. Analysis of Principal Components for the Assessment of Silage Corn Hybrid Performance under Water Deficit. Agriculture 2023, 13, 1335. [Google Scholar] [CrossRef]
- Moeinoddini, H.R.; Alikhani, M.; Ahmadi, F.; Ghorbani, G.R.; Rezamand, P. Partial Replacement of Triticale for Corn Grain in Starter Diet and Its Effects on Performance, Structural Growth and Blood Metabolites of Holstein Calves. Animal 2017, 11, 61–67. [Google Scholar] [CrossRef] [PubMed]
- Shimada, A.; Cline, T.R.; Rogler, J.C. Nutritive Value of Triticale for the Nonruminant. J. Anim. Sci. 1974, 38, 935–940. [Google Scholar] [CrossRef] [PubMed]
- Tarricone, S.; Colonna, M.A.; Giannico, F.; Facciolongo, A.M.; Caputi Jambrenghi, A.; Ragni, M. Effects of Dietary Extruded Linseed (Linum usitatissimum L.) on Performance and Meat Quality in Podolian Young Bulls. S. Afr. J. Anim. Sci. 2019, 49, 781. [Google Scholar] [CrossRef]
- Cosentino, C.; D’Adamo, C.; Naturali, S.; Pecora, G.; Paolino, R.; Musto, M.; Adduci, F.; Freschi, P. Podolian Cattle: Reproductive Activity, Milk and Future Prospects. Ital. J. Agron. 2018, 13, 200–207. [Google Scholar] [CrossRef]
- Freschi, P.; Musto, M.; Paolino, R.; Cosentino, C. Grazing and Biodiversity Conservation: Highlights on a Natura 2000 Network Site. In The Sustainability of Agro-Food and Natural Resource Systems in the Mediterranean Basin; Vastola, A., Ed.; Springer: Cham, Swizerland, 2015; pp. 271–288. ISBN 978-3-319-16356-7. [Google Scholar]
- Lanzas, C.; Sniffen, C.J.; Seo, S.; Tedeschi, L.O.; Fox, D.G. A Revised CNCPS Feed Carbohydrate Fractionation Scheme for Formulating Rations for Ruminants. Anim. Feed Sci. Technol. 2007, 136, 167–190. [Google Scholar] [CrossRef]
- Koch, C.; Schönleben, M.; Mentschel, J.; Göres, N.; Fissore, P.; Cohrs, I.; Sauerwein, H.; Ghaffari, M.H. Growth Performance and Economic Impact of Simmental Fattening Bulls Fed Dry or Corn Silage-Based Total Mixed Rations. Animal 2023, 17, 100762. [Google Scholar] [CrossRef]
- Schingoethe, D.J. A 100-Year Review: Total Mixed Ration Feeding of Dairy Cows. J. Dairy Sci. 2017, 100, 10143–10150. [Google Scholar] [CrossRef] [PubMed]
- Giorgino, A.; Raspa, F.; Valle, E.; Bergero, D.; Cavallini, D.; Gariglio, M.; Bongiorno, V.; Bussone, G.; Bergagna, S.; Cimino, F.; et al. Effect of Dietary Organic Acids and Botanicals on Metabolic Status and Milk Parameters in Mid–Late Lactating Goats. Animals 2023, 13, 797. [Google Scholar] [CrossRef]
- Garcia, F.; Agabriel, J.; Micol, D. Alimentation Des Bovines in en Croissance et à l’Engrais. In Alimentation Des Bovins, Ovins et Caprins. Besoins Des Animaux- Valeurs Des Aliments. Table INRA; Editions Quae: Paris, France, 2010; pp. 91–122. Available online: http://www.civamad53.org/wp-content/uploads/2020/12/Tables-INRA.pdf (accessed on 2 September 2023).
- Fox, D.G.; Tedeschi, L.O.; Guiroy, P.J. Determining Feed Intake and Feed Efficiency of Individual Cattle Fed in Groups; Beef Improvement Federation: San Antonio, TX, USA, 2001; pp. 80–98. [Google Scholar]
- Bailey, K.; Beck, T.; Cowan, E.; Ishler, V. Management Education: Managing Income Over Feed Costs; Agricultural Communications and Marketing, The Pennsylvania State University: State College, PA, USA, 2009. [Google Scholar]
- Chapagain, A.K.; Hoekstra, A.Y. Water Footprints of Nations. Volume 1: Main Report; UNESCO-IHE: Delft, The Netherlands, 2004; p. 25. Available online: https://www.waterfootprint.org/resources/Report16Vol1.pdf (accessed on 14 April 2023).
- Hoekstra, A.Y.; Mekonnen, M.M. Global Water Scarcity: Monthly Blue Water Footprint Compared to Blue Water Availability for the World’s Major River Basins; Value of Water Research Report Series No.53; UNESCO-IHE: Delft, The Netherlands, 2011; pp. 12–24. [Google Scholar]
- R Core Version 3.6.1. Available online: https://www.r-project.org (accessed on 8 September 2023).
- Hill, G.M.; Utley, P.R. Digestibility, Protein Metabolism and Ruminal Degradation of Beagle 82 Triticale and Kline Barley Fed in Corn-Based Cattle Diets. J. Anim. Sci. 1989, 67, 1793. [Google Scholar] [CrossRef]
- Buonaiuto, G.; Lopez-Villalobos, N.; Niero, G.; Degano, L.; Dadati, E.; Formigoni, A.; Visentin, G. The Application of Legendre Polynomials to Model Muscularity and Body Condition Score in Primiparous Italian Simmental Cattle. Ital. J. Anim. Sci. 2022, 21, 350–360. [Google Scholar] [CrossRef]
- Schumann, B.; Dänicke, S.; Meyer, U.; Ueberschär, K.-H.; Breves, G. Effects of Different Levels of Ergot in Concentrates on the Growing and Slaughtering Performance of Bulls and on Carry-over into Edible Tissue. Arch. Anim. Nutr. 2007, 61, 357–370. [Google Scholar] [CrossRef] [PubMed]
- Young, R.H.; Potschin, M. Common International Classification of Ecosystem Services (CICES) V5.1 and Guidance on the Application of the Revised Structure; Fabis Consulting: Nottingham, UK, 2018. [Google Scholar]
- Filipov, N.M.; Thompson, F.N.; Stuedemann, J.A.; Elsasser, T.H.; Kahl, S.; Stanker, L.H.; Young, C.R.; Dawe, D.L.; Smith, C.K. Anti-Inflammatory Effects of Ergotamine in Steers. Proc. Soc. Exp. Biol. Med. 2000, 225, 136–142. [Google Scholar] [CrossRef] [PubMed]
- Peart, R.M.; Shoup, W.D. (Eds.) Agricultural Systems Management: Optimizing Efficiency and Performance, 1st ed.; CRC Press: Boca Raton, FL, USA, 2004; ISBN 978-0-429-21554-4. [Google Scholar] [CrossRef]
- Finneran, E.; Crosson, P.; O’Kiely, P.; Shalloo, L.; Forristal, D.; Wallace, M. Stochastic Simulation of the Cost of Home-Produced Feeds for Ruminant Livestock Systems. J. Agric. Sci. 2012, 150, 123–139. [Google Scholar] [CrossRef]
- Palhares, J.C.P.; Morelli, M.; Novelli, T.I. Water Footprint of a Tropical Beef Cattle Production System: The Impact of Individual-Animal and Feed Management. Adv. Water Resour. 2021, 149, 103853. [Google Scholar] [CrossRef]
- Eady, S.; Viner, J.; MacDonnell, J. On-Farm Greenhouse Gas Emissions and Water Use: Case Studies in the Queensland Beef Industry. Anim. Prod. Sci. 2011, 51, 667. [Google Scholar] [CrossRef]
- Mourad, R.; Jaafar, H.H.; Daghir, N. New Estimates of Water Footprint for Animal Products in Fifteen Countries of the Middle East and North Africa (2010–2016). Water Resour. Ind. 2019, 22, 100113. [Google Scholar] [CrossRef]
- Maré, F.A.; Jordaan, H.; Mekonnen, M.M. The Water Footprint of Primary Cow–Calf Production: A Revised Bottom-Up Approach Applied on Different Breeds of Beef Cattle. Water 2020, 12, 2325. [Google Scholar] [CrossRef]
- Broom, D.M. Land and Water Usage in Beef Production Systems. Animals 2019, 9, 286. [Google Scholar] [CrossRef]
Figure 1.
Water footprint (L/kg ADG) calculated over the entire experimental period. CSF: Corn silage feeding; TSF: Triticale silage feeding.
Figure 1.
Water footprint (L/kg ADG) calculated over the entire experimental period. CSF: Corn silage feeding; TSF: Triticale silage feeding.
Table 1.
Composition, estimated nutritive values and costs of diet 1.
| Components | CSF | TSF |
|---|---|---|
| Diet composition, % | ||
| Corn Silage | 41.1 | - |
| Triticale Silage | - | 45.9 |
| Corn Meal | 13.7 | 13.7 |
| Wheat Straw | 13.7 | 6.9 |
| Barley Meal | 1.4 | 5.5 |
| Corn Gluten Meal | - | 3.8 |
| Sunflower Meal | - | 6.9 |
| Soybean Meal Extraction | 10.27 | - |
| Beet Pressed Pulp | 3.4 | 5.5 |
| Corn Distillers | 3.4 | 1.7 |
| Hydrogenated Fat | 1.0 | - |
| Vitamin Mineral Supplement | 1.4 | 1.4 |
| NaHCO3 | 1.0 | 1.0 |
| NaCl | 0.7 | 1.03 |
| Water Mixing | 8.9 | 6.8 |
| DM | 58.4 | 58.3 |
| Feed cost | ||
| EUR/kg DM | 0.42 | 0.42 |
| Chemical composition, g/kg DM a | ||
| CP | 147.4 | 147.0 |
| CF | 166.4 | 167.6 |
| NDF | 367.5 | 390.7 |
| ADF | 212.3 | 239.7 |
| ADL | 42.7 | 46.3 |
| EE | 43.0 | 27.1 |
| Ash | 78.9 | 87.9 |
| Starch | 248.8 | 249.7 |
| Nutritive value, kg/DM | ||
| UFV b | 0.9 | 0.9 |
| PDIN c | 96.5 | 106.0 |
| PDIE d | 105.1 | 111.8 |
| PDIA e | 51.5 | 59.5 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding; a Calculated by analysis of TMR; b UFV: Feed unit for meat production (net energy); c PDIN: Protein digested in the small intestine when rumen-fermentable nitrogen is limited; d PDIE: Protein digestible in the small intestine; e PDIA: Protein digestible in the small intestine supplied by rumen-undegraded dietary protein.
Table 2.
Average daily dry matter intake ( ± SE) 1.
| Trial Day | CSF | TSF | p-Value | ||
|---|---|---|---|---|---|
| DM | SE | DM | SE | ||
| 0 | 6.56 | 0.039 | 6.41 | 0.033 | 0.551 |
| 14 | 6.8 | 0.041 | 6.64 | 0.035 | 0.121 |
| 28 | 7.03 | 0.043 | 6.86 | 0.036 | 0.222 |
| 42 | 7.26 | 0.044 | 7.09 | 0.037 | 0.473 |
| 56 | 7.49 | 0.046 | 7.31 | 0.039 | 0.098 |
| 70 | 7.71 | 0.048 | 7.52 | 0.040 | 0.372 |
| 84 | 7.93 | 0.049 | 7.73 | 0.042 | 0.440 |
| 98 | 8.14 | 0.051 | 7.94 | 0.043 | 0.089 |
| 112 | 8.35 | 0.052 | 8.15 | 0.044 | 0.156 |
| 126 | 8.55 | 0.054 | 8.34 | 0.045 | 0.399 |
| 140 | 8.75 | 0.055 | 8.54 | 0.046 | 0.414 |
| 154 | 8.95 | 0.057 | 8.73 | 0.048 | 0.444 |
| 168 | 9.13 | 0.058 | 8.91 | 0.049 | 0.088 |
| 182 | 9.32 | 0.059 | 9.09 | 0.050 | 0.115 |
| All | 8.00 | 0.050 | 7.80 | 0.040 | 0.255 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding; DM: Dry matter.
Table 3.
Live weight (LW) and average daily gain (ADG) ( ± SE) 1.
| Trial Day | LW, kg | p-Value | ADG, kg/day | p-Value | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| CSF | SE | TSF | SE | CSF | SE | TSF | SE | |||
| 1 | 347.43 | 0.741 | 341.3 | 0.636 | 0.291 | 1.42 | 0.003 | 1.39 | 0.003 | 0.471 |
| 14 | 367.32 | 0.783 | 360.84 | 0.673 | 0.418 | 1.42 | 0.003 | 1.40 | 0.003 | 0.223 |
| 28 | 387.26 | 0.826 | 380.43 | 0.709 | 0.586 | 1.43 | 0.003 | 1.40 | 0.003 | 0.318 |
| 42 | 407.19 | 0.868 | 400.01 | 0.746 | 0.577 | 1.42 | 0.003 | 1.40 | 0.003 | 0.098 |
| 56 | 427.07 | 0.911 | 419.53 | 0.782 | 0.834 | 1.42 | 0.003 | 1.39 | 0.003 | 0.355 |
| 70 | 446.84 | 0.953 | 438.95 | 0.818 | 0.722 | 1.41 | 0.003 | 1.38 | 0.003 | 0.472 |
| 84 | 466.45 | 0.994 | 458.23 | 0.854 | 0.650 | 1.40 | 0.003 | 1.37 | 0.003 | 0.399 |
| 98 | 485.88 | 1.036 | 477.31 | 0.89 | 0.388 | 1.38 | 0.003 | 1.36 | 0.003 | 0.211 |
| 112 | 505.07 | 1.077 | 496.16 | 0.925 | 0.617 | 1.36 | 0.003 | 1.34 | 0.002 | 0.118 |
| 126 | 524 | 1.117 | 514.75 | 0.959 | 0.171 | 1.34 | 0.003 | 1.32 | 0.002 | 0.222 |
| 140 | 542.62 | 1.157 | 533.05 | 0.993 | 0.433 | 1.32 | 0.003 | 1.30 | 0.002 | 0.569 |
| 154 | 560.92 | 1.196 | 551.02 | 1.027 | 0.738 | 1.30 | 0.003 | 1.27 | 0.002 | 0.104 |
| 168 | 578.86 | 1.234 | 568.65 | 1.06 | 0.092 | 1.27 | 0.003 | 1.25 | 0.002 | 0.274 |
| 182 | 596.43 | 1.272 | 585.91 | 1.092 | 0.114 | 1.24 | 0.003 | 1.22 | 0.002 | 0.099 |
| All | - | - | - | - | - | 1.37 | 0.003 | 1.34 | 0.002 | 0.117 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding.
Table 4.
Feed conversion ratio (FCR) ( ± SE) 1.
| Trial Day | Feed Conversion Ratio | p-Value | |||
|---|---|---|---|---|---|
| CSF | SE | TSF | SE | ||
| 0 | 4.629 | 0.08 | 4.603 | 0.09 | 0.233 |
| 14 | 4.777 | 0.05 | 4.748 | 0.03 | 0.455 |
| 28 | 4.935 | 0.09 | 4.904 | 0.02 | 0.128 |
| 42 | 5.104 | 0.11 | 5.072 | 0.12 | 0.241 |
| 56 | 5.285 | 0.07 | 5.251 | 0.06 | 0.364 |
| 70 | 5.477 | 0.06 | 5.442 | 0.05 | 0.455 |
| 84 | 5.682 | 0.07 | 5.645 | 0.05 | 0.451 |
| 98 | 5.900 | 0.07 | 5.860 | 0.04 | 0.624 |
| 112 | 6.131 | 0.06 | 6.089 | 0.09 | 0.131 |
| 126 | 6.376 | 0.09 | 6.332 | 0.03 | 0.832 |
| 140 | 6.635 | 0.05 | 6.589 | 0.09 | 0.221 |
| 154 | 6.910 | 0.07 | 6.861 | 0.07 | 0.119 |
| 168 | 7.200 | 0.08 | 7.149 | 0.05 | 0.417 |
| 182 | 7.507 | 0.07 | 7.454 | 0.09 | 0.151 |
| All | 5.896 | 0.05 | 5.857 | 0.09 | 0.331 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding.
Table 5.
Income over feed costs (IOFC) ( ± SE) 1.
| Trial Day | Income over Feed IOFC | p-Value | |||
|---|---|---|---|---|---|
| CSF | SE | TSF | SE | ||
| 0 | 2.215 | 0.25 | 2.173 | 0.13 | 0.485 |
| 14 | 2.114 | 0.13 | 2.111 | 0.11 | 0.094 |
| 28 | 2.052 | 0.09 | 2.019 | 0.15 | 0.163 |
| 42 | 1.921 | 0.15 | 1.922 | 0.09 | 0.551 |
| 56 | 1.824 | 0.08 | 1.795 | 0.13 | 0.258 |
| 70 | 1.697 | 0.10 | 1.672 | 0.20 | 0.335 |
| 84 | 1.569 | 0.11 | 1.548 | 0.12 | 0.711 |
| 98 | 1.411 | 0.11 | 1.425 | 0.10 | 0.223 |
| 112 | 1.253 | 0.09 | 1.267 | 0.14 | 0.066 |
| 126 | 1.099 | 0.10 | 1.117 | 0.08 | 0.494 |
| 140 | 0.945 | 0.12 | 0.963 | 0.16 | 0.239 |
| 154 | 0.791 | 0.14 | 0.778 | 0.08 | 0.366 |
| 168 | 0.61 | 1.13 | 0.633 | 0.11 | 0.251 |
| 182 | 0.426 | 1.11 | 0.452 | 0.13 | 0.592 |
| All | 1.418 | 0.90 | 1.418 | 0.11 | 0.114 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding.
Table 6.
Trial period water footprint average (L/day/animal) 1.
| Groups 1 | Indirect Water Footprint | Direct Water Footprint | WF Average L/Day/Animal | ||
|---|---|---|---|---|---|
| WFFeed | WFFeed Mixing | WFDrinking | WFService | ||
| Estimated | Observed | ||||
| CSF | 8471 | 1.439 | 23.99 | 75 | 8571 |
| TSF | 7626 | 1.756 | 23.41 | 75 | 7726 |
1 CSF: Corn silage feeding; TSF: Triticale silage feeding.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Cosentino, C.; Paolino, R.; Adduci, F.; Tarricone, S.; Pacelli, C.; Sabia, E.; Freschi, P. Case Study on the Impact of Water Resources in Beef Production: Corn vs. Triticale Silage in the Diet of Limousine × Podolian Young Bulls. Animals 2023, 13, 3355. https://doi.org/10.3390/ani13213355
AMA Style
Cosentino C, Paolino R, Adduci F, Tarricone S, Pacelli C, Sabia E, Freschi P. Case Study on the Impact of Water Resources in Beef Production: Corn vs. Triticale Silage in the Diet of Limousine × Podolian Young Bulls. Animals. 2023; 13(21):3355. https://doi.org/10.3390/ani13213355
Chicago/Turabian StyleCosentino, Carlo, Rosanna Paolino, Francesco Adduci, Simona Tarricone, Corrado Pacelli, Emilio Sabia, and Pierangelo Freschi. 2023. "Case Study on the Impact of Water Resources in Beef Production: Corn vs. Triticale Silage in the Diet of Limousine × Podolian Young Bulls" Animals 13, no. 21: 3355. https://doi.org/10.3390/ani13213355
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
