Dados do Trabalho

Título

Milk Composition and Quality in High-Input vs. Low-Input Feeding Systems on an Organic Farm

Titulo em português

Composição e Qualidade do Leite em Sistemas de Alimentação High-Input vs. Low-Input em Fazenda Orgânica

Introdução (obrigatório)

Organic milk production has gained attention as a sustainable alternative in the agricultural sector, driven by consumer demand for environmentally friendly and animal- welfare-focused products. Milk quality and composition reflect dairy cow health and production efficiency, heavily influenced by feeding regimens.
Generally, high-input feeding systems (HI), uses corn silage to maximize milk production by providing a constant energy source. In contrast, the low-input systems (LI) avoid or minimize the use of corn silage, focusing on local pastures and forages, avoiding land competition for human food production. (EISERT, 2019)
Our objective is to evaluate the impact of HI and LI feeding on milk quality in an organic dairy production system.

Material e métodos (obrigatório)

The study was conducted at the Gladbacherhof Experimental Farm of Justus Liebig University (JLU) Giessen. Germany, utilizing a herd of Holstein cows kept in an organic production system. This experiment is part of a project called GreenDairy - Integrated Animal, Plant, and Livestock Production system, where the environmental impacts of HI and LI feeding systems are evaluated. The animals were divided into two groups: one fed a HI diet including corn silage and a higher amount of concentrate (6.7 Kg/cow/day), and the other with a LI diet without corn silage and with a lower amount of concentrate (4.2 Kg/cow/day).  The basic diet for both groups consisted of grass silage, alfalfa silage, and access to pasture in spring and summer. Each group remained separated in the barn with access to a Lely A5 automated milking system (AMS). The milking system collected individual information on milk volume, fat and protein percentage, lactose, and somatic cell count at each milking. Data collection was conducted over one year, from June 2023 to June 2024, A variance analysis was conducted using the MIXED procedure (SAS), after testing the data for normality of residuals with the Kolmogorov– Smirnov test. To obtain data normality, SCC was transformed into somatic cell score (SCS) by applying the following equation: SCS = log2 (SCC/100,000) + 3 The REML model included the fixed effects of feeding group, season (spring (March to May), summer (June to August), autumn (September to November), and winter (December to February)), days in milk (DIM), and lactation number (LN – 1, 2 or 3+ and more lactation), as well as the interaction between feeding group and LN and the interaction between feeding group and season. The significance level was set at P<0.05.

Resultados e discussão (obrigatório)

The average fat content was higher in the LI group compared to the HI group (4.33 vs 4.18 respectively, Table 1) The fat content increased with each subsequent lactation for both feeding groups. Table 1. Comparison of fat and protein content from the High-input and Low-input feeding groups (in % ± standard error), separation by lactation number   Fat content Protein content   High - Input Low - Input High - Input Low - Input Average 4.18 ± 0.05 A 4.33 ± 0.04 B 3.18 ± 0.02 3.14 ± 0.02 Lactation Number 1 3.88 ± 0.05 Bc 4.05 ±   0.04 Ac 2.97 ± 0.02 c 3.01 ± 0.02 c 2 4.17 ± 0.05 Bb 4.41 ±   0.04 Ab 3.18 ± 0.02 b 3.13 ± 0.02 b 3 4.49 ± 0.05 a 4.55 ± 0.04 a 3.40 ±   0.02 Aa 3.27 ± 0.02 Ba Season Winter 4.37 ± 0.05 Ba 4.59 ±   0.04 Aa 3.35 ±   0.02 Aa 3.27 ± 0.02 Ba Spring 4.20 ± 0.05 b 4.45 ±   0.04 Ab 3.10 ± 0.02 b 3.14 ± 0.02 b Summer 3.96 ± 0.05 c 4.05 ± 0.04 d 3.21 ±   0.02 Ac 3.11 ± 0.02 Bc Autumn 4.18 ± 0.05 b 4.25 ± 0.04 c 3.07 ± 0.02 d 3.03 ± 0.02 d Uppercase letters indicate differences within rows, while lowercase letters represent differences within columns. Significance level p < 0.05. Seasonal variations showed the highest fat content in winter and the lowest in summer for both groups. Protein content varied less than fat, averaging 3.14% in the LI group and 3.18% in the HI group. Like fat, protein content increased with lactation number, with the highest levels in winter and the lowest in autumn for both groups. These findings emphasize the role of diet and seasonal changes in milk composition. The higher fat content in the LI group suggests that a grass-based diet influences milk fat synthesis differently, possibly due to fiber fermentation in the rumen producing short-chain fatty acids like acetate (REYNOLDS, 2006). Additionally, the increase in fat and protein content with lactation number indicates that mature cows produce higher quality milk. For somatic cell score (SCS), there was no significant difference between feeding systems. HI cows had an SCS of 1.97 ± 0.17, while LI cows had an SCS of 2.10 ± 0.16. However, SCS varied across lactation numbers, with lower values in primiparous cows (1.18 ± 0.13) compared to cows in their second (2.09 ± 0.12) and third or more lactations (2.20 ± 0.12). The low SCS values for both feeding systems indicate that in organic systems, it is possible to produce milk with low SCS and high quality through appropriate management, feeding, and environmental strategies.

Conclusão (obrigatório)

We concluded that feeding regimens and seasonal variations significantly impact milk composition in organic systems. Low-input (LI) cows, which receive a grass-based diet, tend to have higher fat production. Additionally, our findings suggest that the feeding system does not significantly influence somatic cell count (SCS), indicating the potential for low SCS in organic dairy milk production where the use of antibiotics is limited.

Referências bibliográficas (opcional)

EISERT, J. Environmental impact of organic milk production: The case of low- versus high-input at Gladbacherhof. 2019. Thesis (PhD) – Universität für Bodenkultur Wien, Vienna, 2019.

REYNOLDS, C.K., KRISTENSEN, N.B., & BEEVER, D.E. (2006). Fibre effects on dairy cow dry matter intake, feeding behaviour, and production: a review. Livestock Production Science, 99(1), 1-11.