Figure 1 illustrates intricate patterns of variation observed in MY, FAT, and PROT across individual dairy cattle within a diverse Thai multibreed population. The depiction of these patterns provides valuable insights into lactation dynamics and offers points of comparison with other studies. Here, we delve into a detailed analysis and contextualization of these findings.
The MY pattern, as displayed in Fig. 1, aligns with the classical lactation trend observed in dairy cows. Following calving, MY exhibited a steady rise, reaching its peak on day 52, registering at 18.09 kg/day (SD = 4.91 kg/day). It's noteworthy that the peak MY in this study, while substantial, was comparatively lower than findings reported in Portugal Holstein (36.70 kg/day; Silvestre et al. 2009), Moroccan Holstein (28.20 kg/day; Boujenane and Elouaddi, 2021), and African Holstein (23.20 kg/day; Khalifa et al. 2018). However, the time taken to reach the MY peak (52 days) was notably shorter compared to Khalifa et al. (2018; 84.9 days), and Boujenane and Elouaddi (2021; 61 days), albeit longer than Silvestre et al. (2009; 47 days). These disparities can likely be attributed to breed variations, distinct management practices, and prevailing environmental factors across the studies.
A study conducted by Hamdi et al. (2021) discovered that elevated heat stress contributes to reduced milk yield and can also impact the continuity of milk production. Thailand, a country situated in Southeast Asia with a hot and humid climate (Temperature-Humidity Index [THI] ranged from 71.2 to 83.4; Sae-tiao et al. 2019), is located near the equator, which may result in higher heat index values compared to countries farther from the equator (Thai Meteorological Department, 2023). Consequently, this climatic condition could lead to lower milk yields and a reduction in days to peak during the lactation period compared to the cows rested in other countries especially in temperate regions.
Intriguingly, the variations observed in MY throughout the lactation period were mirrored by contrasting patterns in both FAT and PROT content. After calving, both FAT and PROT underwent a gradual decline, reaching their respective nadirs at day 72 (3.27%, SD = 0.74%) and day 47 (2.86%, SD = 0.36%) as illustrated in Fig. 1. Of note, the milk protein fraction reached its trough earlier and registered lower values than the milk fat fraction, consistent with the findings of Silvestre et al. (2009), who reported 70 days (3.60%) for milk fat and 65 days (3.10%) for milk protein. A parallel observation by Schutz et al. (1990) revealed a swift decrease in both fat and protein content, reaching their minimum at 50 days post-calving, followed by a gradual ascent until the culmination of lactation. The apogee for both fat and protein content materialized on day 297 (FAT: 4.08%; SD = 0.96% and PROT: 3.43%; SD = 0.47%; Fig. 1), signifying their synchronous attainment of peak levels. These outcomes underscore the dynamic nature of fat and protein content over the course of lactation, reinforcing earlier research aligning with analogous patterns of variation.
The elucidation of these multifaceted patterns not only contributes to our understanding of lactation dynamics but also offers a comparative perspective with prior investigations, facilitating a nuanced interpretation of the factors at play in the context of breed diversity, management strategies, and environmental influences.
Figure 2 presents a comprehensive depiction of the variations observed in the FPR among dairy cattle in Thailand, shedding light on the prevalent risks of metabolic diseases within the population. The insights gleaned from this analysis provide crucial implications for dairy herd management and welfare, which we delve into below.
Strikingly, the findings indicated that a substantial proportion of dairy herds, specifically 56.34%, were at risk of experiencing both acidosis and ketosis, underscoring the significance of metabolic disease management within these herds. Further dissection of the FPR data reveals that milking cows faced a 46.48% risk of acidosis, a 9.86% risk of ketosis, and, reassuringly, a 43.66% likelihood of maintaining FPR within the normal range.
When considering the risk of metabolic diseases across distinct phases of the lactation period post-calving, i.e., the early (100 days), middle (200 days), and late (300 days) stages, noteworthy trends emerge. The risk of acidosis was observed to be 47.65%, 46.87%, and 44.50% in these respective stages. For ketosis, the risks were 10.64%, 9.43%, and 9.44%, while the normal range accounted for 41.71%, 43.70%, and 46.07%, mirroring the FPR distributions.
Especially, while the risks may vary marginally across these lactation stages, the early lactation phase stands out as the period most susceptible to both acidosis and ketosis. This aligns with previous research by Gürtler and Schweigert (2005), Esposito et al. (2014), and Tatone et al. (2016), which establishes that ketosis predominantly manifests in the initial stages of lactation, typically within the first 6–8 weeks. This vulnerability is attributed to the increased energy demands for milk production during early lactation, which, if not met through meticulous dietary management, can precipitate ketosis. Moreover, this is consistent with Suree et al. (2021) previous research, which studied the risk of acidosis, normal, and ketosis in bulk tank milk of dairy farms in Thailand based on the FPR. It was found that the majority of milking herds (81.94%) have a chance of both acidosis and ketosis.
The consistent risk levels observed throughout the lactation stages suggested that the feeding regimens for dairy cows in this population remained relatively uniform. This implied that farmers might not have tailored feed portions to precisely meet the changing energy requirements of cows during different lactation phases. Consequently, it becomes imperative to foster knowledge dissemination and enhance farmers' understanding of optimized feeding practices (Yeamkong et al. 2010). Such efforts hold the potential to enhance milk production efficiency, mitigate the risks associated with acidosis and ketosis, and concurrently curtail production costs and the expenses incurred in maintaining milk cows (Lock and Van Amburg 2012; Vlcek et al. 2016). Furthermore, it is worth considering the importance of regularly following up and monitoring the FPR profile in dairy cows, particularly during the early stages of lactation. This practice can serve as a cost-effective tool to identify cows experiencing NEB. Consequently, farmers can make informed on-farm decisions aimed at preventing unfavorable consequences for the cows' health and productivity.
These findings underscore the pressing need for targeted interventions and educational initiatives within the dairy farming community. By equipping farmers with the requisite knowledge and strategies needed for tailored nutritional management across lactation phases, the industry can support both animal welfare and economic sustainability.
Figure 3 provides an insightful overview of the Pearson correlations between key variables (i.e., MY, FAT, PROT, and FPR), unraveling significant associations that have implications for dairy herd management and productivity. Especially, MY exhibited intriguing relationships with the other variables, displaying negative correlations (P < 0.05) with FAT (r = -0.16 to -0.09), PROT (r = -0.16 to -0.06), and FPR (r = -0.12 to -0.02). This suggests that higher milk production tends to coincide with lower fat content, lower protein content, and a reduced FPR. The mentioned associations underline the complex interplay between milk quantity and its compositional attributes.
Comparisons with previous studies, such as Bondan et al. (2018), reveal both congruencies and disparities in the observed correlations. Bondan et al. (2018) reported negative correlations between MY and FAT, as well as between MY and PROT (r = -0.226 and − 0.396, respectively), which aligns with the present findings. However, the positive correlation they identified between MY and FPR (r = 0.012) diverges from our results.
When FAT is examined separately, it becomes evident that it shares a positive correlation with both PROT and FPR, indicating that higher FAT content is associated (P < 0.01) with higher protein levels and an increased FPR. However, a counterintuitive negative correlation was observed between FAT and MY (P < 0.01). This indicated the balance of energy that cows received in the past. If FPR was higher than 1.5, cows could have lacked energy and might have entered ketosis (Gjoko et al. 2020; Poljak et al. 2022) due to inappropriate feed intake proportions, with the feed having low concentration and energy levels but possibly containing high-fiber feeds, leading to an increase in fat content. (Huhtanen et al. 2012). In contrast, with a lower FPR, cattle might have been fed starchy feeds with high concentration levels but a low-fiber diet, resulting in a reduction in fat content. Several studies indicated that an increase in dietary concentration levels was associated with a decrease in FAT content (Alatas et al. 2015; Dewanckele et al. 2020).
Protein content increased due to higher starch intake (Walker et al. 2004; Huhtanen et al. 2012), which was inversely related to FPR. The results of the study have shown that protein content was most strongly associated with FPR during the early stages of lactation. This may suggest that cows had high energy needs at the beginning and, therefore, required feed with a high concentration and energy level to replenish the energy lost after calving. Furthermore, a negative correlation was uncovered between FPR and MY (P < 0.05), highlighting the interdependence between FPR and milk yield.
This paradoxical relationship necessitates a nuanced understanding of the intricate dynamics governing milk composition. And this research can also indicate the basic health of individual milking cows. But it may not be a clear indicator of health. This may require other methods of diagnosis and observation as well. However, the study will help put the information already available to greater benefit.
The contrasting correlations between fat and protein content in different lactation stages suggest that milk composition dynamics are subject to temporal variation. Specifically, the relationship between FAT and FPR, as well as PROT and FPR, exhibited strong correlations early in lactation, implying that higher FPR might correspond to reduced milk protein levels. This finding is consistent with Negussie et al. (2013), who reported that ketosis led to reduced milk yield and milk protein, especially when animals were fed a high-quality roughage diet.
In conclusion, these correlation patterns underscore the multifaceted nature of milk composition dynamics and its intricate relationship with milk yield. The observed associations highlight the need for tailored nutritional strategies and health management protocols, emphasizing the potential impact of FPR on milk protein content. Further research is warranted to elucidate the underlying mechanisms driving these correlations and their practical implications for dairy cattle management.