Zelin Li

Mr. Zelin Li

Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Dookie Campus, Victoria, 3647, Australia.
orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 October 2022 in Antioxidants
Verified
Journal Article
Open access
PDF file
YMYi Ma
Yi Ma
MEMawada Elmhadi
Mawada Elmhadi
CWChao Wang
Chao Wang
ZLZelin Li
Zelin Li
HZHao Zhang
Hao Zhang
HWHongrong Wang
Hongrong Wang
Studies have shown that exogenous thiamine (THI) supplementation can alleviate inflammation and promote rumen epithelial development in goats and cows. This research aimed to evaluate the effect of THI supplementation on LPS-induced inflammation and energy metabolic dysregulation in RECs of goats. Cells were stimulated with either 5 μg/mL THI for 18 h (THI group) or with 5 μg/mL LPS for 6 h (LPS group). The CON group was stimulated with DMEM/F-12 medium without THI for 18 h. The LPTH group was pretreated with THI for 18 h, followed by LPS stimulation for 6 h. THI supplementation decreased the ROS content (p < 0.05), as well as the ratios of phosphorylated (p)-p65 to p65 (p < 0.05) and p-AMPKα to AMPKα (p < 0.05). Interestingly, when the p38 gene was overexpressed in the LPTH group, the ratio of p-p65 to p65 and p-AMPKα to AMPKα proteins significantly increased, and ATP content decreased (p < 0.05). Our results suggest that THI possesses anti-inflammatory and metabolic-modulatory effects in RECs. The mechanism is largely related to the suppression of the NF-κB/p38 MAPK/AMPK signaling pathway. Additionally, we also revealed that THI supplementation can inhibit LPS-induced oxidative damage and apoptosis to protect mitochondrial function in RECs.

10 February 2021 in Dairy
Verified
Journal Article
Open access
PDF file
ZLZelin Li
Zelin Li
LCLong Cheng
Long Cheng
Brendan CullenBrendan Cullen
Brendan Cullen
Precision livestock farming (PLF) supports the development of sustainable dairy production. The sensors used in PLF provide valuable information for farm management, but they must be validated to ensure the accuracy. The goal of this study was to validate and use the RumiWatch sensor (RWS; Itin+Hoch GmbH, Liestal, Switzerland) to differentiate prehension bites, eating chews, mastication chews and rumination chews in pressure-based system. Twenty cows were used for 14 days to provide a validation dataset. The concordance correlation coefficient (CCC) was adopted to test the concordance between the RumiWatch sensor and video observation. The RumiWatch sensor performed well in counting prehension bites (CCC = 0.98), eating chews (CCC = 0.95) and rumination chews (CCC = 0.96), while it showed an acceptable concordance in counting mastication chews with video observation (CCC = 0.77). Moderate correlations were found between eating chews and daily milk production: daily milk production (kg/day) = 0.001151 × eating chews (chews/day) − 11.73 (R2 = 0.31; standard error (SE) = 8.88; p = 0.011), and between mastication chews and daily milk production: daily milk production (kg/day) = 0.001935 × mastication chews (chews/day) + 2.103 (R2 = 0.34; SE = 8.70; p = 0.007). Overall, the results indicated that the RumiWatch sensor can be confidently used to quantify and differentiate prehension bites, eating chews and rumination chews; in addition, ingestive behaviours explained up to 34% of the variation in milk production.

27 June 2025 in Grass and Forage Science
Verified
Journal Article
Open access
ZLZelin Li
Zelin Li
GZG. Zhao
G. Zhao
STSaranika Talukder
Saranika Talukder
FDF. Dunshea
F. Dunshea
SCS. Chauhan
S. Chauhan
LCL. Cheng
L. Cheng
Roughage constitutes a fundamental component of dairy cow diets; it promotes rumen health and supports optimal animal productivity. This study applied an ANKOM gas production system to assess the in vitro fermentation characteristics of seven widely used dairy roughages (barley hay, corn silage, lucerne hay, oaten hay, ryegrass hay, timothy hay and wheaten hay) classified into relatively high and low nutritive value groups. Roughage samples representing high and low nutritive values were selected based on the upper and lower quartiles of the feed quality database. The results showed that high‐nutritive value oaten hay exhibited higher dry matter (DM) digestibility (0.50 vs. 0.24–0.43 g/g DM, p < 0.05), total gas production (87.5 vs. 15.3–81.0 mL/g DM) and total volatile fatty acid (63.2 vs. 39.3–62.5 mM) than other roughages. High‐nutritive value barley hay and oaten hay both exhibited higher methane production (7.58 and 7.77 mL/g DM, respectively) compared to other roughages (0.44–4.76 mL/g DM). Similarly, high‐nutritive value barley hay (40.23 mg/100 mL) and lucerne hay (40.76 mg/100 mL) exhibited higher ammonia nitrogen (12.16–31.99 mg/mL) than other roughages. High‐nutritive value oaten and barley hay promoted superior fermentation performance but also led to greater methane emissions, while barley and lucerne hay increased nitrogen release. These results underscore the need to balance productivity with environmental impacts when selecting roughages for dairy systems.

9 October 2024 in Animal Feed Science and Technology
Verified
Journal Article
Closed access
YMYi Ma
Yi Ma
PYPeng Yang
Peng Yang
PLPengfei Li
Pengfei Li
MEMabrouk Elsabagh
Mabrouk Elsabagh
LCLong Cheng
Long Cheng
MXMengsi Xu
Mengsi Xu

29 January 2023 in Dairy
Verified
Journal Article
Open access
PDF file
Brendan CullenBrendan Cullen
Brendan Cullen
ZLZelin Li
Zelin Li
STSaranika Talukder
Saranika Talukder
LCLong Cheng
Long Cheng
EJEllen Jongman
Ellen Jongman
The monitoring and measurement of animal behaviour may be valuable for improving animal production and welfare. This study was designed to develop thresholds to predict the grazing, standing, walking, and lying behaviour of dairy cows from motion sensor (IceTag) output. The experiment included 29 lactating cows grazed in a pasture-based dairy production system with voluntary cow movement in northern Victoria, Australia. Sensors recorded motion data at 1 min intervals. A total of 5818 min of cow observations were used. Two approaches were developed using (1) the IceTag lying index and steps only and (2) the IceTag lying index, steps, and motion index for each behaviour. Grazing behaviour was best predicted by the second approach, which had a sensitivity of 92% and specificity of 60%. The thresholds were then used to predict cow behaviour during two periods. On average, across both time periods, cows spent 38% of the day grazing, 38% lying, 19% standing, and 5% walking. Predicted individual cow grazing time was positively correlated with both milk production and milking frequency. The thresholds developed were effective at predicting cow behaviours and can be applied to measure behaviour in pasture-based dairy production.

21 January 2021 in Grassland Science
Verified
Journal Article
Closed access
PDF file
RZRongzhen Zhong
Rongzhen Zhong
LCLong Cheng
Long Cheng
YFYi Fang
Yi Fang
ZLZelin Li
Zelin Li
VLVida Lamptey
Vida Lamptey
DZDaowei Zhou
Daowei Zhou