Elieder Romanzini

Dr. Elieder Romanzini

São Paulo State University - UNESP
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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20 May 2019 in Scientific Reports
Verified
Journal Article
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LDLutti M. Delevatti
Lutti M. Delevatti
Abmael CardosoAbmael Cardoso
Abmael Cardoso
RBRondineli Pavezzi Barbero
Rondineli Pavezzi Barbero
RLRhaony G. Leite
Rhaony G. Leite
Elieder RomanziniElieder Romanzini
Elieder Romanzini
Ricardo Andrade ReisRicardo Andrade Reis
Ricardo Andrade Reis
A three-year-long field experiment was conducted in a continuous grazing system with a variable stocking rate to evaluate effects of increasing nitrogen levels in Marandu grass (Brachiaria brizantha Hochst ex A. Rich Stapf “marandu”) on herbage mass, forage accumulation rate (FAR), forage quality, stocking rate (SR), average daily gain (ADG), gain per hectare (GPH), and gain per kg of applied N. The experimental design was completely randomized with four treatments (control without application of N, and 90, 180, and 270 kg N ha−1 year−1) and three replicates (paddocks per treatment); nitrogen was applied in the form of urea. Herbage mass, crude protein (CP), FAR, SR, GPH, and the nitrogen nutrition index increased with increasing nitrogen level (P < 0.05), whereas the neutral detergent fibre (NDF), acid detergent fibre, and nitrogen usage efficiency decreased with increasing nitrogen level (P < 0.01). Crude protein was higher than 12% and NDF lower than 60% in all treatments. Nitrogen application rate affected ADG (P < 0.05) but did not fit any equation. The highest ADG was 90 kg N ha−1 year−1 (985 g animal−1 day−1). Increasing the nitrogen level is a promising way to improve Marandu grass production, nutritive value, and animal production.

18 August 2020 in Sustainability
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Journal Article
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Abmael CardosoAbmael Cardoso
Abmael Cardoso
RBRondineli Pavezzi Barbero
Rondineli Pavezzi Barbero
Elieder RomanziniElieder Romanzini
Elieder Romanzini
RTRonyatta Weich Teobaldo
Ronyatta Weich Teobaldo
FOFernando Ongaratto
Fernando Ongaratto
Ricardo Andrade ReisRicardo Andrade Reis
Ricardo Andrade Reis
Intensification of tropical grassland can be a strategy to increase beef production, but methods for achieving this should maintain or reduce its environmental impact and should not compromise future food-producing capacity. The objective of this review was to discuss the aspects of grassland management, animal supplementation, the environment, and the socioeconomics of grassland intensification. Reducing environmental impact in the form of, for example, greenhouse gas (GHG) emissions is particularly important in Brazil, which is the second-largest beef producer in the world. Most Brazilian pastures, however, are degraded, representing a considerable opportunity for the mitigation and increase of beef-cattle production, and consequently increasing global protein supply. Moreover, in Brazil, forage production is necessary for seasonal feeding strategies that maintain animal performance during periods of forage scarcity. There are many options to achieve this objective that can be adopted alone or in association. These options include improving grassland management, pasture fertilization, and animal supplementation. Improving grazing management has the potential to mitigate GHG emissions through the reduction of the intensity of CO2 emissions, as well as the preservation of natural areas by reducing the need for expanding pastureland. Limitations to farmers adopting intensification strategies include cultural aspects and the lack of financial resources and technical assistance.

1 January 2019 in Animal Feed Science and Technology
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Journal Article
Closed access
LDLutti Maneck Delevatti
Lutti Maneck Delevatti
Elieder RomanziniElieder Romanzini
Elieder Romanzini
JKJefferson Fabiano Werner Koscheck
Jefferson Fabiano Werner Koscheck
TATiago Luis da Ross de Araujo
Tiago Luis da Ross de Araujo
DRDiego Monteira Renesto
Diego Monteira Renesto
Ricardo Andrade ReisRicardo Andrade Reis
Ricardo Andrade Reis

24 March 2020 in Animal Production Science
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Journal Article
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JKJ. F. W. Koscheck
J. F. W. Koscheck
Elieder RomanziniElieder Romanzini
Elieder Romanzini
RBR. P. Barbero
R. P. Barbero
LDL. M. Delevatti
L. M. Delevatti
AFA. C. Ferrari
A. C. Ferrari
Ricardo Andrade ReisRicardo Andrade Reis
Ricardo Andrade Reis
Context: Yields from Brazilian beef-production systems do not always match the expected potential of a forage-based beef-production system. This efficiency is dependent on adjustments of grazing intensity and supplement utilisation to achieve higher bodyweight gain and lower methane emission. Therefore, more studies are necessary to evaluate the association between pasture management and supplement doses. Aims: The aim of the present study was to determine nutrient intake, nutrient digestibility, animal performance, carcass characteristics and enteric methane emissions of young Nellore bulls grazing Urochloa brizantha cv. Marandu pastures. Methods: One hundred and forty-eight yearling bulls (230 ± 17 kg) were randomly assigned to a grazing-by-supplementation strategy that was designed to allocate three different sward heights with differing levels of supplementation during the wet season. Treatment combinations were (1) low sward height with high supplementation (LH-HS, 15-cm sward height and supplementation at 0.6% of bodyweight (BW)); (2) low height with moderate supplementation (LH-MS, 15 cm and 0.3% BW); (3) moderate height with moderate supplementation (MH-MS, 25 cm and 0.3% BW); (4) moderate height with low supplementation (MH-LS, 25 cm and 0.1% BW); (5) high height with low supplementation (HH-LS, 35 cm and 0.1% BW); and (6) high height with no supplementation (HH-WS, 35 cm). Key results: Bulls in the HH groups had a greater herbage intake than did those in the LH groups (P < 0.01). Bulls in the LH-HS treatment resulted in a greater (P < 0.01) carcass average daily gain than that obtained with LH-MS, MH-LS or HH-WS treatment. Higher stocking rate with the LH treatment resulted in greater gains per hectare in terms of both BW and carcass (P < 0.01). Carcass yield was greater for bulls maintained with the LH-HS treatment (54.3% BW). Higher enteric methane emissions were observed from bulls under the HH treatments (P < 0.01). Conclusions: Comparing carcass gains per hectare and low methane emissions, the present study indicated that pasture management towards a low sward height combined with 0.3% or 0.6% BW supplementation can result in a greater nutrient utilisation efficiency of bulls. Implications: Results provided information to obtain better gains per animals and area, also decreasing methane emission of beef cattle production system.

1 January 2020 in Journal of Applied Animal Research
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Journal Article
Open access
RBRondineli Pavezzi Barbero
Rondineli Pavezzi Barbero
EMEuclides Braga Malheiros
Euclides Braga Malheiros
NANatalia María Aguilar
Natalia María Aguilar
Elieder RomanziniElieder Romanzini
Elieder Romanzini
AFAdriana Cristina Ferrari
Adriana Cristina Ferrari
Ricardo Andrade ReisRicardo Andrade Reis
Ricardo Andrade Reis
To evaluate the foraging behaviour of yearling bulls grazing on Marandu grass, we conducted two experiments. In the first experiment (Exp. 1), three grazing heights of 15, 25, and 35 cm were evaluated, with bulls receiving 0.3% of body weight (BW) of supplement (161 g kg–1 crude protein (CP) and 20.1 MJ kg–1 gross energy (GE)); in the second experiment (Exp. 2), supplementation levels were decreased as grazing height increased: (1) low height (15 cm) and high supplementation (0.6% BW: 142 g kg–1 CP and 18.9 MJ kg–1 GE (LH-HS)); (2) moderate height (25 cm) and moderate supplementation (0.3% BW: 161 g kg–1 CP and 20.1 MJ kg–1 GE (MH-MS)) or (3) high height (35 cm) without supplementation (HH-WS). Ingestive behaviour was evaluated by direct visual observations, and intake using markers. It was used 9 paddocks each experiment. The experimental design was completely randomized, analysing effects by polynomial orthogonal contrasts (Exp. 1) and Tukey test (Exp. 2). In Exp. 1, a linear decreasing response to daily grazing time (P < 0.01) was observed, whereas a linear increasing response to herbage intake (P < 0.01) was observed with increased grazing height. In Exp. 2, LH-HS bulls had lower herbage intake (P < 0.01) than their counterparts. Bulls from both experiments showed increased grazing activity after 12 PM (P < 0.05). The herbage intake substitution effect of supplements can be explored as a production strategy, as the adjustment of supplementation levels can promote high dry matter intake as well as performance in beef cattle, in conditions of low grazing height or low forage allowance, even with a high stocking rate.

2 December 2021 in Animals
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Journal Article
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RWRafael Nakamura Watanabe
Rafael Nakamura Watanabe
PBPriscila A. Bernardes
Priscila A. Bernardes
Elieder RomanziniElieder Romanzini
Elieder Romanzini
LBLarissa Braga
Larissa Braga
TBThaís R. Brito
Thaís R. Brito
DMDanisio Munari
Danisio Munari
Knowledge of animal behavior can be indicative of the well-being, health, productivity, and reproduction of animals. The use of accelerometers to classify and predict animal behavior can be a tool for continuous animal monitoring. Therefore, the aim of this study was to provide strategies for predicting more and less frequent beef cattle grazing behaviors. The behavior activities observed were grazing, ruminating, idle, water consumption frequency (WCF), feeding (supplementation) and walking. Three Machine Learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) and two resample methods: under and over-sampling, were tested. Overall accuracy was higher for RF models trained with the over-sampled dataset. The greatest sensitivity (0.808) for the less frequent behavior (WCF) was observed in the RF algorithm trained with the under-sampled data. The SVM models only performed efficiently when classifying the most frequent behavior (idle). The greatest predictor in the NBC algorithm was for ruminating behavior, with the over-sampled training dataset. The results showed that the behaviors of the studied animals were classified with high accuracy and specificity when the RF algorithm trained with the resampling methods was used. Resampling training datasets is a strategy to be considered, especially when less frequent behaviors are of interest.