Costa, E. J. X. | bioRxiv Science

bioRxiv2021

Effect of electrical hybrid-frequency water bath stunning on the spontaneous electroencephalogram (EEG) and electrocardiogram (ECG) of broilers

Concerns about animal welfare and meat quality have encouraged research on new methods for the stunning of broilers during animal slaughter. In this study, the electroencephalogram (EEG) and electrocardiogram (ECG) of broilers were acquired during stunning using an electrical hybrid instead of a single frequency. Considering a square-wave with a current of 220 mA and a frequency of 1100 Hz (duty-cycle 50%), the hybrid-frequency waveform is obtained generating pulses at 6600 Hertz in the pulse-width phase. Sixty broilers aged 42 days were randomly sampled; thirty were used for EEG measurement and thirty for ECG measurement. For EEG measurements, the birds scalps were anaesthetized, and EEG electrode needles were inserted on the subcutaneous part of the occipital scalp. For ECG, the non-invasive surface electrode was used. The electrodes were connected to a digital EEG/ECG system. The results showed that the hybrid-frequency waveform system generated epileptic forms in the birds EEGs. Therefore, a hybrid-frequency system may present better carcass quality results, while preserving the birds welfare, when compared with a single frequency system use.

neuroscience↗

bioRxiv2020

Bioelectrical pattern discrimination of Miconia plants by spectral analysis and machine learning

We have conducted an in loco investigation into the species Miconia albicans (SW.) Triana and Miconia chamissois Naudin (Melastomataceae), distributed in different phytophysiognomies of three Cerrado fragments in the State of Sao Paulo, Brazil, to characterize their oscillatory bioelectrical signals and to find out whether these signals have distinct spectral density. The experiments provided a sample bank of bioelectrical amplitudes, which were analyzed in the time and frequency domain. On the basis of the power spectral density (PSD) and machine learning techniques, analyses in the frequency domain suggested that each species has a characteristic biological pattern. Comparison between the oscillatory behavior of the species clearly showed that they have bioelectrical features, that collecting data is feasible, that Miconia display a bioelectrical pattern, and that environmental factors influence this pattern. From the point of view of experimental Botany, new questions and concepts must be formulated to advance understanding of the interactions between the communicative nature of plants and the environment. The results of this on-site technique represent a new methodology to acquire non-invasive information that might be associated with physiological, chemical, and ecological aspects of plants. HighlightIn loco characterization of the bioelectrical signals of two Miconia species in the time and frequency domain suggests that the species have distinct biological patterns.

plant biology↗