This study was conducted to investigate the effects of catechins on reproductive performance, antioxidative capacity and immune function of gestating sows. A total of 60 cross-bred (Landrace × Large White) multiparious sows were blocked by body weight, parity and backfact and randomly allocated to 1 of 5 treatments: 0, 100, 200, 300, or 400 mg/kg catechins. Dietary treatments were imposed from mating to d 40 of gestation of sows. At farrowing, litter total born, born alive, dead, and normal-(healthy piglets, ≥0.85 kg) and low-birth weight piglets (<0.85 kg) were recorded. Within 3.00 ± 0.50 days after farrowing litter size was standardized to 8.00 ± 1.50 piglets within treatment. The piglets were weighed at birth (d 1) and weaning (d 28). Sows serum samples were obtained from blood samples collected on d 40 of gestation for analyses of glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), hydrogen peroxide (H2O2), nitric oxide synthetase (NOS) and nitrogen monoxide (NO). Our results showed that supplementation of catechins at levels of 200 or 300 mg/kg led to improvements in litter born alive (P < 0.01) and piglet born healthy (P < 0.01) and a decrease in stillborn (P < 0.05) at farrowing when compared with the control. In comparison with the control, catechins at any supplemental levels all enhanced the serum SOD (P < 0.05) and CAT (P < 0.01) activities of sows at farrowing but no obvious differences in the serum GSH-Px and NOS activities were observed in this trial (P > 0.05). Sows received 200 mg catechin per kg diets showed a reduction (P < 0.05) of the serum MDA level at farrowing compared with all other treatments. Sows received all the levels of catechin showed a reduction (P < 0.05) of serum H2O2 level compared with sows received the control diet on both d 40 of gestation and farrowing. Our results demonstrated that the catechins may be a potential antioxidant to increase the reproductive performance and antioxidative capacity of sows when it was added into diets during the early gestation.
3D convolutional neural networks (CNNs) have been demonstrated to be a powerful tool in hyperspectral images (HSIs) classification. However, using the conventional 3D CNNs to extract the spectral–spatial feature for HSIs results in too many parameters as HSIs have plenty of spatial redundancy. To address this issue, in this paper, we first design multiscale convolution to extract the contextual feature of different scales for HSIs and then propose to employ the octave 3D CNN which factorizes the mixed feature maps by their frequency to replace the normal 3D CNN in order to reduce the spatial redundancy and enlarge the receptive field. To further explore the discriminative features, a channel attention module and a spatial attention module are adopted to optimize the feature maps and improve the classification performance. The experiments on four hyperspectral image data sets demonstrate that the proposed method outperforms other state-of-the-art deep learning methods.
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