Comparative effects of various dietary selenium sources on growth performance, meat quality, essential trace elements content, and antioxidant capacity in broilers.

This study aimed to compare the effects of various dietary selenium (Se) sources (0.5 mg/kg) on performance, meat quality, and antioxidant capacity in broilers as well as essential trace elements concentrations in their blood and tissues. A total of 360 one-day-old male yellow-feathered chickens (37.00 ± 0.17 g) were randomly allocated to 5 diet treatments: the basal diet (CON) and 4 diets supplemented with sodium selenite (SS), selenomethionine (SM), selenium-enriched yeast (SY), and nano-selenium (NS) for 56 d, respectively, with 6 replicates per treatment and 12 chickens per replicate. Dietary Se supplementation did not affect growth performance and carcass characteristics in broilers (P > 0.05). Supplemental SM enhanced the redness in the pectoral muscle compared to CON and NS (P < 0.05). Supplementation of SY and NS improved the concentrations of Se, copper, manganese, and zinc in the serum (P < 0.05). Supplemental SS also elevated the zinc content in the serum (P < 0.05). Broilers fed the SY diet showed increased Se content in the liver and pectoral muscle compared to those fed CON, SM, and NS diets (P < 0.05). Also, SY improved the pectoral muscle Se concentration compared to SS (P < 0.05). Besides, dietary Se supplementation increased the Se content in the thigh muscle (P < 0.05), with SY showing highest Se deposition. Dietary supplementation with SS, SM, and NS improved the activities of total superoxide dismutase and total antioxidant capacity (T-AOC) in the serum (P < 0.05). Supplemental SY also elevated the T-AOC in the serum (P < 0.05). Additionally, SS and SM enhanced the T-AOC in the liver (P < 0.05). In conclusion, supplemental SM affected meat color. Supplementing diets with various Se sources increased antioxidant capacity and Se content in the thigh muscle of broilers, with SY showing a more pronounced deposition efficiency. Besides, diets supplemented with different Se sources had variable effects on the concentrations of essential trace elements in the serum and tissues of broilers.

A Dual Robust Strategy for Removing Outliers in Multi-Beam Sounding to Improve Seabed Terrain Quality Estimation.

During the process of seabed terrain exploration using a multi-beam echo system, it is inevitable to obtain a sounding set containing anomalous points. Conventional methods for eliminating outliers are unable to reduce the disruption caused by outliers over the whole dataset. Furthermore, incomplete consideration is given to the terrain complexity, error magnitude, and outlier distribution. In order to achieve both a high-precision terrain quality estimate and quick detection of depth anomalies, this study suggests a dual robust technique. Firstly, a robust polyhedral function is utilized to solve anomaly detection for large errors. Secondly, the robust kriging algorithm is used for refined outlier removal. Ultimately, the process of dual detection and anomaly removal is achieved. The experimental results demonstrate that DRS technology has the most favorable mean square error and error fluctuation range in the test set, with values of 0.8321 and [-2.0582, 1.9209], respectively, when compared to RPF, WT, GF, and WLS-SVM schemes. Furthermore, DRS is able to adjust to various terrain complexities, discrete distribution features, and cluster outlier detection, as shown by objective indicators and visual outcome maps, guaranteeing a high-quality seabed terrain estimate.

Black Soldier Fly (Hermetia illucens) Larvae Meal Modulates Intestinal Morphology and Microbiota in Xuefeng Black-Bone Chickens.

The addition of Hermetia illucens larvae meal (HILM) to the feed could contribute to particular antimicrobial and intestinal health in animal husbandry. This study was conducted to investigate the effects of HILM on intestinal morphology and microbial diversity in different intestinal segments of Xuefeng black-bone chickens. All of 432 birds (45 weeks old) were randomly assigned to four equal groups with six replicates and 18 hens in each replicate: (A) basal diet, (B) basal diet with 1% HILM, (C) basal diet with 3% HILM, and (D) basal diet with 5% HILM. The results showed that, compared with the basal diet group, the HILM supplement significantly increased the abundance-based coverage estimator (ACE) and Chao index in cecum (p < 0.05). Diet with 1% HILM significantly increased the villus height (VH) of the duodenum (p < 0.05) and cecum microbial diversity as represented by the Simpson index (p < 0.05). In particular, 1% HILM displayed a markedly increase in the genus unclassified Bacteroidales (cecum, p < 0.05). A basal diet with 3% HILM markedly increased the beneficial genus Romboutsia (jejunum, p < 0.05). Also, principal component analysis (PCA) cluster analysis showed that 3% of HILM was more individual than other groups (p < 0.05). However, 5% HILM decreased the VH and the ratio of villus height to crypt depth (VH/CD) of the jejunum and increased beneficial bacteria such as Staphylococcus (p < 0.05), which was regarded as pathogenetic genera. In conclusion, we found that HILM improved intestinal morphology and increased microbiological diversity and species abundance. Together, dietary supplementation of 1 or 3% HILM might benefit the intestinal morphology and intestinal microbiota of Xuefeng black-bone chicken. However, the addition of 5% HILM could decrease VH and the ratio of VH/CD of the jejunum and increased pathogenetic genera. HILM was an excellent protein substitute for Xuefeng black-bone chickens, which could meet the nutritional requirements under the condition of less feed. These results provide information for HILM meal as an alternative source of soybean meal in Xuefeng black-bone chickens' feed.

Coastal Land Cover Classification of High-Resolution Remote Sensing Images Using Attention-Driven Context Encoding Network.

Low inter-class variance and complex spatial details exist in ground objects of the coastal zone, which leads to a challenging task for coastal land cover classification (CLCC) from high-resolution remote sensing images. Recently, fully convolutional neural networks have been widely used in CLCC. However, the inherent structure of the convolutional operator limits the receptive field, resulting in capturing the local context. Additionally, complex decoders bring additional information redundancy and computational burden. Therefore, this paper proposes a novel attention-driven context encoding network to solve these problems. Among them, lightweight global feature attention modules are employed to aggregate multi-scale spatial details in the decoding stage. Meanwhile, position and channel attention modules with long-range dependencies are embedded to enhance feature representations of specific categories by capturing the multi-dimensional global context. Additionally, multiple objective functions are introduced to supervise and optimize feature information at specific scales. We apply the proposed method in CLCC tasks of two study areas and compare it with other state-of-the-art approaches. Experimental results indicate that the proposed method achieves the optimal performances in encoding long-range context and recognizing spatial details and obtains the optimum representations in evaluation indexes.