An efficient headland-turning navigation system for a safflower picking robot

This study proposes a navigation system for the headland autonomous turning of a safflower picking robot. The proposed system includes binocular cameras, differential satellites, and inertial sensors. The method of extracting the headland boundary line combining the hue, saturation, and value-fixed threshold segmentation method and random sample consensus algorithm and planning the headland-turning trajectory of a robot based on the multiorder Bezier curve are used as control methods. In addition, a headland-turning tracking model of a safflower picking robot is designed, and a path-tracking control algorithm is developed. A field test verifies the performance of the designed headland-turning navigation system. The test results show that the accuracy of the judgment result regarding the existence of a headland is higher than 96%. In headland boundary detection, the angle deviation is less than 1.5˚, and the depth value error is less than 50 mm. The headland-turning path tracking test result shows that at a turning speed of 0.5 km/h, the average lateral deviation is 37 mm, and the turning time is 24.2 seconds. Compared to the 1 km/h, the turning speed of 0.5 km/h provides a better trajectory tracking effect, but the turning time is longer. The test results verify that this navigation system can accurately extract the headland boundary line and can successfully realise the headland-turning path tracking of a safflower picking robot. The results presented in this study can provide a useful reference for the autonomous navigation of a field robot

Detecting the Neuraminidase R294K Mutation in Avian Influenza A (H7N9) Virus Using Reverse Transcription Droplet Digital PCR Method

The R294K mutation in neuraminidase (NA) causes resistance to oseltamivir in the avian influenza virus H7N9. Reverse transcription droplet digital polymerase chain reaction (RT-dd PCR) is a novel technique for detecting single-nucleotide polymorphisms. This study aimed to develop an RT-dd PCR method for detecting the R294K mutation in H7N9. Primers and dual probes were designed using the H7N9 NA gene and the annealing temperature was optimized at 58.0 °C. The sensitivity of our RT-dd PCR method was not significantly different from that of RT-qPCR (p = 0.625), but it could specifically detect R294 and 294K in H7N9. Among 89 clinical samples, 2 showed the R294K mutation. These two strains were evaluated using a neuraminidase inhibition test, which revealed that their sensitivity to oseltamivir was greatly reduced. The sensitivity and specificity of RT-dd PCR were similar to those of RT-qPCR and its accuracy was comparable to that of NGS. The RT-dd PCR method had the advantages of absolute quantitation, eliminating the need for a calibration standard curve, and being simpler in both experimental operation and result interpretation than NGS. Therefore, this RT-dd PCR method can be used to quantitatively detect the R294K mutation in H7N9