An efficient approach to detect and track winter flush growth of litchi tree based on UAV remote sensing and semantic segmentation.

The immature winter flush affects the flower bud differentiation, flowering and fruit of litchi, and then seriously reduces the yield of litchi. However, at present, the area estimation and growth process monitoring of winter flush still rely on manual judgment and operation, so it is impossible to accurately and effectively control flush. An efficient approach is proposed in this paper to detect the litchi flush from the unmanned aerial vehicle (UAV) remoting images of litchi crown and track winter flush growth of litchi tree. The proposed model is constructed based on U-Net network, of which the encoder is replaced by MobeilNetV3 backbone network to reduce model parameters and computation. Moreover, Convolutional Block Attention Module (CBAM) is integrated and convolutional layer is added to enhance feature extraction ability, and transfer learning is adopted to solve the problem of small data volume. As a result, the Mean Pixel Accuracy (MPA) and Mean Intersection over Union (MIoU) on the flush dataset are increased from 90.95% and 83.3% to 93.4% and 85%, respectively. Moreover, the size of the proposed model is reduced by 15% from the original model. In addition, the segmentation model is applied to the tracking of winter flushes on the canopy of litchi trees and investigating the two growth processes of litchi flushes (late-autumn shoots growing into flushes and flushes growing into mature leaves). It is revealed that the growth processes of flushes in a particular branch region can be quantitatively analysed based on the UAV images and the proposed semantic segmentation model. The results also demonstrate that a sudden drop in temperature can promote the rapid transformation of late-autumn shoots into flushes. The method proposed in this paper provide a new technique for accurate management of litchi flush and a possibility for the area estimation and growth process monitoring of winter flush, which can assist in the control operation and yield prediction of litchi orchards.

Synergistically Active Piezoelectrical H2 O2 Production Composite Film Achieved from a Catalytically Inert PVDF-HFP Matrix and SiO2 Fillers.

Local and decentralized H2 O2 production via a piezoelectrical process promises smart biological utilization as well as environmental benefits. However, stable, bio/environmentally safe, and easily applied H2 O2 generation materials are still lacking. Here, we report a novel flexible H2 O2 generation polymeric film composed of catalytically inert PVDF-HFP (Poly(vinylidene fluoride-co-hexafluoropropylene)) matrix and SiO2 nanoparticle fillers. The film is bio-/environmentally benign at resting states, but effectively produces H2 O2 upon ultrasonic motivation at a production rate of 492 µmol g SiO 2 - 1 in one hour. Experimental and simulation methods in combination indicate that the effective H2 O2 generation capabilities stem from the synergistic existence of piezoelectrical fields and the air-liquid-solid three-phase regions around the porous film. The chemical conversions are motivated by the adsorbed charges. The silicon hydroxyl groups properly stabilize the *OOH intermediate and facilitate the chemical conversions of 2e- ORR of ambient O2 . We expect the report to inspire H2 O2 piezoelectrical generation materials and promote the novel production strategies of H2 O2 as well as piezoelectrical functional materials.