Improving the estimation of rice above-ground biomass based on spatio-temporal UAV imagery and phenological stages.

Introduction: Unmanned aerial vehicles (UAVs) equipped with visible and multispectral cameras provide reliable and efficient methods for remote crop monitoring and above-ground biomass (AGB) estimation in rice fields. However, existing research predominantly focuses on AGB estimation based on canopy spectral features or by incorporating plant height (PH) as a parameter. Insufficient consideration has been given to the spatial structure and the phenological stages of rice in these studies. In this study, a novel method was introduced by fully considering the three-dimensional growth dynamics of rice, integrating both horizontal (canopy cover, CC) and vertical (PH) aspects of canopy development, and accounting for the growing days of rice. Methods: To investigate the synergistic effects of combining spectral, spatial and temporal parameters, both small-scale plot experiments and large-scale field testing were conducted in Jiangsu Province, China from 2021 to 2022. Twenty vegetation indices (VIs) were used as spectral features, PH and CC as spatial parameters, and days after transplanting (DAT) as a temporal parameter. AGB estimation models were built with five regression methods (MSR, ENet, PLSR, RF and SVR), using the derived data from six feature combinations (VIs, PH+CC, PH+CC+DAT, VIs+PH +CC, VIs+DAT, VIs+PH+CC+DAT). Results: The results showed a strong correlation between extracted and ground-measured PH (R2 = 0.89, RMSE=5.08 cm). Furthermore, VIs, PH and CC exhibit strong correlations with AGB during the mid-tillering to flowering stages. The optimal AGB estimation results during the mid-tillering to flowering stages on plot data were from the PLSR model with VIs and DAT as inputs (R 2 = 0.88, RMSE=1111kg/ha, NRMSE=9.76%), and with VIs, PH, CC, and DAT all as inputs (R 2 = 0.88, RMSE=1131 kg/ha, NRMSE=9.94%). For the field sampling data, the ENet model combined with different feature inputs had the best estimation results (%error=0.6%-13.5%), demonstrating excellent practical applicability. Discussion: Model evaluation and feature importance ranking demonstrated that augmenting VIs with temporal and spatial parameters significantly enhanced the AGB estimation accuracy. In summary, the fusion of spectral and spatio-temporal features enhanced the actual physical significance of the AGB estimation models and showed great potential for accurate rice AGB estimation during the main phenological stages.

Genomic insights into Cronobacter spp. recovered from food and human clinical cases in Zhejiang province, China (2008-2021).

AIMS: Cronobacter spp. are emerging food-borne pathogens capable of causing life-threatening illness via several distinct routes. Although endeavors to reduce the incidence of Cronobacter infections are implemented, potential risk of these microorganisms on food safety remains poorly understood. Here, we evaluated the genomic features of clinical Cronobacter and the possible food reservoirs of these infections. METHODS AND RESULTS: Whole-genome sequencing (WGS) data of all human clinical cases (n = 15) during 2008-2021 in Zhejiang were used and compared to sequenced Cronobacter genomes (n = 76) representing various food products. Cronobacter strains exhibited a high degree of genetic diversity by WGS-based subtyping. A variety of serotypes (n = 12) and sequence types (n = 36) were identified, including six novel STs (ST762-ST765, ST798, and ST803) first-time described in this study. Nine clinical clusters representing 12/15 (80%) patients match a potential food source. Genomic insights into virulence genes revealed species/hosts specificity signatures associated with autochthonous populations. Resistance to streptomycin, azithromycin, sulfanilamide isoxazole, cefoxitin, amoxicillin, ampicillin, and chloramphenicol, as well as multidrug resistance, was noted. WGS data can be used to predict resistance phenotypes in amoxicillin, ampicillin, and chloramphenicol, which were extensively used in clinical treatment. CONCLUSIONS: The wide dissemination of pathogenic potential and antibiotic-resistant strains in multiple food sources emphasized the importance of rigorous food safety policies to reduce Cronobacter contamination in China.

Genomic characterization of Salmonella enterica serovar Kentucky and London recovered from food and human salmonellosis in Zhejiang Province, China (2016-2021).

Increasing human salmonellosis caused by Salmonella enterica serovar Kentucky and London has raised serious concerns. To better understand possible health risks, insights were provided into specific genetic traits and antimicrobial resistance of 88 representative isolates from human and food sources in Zhejiang Province, China, during 2016-2021. Phylogenomic analysis revealed consistent clustering of isolates into the respective serovar or sequence types, and identified plausible interhost transmission via distinct routes. Each serovar exhibited remarkable diversity in host range and disease-causing potential by cgMLST analyses, and approximately half (48.6%, 17/35) of the food isolates were phylogenetically indistinguishable to those of clinical isolates in the same region. S. London and S. Kentucky harbored serovar-specific virulence genes contributing to their functions in pathogenesis. The overall resistance genotypes correlated with 97.7% sensitivity and 60.2% specificity to the identified phenotypes. Resistance to ciprofloxacin, cefazolin, tetracycline, ampicillin, azithromycin, chloramphenicol, as well as multidrug resistance, was common. High-level dual resistance to ciprofloxacin and cephalosporins in S. Kentucky ST198 isolates highlights evolving threats of antibiotic resistance. These findings underscored the necessity for the development of effective strategies to mitigate the risk of food contamination by Salmonella host-restricted serovars.

Prevalence and genetic characteristics of Cronobacter spp. from food and human clinical stool samples in Wenzhou, China 2008-2018.

Pathogenic Cronobacter species are responsible for life-threatening illness in neonates. A ten-year comprehensive survey was conducted to examine the population structure and antimicrobial resistant patterns of Cronobacter isolates from food (n = 78) and clinical (n = 12) sources in Wenzhou, China. A total of 90 (4.4%) isolates were recovered from 2051 collected samples. The occurrence of Cronobacter spp. was highest in spices with a rate of 22% (26/119), whereas the lowest contamination rate of 1% was found in powered infant and toddler formula (7/494), special medical infant formula (1/95) and human stool samples (12/1024). Cronobacter strains revealed a high degree of genetic diversity among the isolates tested. Pulsed-field gel electrophoresis (PFGE) distinguished 75 clonal groups, and the biggest cluster consisted of four strains. Multilocus sequence typing (MLST) method displayed 43 sequence types (STs), of which ST1, ST4, ST8, ST64, ST148 and ST201 were most frequently identified. Meanwhile, two new sequence types were discovered and added to the PubMLST international database. Resistance to ceftriaxone, cefotaxiv, amoxicillin, ampicillin, cefoxitin, tetracycline, streptomycin, azithromycin, chloramphenicol, as well as multidrug resistance, was noted. Taken together, this large-scale surveillance study highlights the wide dissemination and diverse molecular features of Cronobacter spp. in Wenzhou China.