Sorbent-excluding sample preparation method for GC-MS pesticide analysis in apple peel

Wearable Sensor: An Emerging Data Collection Tool for Plant Phenotyping

The advancement of plant phenomics by using optical imaging-based phenotyping techniques has markedly improved breeding and crop management. However, there remains a challenge in increasing the spatial resolution and accuracy due to their noncontact measurement mode. Wearable sensors, an emerging data collection tool, present a promising solution to address these challenges. By using a contact measurement mode, wearable sensors enable in-situ monitoring of plant phenotypes and their surrounding environments. Although a few pioneering works have been reported in monitoring plant growth and microclimate, the utilization of wearable sensors in plant phenotyping has yet reach its full potential. This review aims to systematically examine the progress of wearable sensors in monitoring plant phenotypes and the environment from an interdisciplinary perspective, including materials science, signal communication, manufacturing technology, and plant physiology. Additionally, this review discusses the challenges and future directions of wearable sensors in the field of plant phenotyping.

Development and application of a numerical dynamic model for pesticide residues in apple orchards

BACKGROUND

Limited understanding of the fate of pesticides in apple orchards may lead to recurring pests or pose risks to food safety. In this study, through a field experiment conducted in an apple orchard, a dynamic plant uptake model, coupled with a soil water model, was developed to simulate measured pesticide concentrations in soil and different plant compartments.

RESULTS

Results showed that the overall model could adequately describe the data set of four pesticides in the apple orchard. An estimated 15%-24.7% of applied pesticides were deposited on leaves and 0.37%-0.58% on fruits. Decreasing pesticide concentrations in fruits were observed after pesticide application, with 9.6%-64.8% of this decrease explained by biodegradation, 29.8%-75.8% by fruit growth dilution and 11.3%-47.6% by wash-off. Furthermore, a first estimation of dietary risks indicated that ingestion of the apples may not represent an acute or chronic risk to human health.

CONCLUSION

The dynamic plant uptake model, coupled with the tipping buckets soil water model, could successfully be fitted to describe to the data set for the fate of four pesticides applied in an apple orchard. The contribution of different pathways to pesticide concentration was highly influenced by precipitation, fruit growth dilution and the characteristics of different pesticides. This model can improve our understanding of pesticide fate in apple orchards and has great potential for supporting food safety assessment and decision-making to minimize impacts arising from pesticide applications. © 2022 Society of Chemical Industry.

Overexpression of PxαE14 Contributing to Detoxification of Multiple Insecticides in Plutella xylostella (L.)

The diamondback moth, Plutella xylostella (L.), has evolved with varying degrees of resistance to almost all major classes of insecticides and has become the most resistant pest worldwide. The multiresistance to different types of insecticides has been frequently reported in P. xylostella, but little is known about the mechanism. In this study, a carboxylesterase (CarE) gene, PxαE14, was found significantly overexpressed in a field-evolved multiresistant P. xylostella population and can be dramatically induced by eight of nine tested insecticides. Results of the real-time quantitative polymerase chain reaction (RT-qPCR) showed that PxαE14 was predominantly expressed in the midgut and malpighian tubule of larvae. Knockdown of PxαE14 dramatically increased the susceptibility of the larvae to β-cypermethrin, bifenthrin, chlorpyrifos, fenvalerate, malathion, and phoxim, while overexpression of PxαE14 in Drosophila melanogaster increased the tolerance of the fruit flies to these insecticides obviously. More importantly, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay showed that the recombinant PxαE14 expressed in Escherichia coli exhibited metabolic activity against the six insecticides. The homology modeling, molecular docking, and molecular dynamics simulation analyses showed that these six insecticides could stably bind to PxαE14. Taken together, these results demonstrate that constitutive and inductive overexpression of PxαE14 contributes to detoxification of multiple insecticides involved in multiresistance in P. xylostella. Our findings provide evidence for understanding the molecular mechanisms underlying the multiresistance in insect pests.

Flexible Wearables for Plants

The excellent stretchability and biocompatibility of flexible sensors have inspired an emerging field of plant wearables, which enable intimate contact with the plants to continuously monitor the growth status and localized microclimate in real-time. Plant flexible wearables provide a promising platform for the development of plant phenotype and the construction of intelligent agriculture via monitoring and regulating the critical physiological parameters and microclimate of plants. Here, the emerging applications of plant flexible wearables together with their pros and cons from four aspects, including physiological indicators, surrounding environment, crop quality, and active control of growth, are highlighted. Self-powered energy supply systems and signal transmission mechanisms are also elucidated. Furthermore, the future opportunities and challenges of plant wearables are discussed in detail.