Achieving robustness to temperature change of a NIRS-PLSR model for intact mango fruit dry matter content

Temperature impacts the extent of H bonding in water and thus impacts near infrared (NIR) spectra of fruit and influences the robustness of models between spectra and attributes such as dry matter content (DMC). Temperature correction methods including external parameter orthogonalisation (EPO), generalised least square weighting (GLSW), bias correction, repeatability file, calibration wavelength optimization and global modelling were applied to reduce the impact of sample temperature change on DMC prediction of intact mango fruit using a calibration data set of 1392 samples and a validation set of 660 samples of variable sample temperatures, drawn from 15 populations sourced from separate harvests. All methods except bias correction reduced bias corrected root mean square error of prediction (RMSEP) and increased coefficient of determination (R2). For a global model, it is recommended that at least 2.4 % of samples in the model be scanned at different temperatures. However, the EPO method is recommended overall, as it returned the lowest RMSEP and highest R2 (1.05 % w/w, and 0.82 compared with the control result of 1.43 % and 0.68, respectively), in prediction of the population with spectra acquired at three temperatures. A residual of ± 0.10×ŷ, where ŷ is the reference value, was associated with a confidence interval of 92.4 and 77.4 % for the EPO corrected and original models, respectively. The results have significance for the practical implementation of NIRS-DMC estimation of fruit in field conditions

NIRS prediction of dry matter content of single olive fruit with consideration of variable sorting for normalisation pre-treatment

The assessment of dry matter content (DMC) as a surrogate for oil content of single olive fruit was considered in terms of spatial variation in DMC, optimisation of spectral pre-treatments, wavelength range and calibration transfer procedure. There was no consistent variation in DMC from apical to distal end of the fruit. Short wave near infrared spectra (to 1100 nm) were acquired of single fruit using an interactance geometry, with the small size of the fruit resulting in baseline variation between samples. The pre-treatment methods of first derivative (D1), second derivative (D2), standard normal variate transformation (SNV), normalized spectral ratio (NSR), variable sorting for normalization (VSN) and their combinations were applied prior to development of partial least squares regression models on DMC. Root mean square error of prediction (RMSEP) values were reduced with use of the SNV-VSN-D2 pre-treatment (by 34 and 35 %) to 0.95 and 0.88 %, for two handheld NIRS instruments, used in prediction of an external set, n = 212. The percentage of the predicted population within the limits of ± 5 % of actual values was 92.5 and 88.7 % for the VSN PLSR models and 83.0 and 77.3 % for the original models, for two instruments, respectively. Variable selection allowed a further improvement in RMSEP values (to 0.93 and 0.87 %) for the two instruments, respectively. For transfer of models between instruments, model updating based on SNV-VSN-D2 pre-treated spectra resulted in a RMSEP of 1.00 %, compared to 1.79 % for D2 pre-treated spectra, outperforming the classical calibration transfer methods of piecewise direct standardization (PDS) and spectral space transformation (SST). The results have significance to the practical implementation of NIRS-DMC estimation of olive fruit in field conditions

A Multichannel Fluorescence Isothermal Amplification Device with Integrated Internet of Medical Things for Rapid Sensing of Pathogens through Deep Learning

The landscape of diagnostic assessments has experienced a paradigm shift driven by the advent of isothermal amplification techniques on point-of-care testing (POCT). The development of compact, portable isothermal amplification devices further emphasizes their transformative influence on diagnostic approaches. However, in prioritizing portability, these devices may exhibit limitations in functionality, rendering them less effective in addressing urgent public health emergencies during sudden pathogen outbreaks. In this paper, an efficient isothermal fluorescence amplification device has been fabricated for the rapid detection of pathogens during public health crises. The device features multichannel capability for simultaneous detection of various targets, integrates with the Internet of Medical Things (IoMT) for remote control and data uploading, and includes a deep learning-based batch processing system for rapid (9.4 ms) and accurate discrimination of pathogen type with excellent accuracy. The device has been successfully employed to simultaneously detect Staphylococcus aureus (SA) and methicillin-resistant Staphylococcus aureus (MRSA) with limits of detection (LODs) of 18 CFU/mL (SA) and 20 CFU/mL (MRSA) within 35 min by multiplex RPA assay and CRISPR/Cas12a-mediated nucleic acid detection assay

NIRS prediction of dry matter content of single olive fruit with consideration of variable sorting for normalisation pre-treatment

The assessment of dry matter content (DMC) as a surrogate for oil content of single olive fruit was considered in terms of spatial variation in DMC, optimisation of spectral pre-treatments, wavelength range and calibration transfer procedure. There was no consistent variation in DMC from apical to distal end of the fruit. Short wave near infrared spectra (to 1100 nm) were acquired of single fruit using an interactance geometry, with the small size of the fruit resulting in baseline variation between samples. The pre-treatment methods of first derivative (D1), second derivative (D2), standard normal variate transformation (SNV), normalized spectral ratio (NSR), variable sorting for normalization (VSN) and their combinations were applied prior to development of partial least squares regression models on DMC. Root mean square error of prediction (RMSEP) values were reduced with use of the SNV-VSN-D2 pre-treatment (by 34 and 35 %) to 0.95 and 0.88 %, for two handheld NIRS instruments, used in prediction of an external set, n = 212. The percentage of the predicted population within the limits of ± 5 % of actual values was 92.5 and 88.7 % for the VSN PLSR models and 83.0 and 77.3 % for the original models, for two instruments, respectively. Variable selection allowed a further improvement in RMSEP values (to 0.93 and 0.87 %) for the two instruments, respectively. For transfer of models between instruments, model updating based on SNV-VSN-D2 pre-treated spectra resulted in a RMSEP of 1.00 %, compared to 1.79 % for D2 pre-treated spectra, outperforming the classical calibration transfer methods of piecewise direct standardization (PDS) and spectral space transformation (SST). The results have significance to the practical implementation of NIRS-DMC estimation of olive fruit in field conditions

Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use

The application of visible (Vis; 400–750 nm) and near infrared red (NIR; 750–2500 nm) region spectroscopy to assess fruit and vegetables is reviewed in context of ‘point’ spectroscopy, as opposed to multi- or hyperspectral imaging. Vis spectroscopy targets colour assessment and pigment analysis, while NIR spectroscopy has been applied to assessment of macro constituents (principally water) in fresh produce in commercial practice, and a wide range of attributes in the scientific literature. This review focusses to key issues relevant to the widespread implementation of Vis-NIR technology in the fruit sector. A background to the concepts and technology involved in the use of Vis-NIR spectroscopy is provided and instrumentation for in-field and in-line applications, which has been available for two and three decades, respectively, is described. A review of scientific effort is made for the period 2015 - February 2020, in terms of the application areas, instrumentation, chemometric methods and validation procedures, and this work is critiqued through comparison to techniques in commercial use, with focus to wavelength region, optical geometry, experimental design, and validation procedures. Recommendations for future research activity in this area are made, e.g., application development with consideration of the distribution of the attribute of interest in the product and the matching of optically sampled and reference method sampled volume; instrumentation comparisons with consideration of repeatability, optimum optical geometry and wavelength range). Recommendations are also made for reporting requirements, viz. description of the application, the reference method, the composition of calibration and test populations, chemometric reporting and benchmarking to a known instrument/method, with the aim of maximising useful conclusions from the extensive work being done around the world

Palladium-Catalyzed C8 Alkylation of 1‑Naphthylamides with Alkyl Halides via Bidentate-Chelation Assistance

A Pd-catalyzed regioselective alkylation of C8–H bonds in 1-naphthylamides containing a quinolinamide or picolinamide moiety as a bidentate directing group with alkyl halides is reported. The amide directing group can be easily hydrolyzed under basic conditions. Various alkyl halides including alkyl iodides and benzyl bromide or chloride can be employed as coupling partners, exclusively providing 8-alkyl-1-naphthylamide derivatives

High-Adhesion Ag Film with Enhanced Electromagnetic Shielding Performance via Post-Treatment of a Polydopamine Adhesive Layer

Low adhesion limits the application of the conformal metal coating based on metal–organic complexing deposition (MOD) ink in electromagnetic interference shielding with an ultrathin thickness and excellent electromagnetic shielding performance. Here, the mussel-inspired polydopamine (PDA) coating with double-sided adhesive characteristic was used to modify the substrate surface, and a high-adhesion silver film was prepared by spin-coating MOD ink on the PDA-modified substrate. The surface chemical bond of the deposited PDA coating was found to change with the exposure time under air in this work, and three post-treatment methods were carried out on the PDA coatings, including exposure to air for 1 min, exposure to air for a day, and oven heat treatment. The influences of such three post-treatment methods of PDA coating on the structure of the substrate surface, the silver film adhesion property, the electrical property, and the electromagnetic shielding property were studied. The adhesion of the silver film was effectively enhanced up to 20.45 MPa by controlling the post-treatment method of the PDA coating. The PDA coating was found to increase the sheet resistance of the silver film and to absorb electromagnetic waves. By optimizing the deposition time and the post-treatment condition of the PDA coating, superior electromagnetic shielding effectiveness up to 51.18 dB was obtained with a thin silver film of 0.42 μm. The introduction of the PDA coating improves the applicability of the MOD silver ink in the field of conformal electromagnetic shielding

Changes in morphology and chlorophyll fluorescence of <i>E</i>. <i>crassipes</i> and <i>P</i>. <i>stratiotes</i> exposed to 100 mg/L Cd for different times.

<p>A: Changes in leaf and root morphology. B: Fv/Fm images. The pseudocolor code depicted at the top of the image ranges from 0 (red) to 1 (purple). C: Average Fv/Fm values. Data are the means ± SE. Different letters following mean values indicate significant differences (Tukey’s test, <i>P</i><0.05).</p

Few-Layered Boron Nitride Nanosheets for Strengthening Polyurethane Hydrogels

Two-dimensional hexagonal boron nitride nanosheets (BNNS) are an outstanding filler and additive, since they are transparent, thermally stable, and chemically inert. However, it is difficult to obtain few-layered BNNS with large lateral sizes in an efficient way due to the strong interlayer interactions in h-BN. Herein, a facile and efficient molten salt-assisted synthesis has been developed to prepare few-layered BNNS with a few microns in lateral size. Ammonia borane was mixed with KCl and NaCl and then heated to 1000 °C and held for 2 min, and the resultant powders were sonicated in water to produce hydroxylated BNNS. Used as an additive with 0.066 wt % loading, the functionalized BNNS can effectively improve the mechanical modulus of polyurethane (PU) hydrogels from 1635 to 2776 kPa, and the optical property of the hydrogel is not compromised. The BNNS-reinforced PU hydrogel with significantly improved mechanical properties can be highly useful in the application of printed electronics

Controlled Photocatalytic Growth of Ag Nanocrystals on Brookite and Rutile and Their SERS Performance

Ag nanocrystals (NCs) were photocatalytically grown on the surfaces of brookite and rutile nanocrystals, respectively, and their surface-enhanced Raman scattering (SERS) performance was evaluated. The resultant Ag NCs exhibit different morphologies owing to the different photocatalytic capabilities of the two types of TiO2 under otherwise identical synthetic conditions. The effects of AgNO3 concentration, UV irradiation time, and UV light power on the morphology evolution and growth kinetics of the Ag NCs were systematically investigated. Moreover, PVP was found to serve as both a reductant and a capping agent in the photocatalytic reaction systems, and its presence allows morphological control of the Ag NCs. A proper amount of PVP was confirmed to favor Ag nanoplates of larger sizes and to produce SERS substrates of substantially better performance