Online inspection of blackheart in potatoes using visible-near infrared spectroscopy and interpretable spectrogram-based modified ResNet modeling.

Introduction: Blackheart is one of the most common physiological diseases in potatoes during storage. In the initial stage, black spots only occur in tissues near the potato core and cannot be detected from an outward appearance. If not identified and removed in time, the disease will seriously undermine the quality and sale of theentire batch of potatoes. There is an urgent need to develop a method for early detection of blackheart in potatoes. Methods: This paper used visible-near infrared (Vis/NIR) spectroscopy to conduct online discriminant analysis on potatoes with varying degrees of blackheart and healthy potatoes to achieve real-time detection. An efficient and lightweight detection model was developed for detecting different degrees of blackheart in potatoes by introducing the depthwise convolution, pointwise convolution, and efficient channel attention modules into the ResNet model. Two discriminative models, the support vector machine (SVM) and the ResNet model were compared with the modified ResNet model. Results and discussion: The prediction accuracy for blackheart and healthy potatoes test sets reached 0.971 using the original spectrum combined with a modified ResNet model. Moreover, the modified ResNet model significantly reduced the number of parameters to 1434052, achieving a substantial 62.71% reduction in model complexity. Meanwhile, its performance was evidenced by a 4.18% improvement in accuracy. The Grad-CAM++ visualizations provided a qualitative assessment of the model's focus across different severity grades of blackheart condition, highlighting the importance of different wavelengths in the analysis. In these visualizations, the most significant features were predominantly found in the 650-750 nm range, with a notable peak near 700 nm. This peak was speculated to be associated with the vibrational activities of the C-H bond, specifically the fourth overtone of the C-H functional group, within the molecular structure of the potato components. This research demonstrated that the modified ResNet model combined with Vis/NIR could assist in the detection of different degrees of black in potatoes.

Computational model of pesticide deposition distribution on canopies for air-assisted spraying.

The deposited pesticide distribution in fruit tree canopies is crucial for evaluating the efficacy of air-assisted spraying in orchards. Most studies have determined the impact of pesticide application on pesticide deposition on canopies without a quantitative computational model. In this study, an air-assisted orchard sprayer with airflow control was used to perform spraying experiments on artificial and peach trees. In the spraying experiment on an artificial tree, a canopy with leaf areas ranging from 2.54~5.08 m2 was found to require an effective air speed of 18.12~37.05 m/s. The canopy leaf area, air speed at the sprayer fan outlet and spray distance were used as test factors in a three-factor five-level quadratic general rotational orthogonal test to develop a computational model for pesticide deposition at the inner, outer and middle regions of a fruit tree canopy with R 2 values of 0.9042, 0.8575 and 0.8199, respectively. A significance analysis was used to rank the influencing factors for the deposited pesticide distribution in decreasing order of significance as follows: the spray distance, leaf area and air speed for the inner region of the canopy, followed by the spray distance, air speed and leaf area for the middle and outer regions of the canopy. The results of the verification test conducted in a peach orchard showed that the computational errors of the pesticide deposition model for the inner, middle and outer regions of the canopy were 32.62%, 22.38% and 23.26%, respectively. The results provide support for evaluating the efficacy of an air-assisted orchard sprayer and optimizing the sprayer parameters.

Conformational change and biocatalysis-triggered spectral shift of single Au nanoparticles.

Spectral shift of localized plasmon resonance scattering of guanine-rich DNA modified single Au nanoparticles is observed under a dark field microscope equipped with a spectrometer. The spectra continuously red-shift with the conformational change of the guanine-rich DNA upon associating with K(+), hemin and the biocatalytic growth of the polymer. The scattering spectrum of single nanoparticles is proved to be sensitive both to a subtle conformational change and the biocatalysis process. 20 mM K(+) or 100 µM H2O2 can trigger a detectable peak shift. The present study paves a new and efficient way to extract chemical information from micro/nanospace.

Core-shell Ag@SiO(2) nanoparticles concentrated on a micro/nanofluidic device for surface plasmon resonance-enhanced fluorescent detection of highly reactive oxygen species.

A micro/nanofluidic device integrating a nanochannel in a microfluidic chip was developed for sensitive fluorescent determination of highly reactive oxygen species (hROS) enhanced by surface plasmon resonance-enhanced fluorescence (SPREF). The nanochannel was simply fabricated by polyaniline nanostructures modified on a glass slide. Core-shell Ag@SiO2 nanoparticles were concentrated in front of the nanochannel for fluorescence enhancement based on the SPREF effect. As a demonstration, hROS in the mainstream of cigarette smoke (CS) were detected by the present micro/nanofluidic device. The fluorescent probe for trapping hROS in puffs of CS employed a microcolumn that was loaded with a composite of DNA (conjugated fluorophores, FAM) and Au membrane (coated on cellulose acetate). With a laser-induced fluorescence detection device, hROS was determined on the basis of the amount of FAM groups generated by DNA cleavage. With the optimization of the trapping efficiency, we detected about 4.91 pmol of hROS/puff in the mainstream CS. This micro/nanofluidic-SPREF system promises a simple, rapid, and highly sensitive approach for determination of hROS in CS and other practical systems.