Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery.

Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models.

Temperature-Dependent Sporulation of the Fungus , the Causal Agent of Grape White Rot.

White rot, caused by the fungus , can severely reduce grapevine yields worldwide. Currently, white rot control mainly relies on fungicides applied on a calendar basis or following hailstorms that favor disease outbreaks; however, the control achieved with this strategy is often inconsistent or otherwise unsatisfactory. Realizing more rational control requires an improved understanding of white rot epidemiology.

Early bruising detection of 'Korla' pears by low-cost visible-LED structured-illumination reflectance imaging and feature-based classification models.

Introduction: Nondestructive detection of thin-skinned fruit bruising is one of the main challenges in the automated grading of post-harvest fruit. The structured-illumination reflectance imaging (SIRI) is an emerging optical technique with the potential for detection of bruises.

Methods: This study presented the pioneering application of low-cost visible-LED SIRI for detecting early subcutaneous bruises in 'Korla' pears.

Applications of Gas Sensing in Food Quality Detection: A Review.

Food products often face the risk of spoilage during processing, storage, and transportation, necessitating the use of rapid and effective technologies for quality assessment. In recent years, gas sensors have gained prominence for their ability to swiftly and sensitively detect gases, making them valuable tools for food quality evaluation. The various gas sensor types, such as metal oxide (MOX), metal oxide semiconductor (MOS) gas sensors, surface acoustic wave (SAW) sensors, colorimetric sensors, and electrochemical sensors, each offer distinct advantages.

Synchronous fluorescence detection of nitrite in meat products based on dual-emitting dye@MOF and its portable hydrogel test kit.

A novel ratiometric fluorescent nanoprobe (Rh6G@UIO-66-NH) was fabricated for efficient nitrite (NO) detection in the present study. When NO was introduced, it interacted with the amino groups on the surface of Rh6G@UIO-66-NH, forming diazonium salts that led to the quenching of blue fluorescence. With this strategy, a good linear relationship between NO concentration and the fluorescent intensity ratio of the nanoprobe in the range of 1-100 μM was established, with a detection limit of 0.

Seasonal Periodicity of the Airborne Spores of Fungi Causing Grapevine Trunk Diseases: An Analysis of 247 Studies Published Worldwide.

Grapevine trunk diseases (GTDs) are among the most devastating grapevine diseases globally. GTDs are caused by numerous fungi belonging to different taxa, which release spores into the vineyard and infect wood tissue, mainly through wounds caused by viticultural operations. The timing of operations to avoid infection is critical concerning the periodicity of GTD spores in vineyards, and many studies have been conducted in different grape-growing areas worldwide.

A lightweight cow mounting behavior recognition system based on improved YOLOv5s.

To improve the detection speed of cow mounting behavior and the lightness of the model in dense scenes, this study proposes a lightweight rapid detection system for cow mounting behavior. Using the concept of EfficientNetV2, a lightweight backbone network is designed using an attention mechanism, inverted residual structure, and depth-wise separable convolution. Next, a feature enhancement module is designed using residual structure, efficient attention mechanism, and Ghost convolution.

Temporal Dynamics and Dispersal Patterns of the Primary Inoculum of , the Causal Agent of Grape White Rot.

Grape white rot can cause considerable yield losses in viticulture areas worldwide and is principally caused by . The fungus overwinters in berry mummies on the soil surface or on the trellis and produces pycnidia and conidia that serve as primary inoculum. However, little is known about the temporal dynamics and dispersal pattern of conidia.

Research on decoupled air speed and air volume adjustment methods for air-assisted spraying in orchards.

Different fruit tree canopies have different requirements for air speed and air volume. Due to the strong relationship between air speed and air volume, the decoupled control of air speed and air volume cannot be achieved using the existing sprayers. In this study, an innovative air-assisted sprayer that supports the independent adjustment of fan speed (0-2940 r/min) and air outlet area (1022.

Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system.

The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system.

Artificial neural network-based shelf life prediction approach in the food storage process: A review.

The prediction of food shelf life has become a vital tool for distributors and consumers, enabling them to determine storage and optimal edible time, thus avoiding unexpected food waste. Artificial neural network (ANN) have emerged as an effective, fast and accurate method for modeling, simulating and predicting shelf life in food. ANNs are capable of tackling nonlinear, complex and ill-defined problems between the variables without prior knowledge.

Three-dimensional branch segmentation and phenotype extraction of maize tassel based on deep learning.

Background: The morphological structure phenotype of maize tassel plays an important role in plant growth, reproduction, and yield formation. It is an important step in the distinctness, uniformity, and stability (DUS) testing to obtain maize tassel phenotype traits. Plant organ segmentation can be achieved with high-precision and automated acquisition of maize tassel phenotype traits because of the advances in the point cloud deep learning method.

Regionally Compatible Individual Tree Growth Model under the Combined Influence of Environment and Competition.

To explore the effects of competition, site, and climate on the growth of Chinese fir individual tree diameter at breast height (DBH) and tree height (H), a regionally compatible individual tree growth model under the combined influence of environment and competition was constructed. Using continuous forest inventory (CFI) sample plot data from Fujian Province between 1993 and 2018, we constructed an individual tree DBH model and an H model based on re-parameterization (RP), BP neural network (BP), and random forest (RF), which compared the accuracy of the different modeling methods. The results showed that the inclusion of competition and environmental factors could improve the prediction accuracy of the model.

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.

Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform.

The field phenotyping platforms that can obtain high-throughput and time-series phenotypes of plant populations at the 3-dimensional level are crucial for plant breeding and management. However, it is difficult to align the point cloud data and extract accurate phenotypic traits of plant populations. In this study, high-throughput, time-series raw data of field maize populations were collected using a field rail-based phenotyping platform with light detection and ranging (LiDAR) and an RGB (red, green, and blue) camera.

A novel method for Pu-erh tea face traceability identification based on improved MobileNetV3 and triplet loss.

Ensuring the traceability of Pu-erh tea products is crucial in the production and sale of tea, as it is a key means to ensure their quality and safety. The common approach used in traceability systems is the utilization of bound Quick Response (QR) codes or Near Field Communication (NFC) chips to track every link in the supply chain. However, counterfeiting risks still persist, as QR codes or NFC chips can be copied and inexpensive products can be fitted into the original packaging.

Non-destructive and in-situ detection of shrimp freshness using mid-infrared fiber-optic evanescent wave spectroscopy.

There is strong interest in non-destructive and rapid determination of food freshness in food research. In this study, mid-infrared (MIR) fiber-optic evanescent wave (FOEW) spectroscopy was applied to monitor shrimp freshness through the evaluation of protein, chitin, and calcite contents in conjunction with a Partial Least Squares Discriminant Analysis (PLS-DA) model. Shrimp shells were wiped with a micro fiber-optic probe to obtain a FOEW spectrum which quickly and nondestructively allowed evaluation of the shrimp freshness.

Disentangling the Heterosis in Biomass Production and Radiation Use Efficiency in Maize: A Phytomer-Based 3D Modelling Approach.

Maize ( L.) benefits from heterosis in-yield formation and photosynthetic efficiency through optimizing canopy structure and improving leaf photosynthesis. However, the role of canopy structure and photosynthetic capacity in determining heterosis in biomass production and radiation use efficiency has not been separately clarified.

Hyperspectral remote sensing for tobacco quality estimation, yield prediction, and stress detection: A review of applications and methods.

Tobacco is an important economic crop and the main raw material of cigarette products. Nowadays, with the increasing consumer demand for high-quality cigarettes, the requirements for their main raw materials are also varying. In general, tobacco quality is primarily determined by the exterior quality, inherent quality, chemical compositions, and physical properties.

Application of Internet of Things to Agriculture-The LQ-FieldPheno Platform: A High-Throughput Platform for Obtaining Crop Phenotypes in Field.

The lack of efficient crop phenotypic measurement methods has become a bottleneck in the field of breeding and precision cultivation. However, high-throughput and accurate phenotypic measurement could accelerate the breeding and improve the existing cultivation management technology. In view of this, this paper introduces a high-throughput crop phenotype measurement platform named the LQ-FieldPheno, which was developed by China National Agricultural Information Engineering Technology Research Centre.

A reinterpretation of the gap fraction of tree crowns from the perspectives of computer graphics and porous media theory.

The gap fraction (GF) of vegetative canopies is an important property related to the contained bulk of reproductive elements and woody facets within the tree crown volume. This work was developed from the perspectives of porous media theory and computer graphics techniques, considering the vegetative elements in the canopy as a solid matrix and treating the gaps between them as pores to guide volume-based GF calculations. Woody components and individual leaves were extracted from terrestrial laser scanning data.

Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail.

Unmanned ground vehicles (UGV) have attracted much attention in crop phenotype monitoring due to their lightweight and flexibility. This paper describes a new UGV equipped with an electric slide rail and point cloud high-throughput acquisition and phenotype extraction system. The designed UGV is equipped with an autopilot system, a small electric slide rail, and Light Detection and Ranging (LiDAR) to achieve high-throughput, high-precision automatic crop point cloud acquisition and map building.

Geometric Wheat Modeling and Quantitative Plant Architecture Analysis Using Three-Dimensional Phytomers.

The characterization, analysis, and evaluation of morphology and structure are crucial in wheat research. Quantitative and fine characterization of wheat morphology and structure from a three-dimensional (3D) perspective has great theoretical significance and application value in plant architecture identification, high light efficiency breeding, and cultivation. This study proposes a geometric modeling method of wheat plants based on the 3D phytomer concept.

A variety test platform for the standardization and data quality improvement of crop variety tests.

Variety testing is an indispensable and essential step in the process of creating new improved varieties from breeding to adoption. The performance of the varieties can be compared and evaluated based on multi-trait data from multi-location variety tests in multiple years. Although high-throughput phenotypic platforms have been used for observing some specific traits, manual phenotyping is still widely used.