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References from Rapid and accurate PLS-RBF neural networks for multi-constituent prediction in intact fresh maize kernels using NIR spectroscopy. Local targets link to admitted publications; unresolved targets remain external evidence.
A tutorial on near infrared spectroscopy and its calibration
10.1080/10408347.2010.515468 · 2010 · External reference
Response of fresh maize yield to nitrogen application rates and characteristics of nitrogen-efficient varieties
10.1016/j.jia.2024.03.085 · 2025 · External reference
Classification of cow milk using artificial neural network developed from the spectral data of single- and three-detector spectrophotometers
10.1016/j.foodchem.2019.05.060 · 2019 · External reference
Application of near-infrared spectroscopy/artificial neural network to quantify glycosylated norisoprenoids in Tannat grapes
10.1016/j.foodchem.2022.132927 · 2022 · External reference
Detection of nonlinearity in multivariate calibration
10.1016/s0003-2670(98)00543-1 · 1998 · External reference
Rapid quality evaluation and geographical origin recognition of ginger powder by portable NIRS in tandem with chemometrics
10.1016/j.foodchem.2023.137931 · 2024 · External reference
FT-NIR spectroscopy combined with PLS-DA-SVM for adulteration detection in Xinyang Maojian tea
10.1016/j.jfca.2025.108667 · 2025 · External reference
An effective method fusing electronic nose and fluorescence hyperspectral imaging for the detection of pork freshness
10.1016/j.fbio.2024.103880 · 2024 · External reference
Optimization of near-infrared reflectance models in determining flavonoid composition of okra (Abelmoschus esculentus L.) pods
10.1016/j.foodchem.2023.135953 · 2023 · External reference
Accurate prediction of the eating and cooking quality of rice using artificial neural networks and the texture properties of cooked rice
10.1016/j.foodchem.2022.135176 · 2023 · External reference
New methods based on back propagation (BP) and radial basis function (RBF) artificial neural networks (ANNs) for predicting the occurrence of haloketones in tap water
10.1016/j.scitotenv.2021.145534 · 2021 · External reference
Pan’s procedure for the tail probabilities of the Durbin-Watson statistic
1980 · External reference
Identification of informative spectral ranges for predicting major chemical constituents in corn using NIR spectroscopy
10.1016/j.foodchem.2022.132442 · 2022 · External reference
Simultaneous determination of glucose, fructose, sucrose and sorbitol in the leaf and fruit peel of different apple cultivars by the HPLC-RI optimized method
10.1016/j.foodchem.2015.12.060 · 2016 · External reference
Improving prediction model robustness with virtual sample construction for near-infrared spectra analysis
10.1016/j.aca.2023.341763 · 2023 · External reference
Using an optimal CC-PLSR-RBFNN model and NIR spectroscopy for the starch content determination in corn
10.1016/j.saa.2018.02.017 · 2018 · External reference
Research on rainfall prediction based on RBF neural network model and stormwater inundation risk in scenic areas: A case study of the Yesanpo Scenic Area, Baoding, China
10.1016/j.pce.2023.103487 · 2023 · External reference
Machine learning approaches for stability prediction of rectangular tunnels in natural clays based on mlp and rbf neural networks
10.1016/j.iswa.2024.200329 · 2024 · External reference
Analysis of secondary biochemical components in maize flour samples by near infrared reflectance NIR spectroscopy
10.1007/s11694-020-00479-0 · 2020 · External reference
Computer aided design of experiments
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Unresolved reference
External reference
A black tea quality testing method for scale production using CV and NIRS with TCN for spectral feature extraction
10.1016/j.foodchem.2024.141567 · 2025 · External reference
A feature-enhanced approach based on joint domain alignment and multi-order derivative spectral reconstruction for predicting apple firmness using Vis-NIR spectroscopy
10.1016/j.foodchem.2025.143457 · 2025 · External reference
A metabolic roadmap of waxy corn flavor
10.1016/j.molp.2024.11.003 · 2024 · External reference
Nitrogen-phosphorus responses and Vis/NIR prediction in fresh tea leaves
10.1016/j.foodchem.2025.143369 · 2025 · External reference
An evaluation of direct orthogonal signal correction and other preprocessing methods for the classification of clinical study lots of a dermatological cream
10.1016/s0731-7085(02)00401-6 · 2002 · External reference
Radial basis function approximations: comparison and applications
10.1016/j.apm.2017.07.033 · 2017 · External reference
Radial basis function network for aggregating predictions of k-nearest neighbors local models generated based on independent data sets
10.1016/j.procs.2022.09.381 · 2022 · External reference
Double stage network inference system using k means clustering and fuzzy cognitive maps for cardiovascular disease diagnosis
10.1016/j.engappai.2025.111540 · 2025 · External reference
Challenging handheld NIR spectrometers with moisture analysis in plant matrices: Performance of PLSR vs, GPR vs. ANN modelling
10.1016/j.saa.2020.119342 · 2021 · External reference
Machine learning for authentication of black tea from narrow-geographic origins: Combination of PCA and PLS with LDA and SVM classifiers
10.1016/j.lwt.2024.116401 · 2024 · External reference
Flexible vitality of near-infrared spectroscopy - Talking about Norris derivative filter
10.1177/0960336019889587 · 2020 · External reference
Effects of nitrogen fertilizer substitution by cow manure on yield, net GHG emissions, carbon and nitrogen footprints in sweet maize farmland in the Pearl River Delta in China
10.1016/j.jclepro.2023.136676 · 2023 · External reference
Unresolved reference
1998 · External reference
Spectrophotometric estimation of amylopectin by double-wavelength method
10.1002/star.19750270805 · 1975 · External reference
Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy
10.2135/cropsci1991.0011183x003100020049x · 1991 · External reference
A cost-effective and scalable machine learning approach for quality assessment of fresh maize kernel using NIR spectroscopy
10.1002/advs.202512750 · 2025 · External reference
Development of automatic tuning for combined preprocessing and hyperparameters of machine learning and its application to NIR spectral data of coconut milk adulteration
10.1016/j.foodchem.2024.140108 · 2024 · External reference
Comparison of Gaussian process regression, partial least squares, random forest and support vector machines for a near infrared calibration of paracetamol samples
10.1016/j.rechem.2022.100508 · 2022 · External reference
Ridge regression and artificial neural network to predict the thermodynamic properties of alkali metal Rankine cycles for space nuclear power
10.1016/j.enconman.2022.116385 · 2022 · External reference
Quantification of heavy metal Cd in peanut oil using near-infrared spectroscopy combined with chemometrics: Analysis and comparison of variable selection methods
10.1016/j.infrared.2024.105447 · 2024 · External reference
Study of bp and rbf neural networks applied to the prediction of vibration characteristics in static blasting of dry ice powder
10.1007/s12205-024-1731-y · 2024 · External reference
Real-time prediction of metacentric height of ro-ro passenger ships in Qiongzhou strait based on improved RBF neural network
2024 · External reference
Fresh or dry maize or both: Which is most economical and preferred by farmers?
10.1016/j.jafr.2024.101158 · 2024 · External reference
Calibration model optimization for rice cooking characteristics by near infrared reflectance spectroscopy (NIRS)
10.1016/j.foodchem.2006.07.063 · 2007 · External reference
Classification of Fritillaria using a portable near-infrared spectrometer and fuzzy generalized singular value decomposition
10.1016/j.indcrop.2024.119032 · 2024 · External reference
Rapid discrimination of quality grade of black tea based on near-infrared spectroscopy (NIRS), electronic nose (E-nose) and data fusion
10.1016/j.foodchem.2023.138242 · 2024 · External reference
Simultaneous determination of apparent amylose, amylose and amylopectin content and classification of waxy rice using near-infrared spectroscopy (NIRS)
10.1016/j.foodchem.2022.132944 · 2022 · External reference
Estimation model for maize multi-components based on hyperspectral data
10.3390/s24186111 · 2024 · External reference
Rapid and simultaneous quality analysis of the three active components in Lonicerae Japonicae Flos by near-infrared spectroscopy
2021 · External reference
Application of dual-wavelength spectrophotometry to determination of amylose and amylopectin contents
10.3136/nskkk1962.40.5_365 · 1993 · External reference
Quantitative assessment of emulsified oil concentration based on near-infrared spectroscopy and multiple machine learning algorithms
10.1016/j.measurement.2025.119204 · 2026 · External reference
Rapid detection of corn moisture content based on improved ICEEMDAN algorithm combined with TCN-BiGRU model
10.1016/j.foodchem.2024.142133 · 2025 · External reference
Adaptive Artificial Neural Network in near infrared spectroscopy for standard-free calibration transfer
10.1016/j.chemolab.2022.104674 · 2022 · External reference
Predicting models for plant metabolites based on PLSR, AdaBoost, XGBoost, and LightGBM algorithms using hyperspectral imaging of brassica juncea
10.3390/agriculture13081477 · 2023 · External reference
Enhancing customer retention in Online Retail through churn prediction: A hybrid RFM, K-means, and deep neural network approach
10.1016/j.eswa.2025.128465 · 2025 · External reference
An overview on the applications of typical non-linear algorithms coupled with NIR spectroscopy in food analysis
10.1007/s12393-020-09210-7 · 2020 · External reference
Characterization of volatile metabolites in temperate and tropical sweet corn cultivars under various post-harvest storage conditions
2024 · External reference
Prediction of oil content in single maize kernel based on hyperspectral imaging and attention convolution neural network
10.1016/j.foodchem.2022.133563 · 2022 · External reference
Deep learning and feature reconstruction assisted vis-NIR calibration method for on-line monitoring of key growth indicators during kombucha production
10.1016/j.foodchem.2024.141411 · 2025 · External reference
Optimizing feature selection with gradient boosting machines in PLS regression for predicting moisture and protein in multi-country corn kernels via NIR spectroscopy
10.1016/j.foodchem.2024.140062 · 2024 · External reference
Prediction of maize crude fat content based on improved conditional mutual information maximization and shap analysis
10.1016/j.foodchem.2025.146054 · 2025 · External reference
Comparative study of indirect and direct feature extraction algorithms in classifying tea varieties using near-infrared spectroscopy
10.1016/j.crfs.2025.101065 · 2025 · External reference
Fusion of convolutional neural network with XGBoost feature extraction for predicting multi-constituents in corn using near infrared spectroscopy
10.1016/j.foodchem.2024.141053 · 2025 · External reference
Variables selection methods in near-infrared spectroscopy
2010 · External reference
