Advancing Agriculture for Future Generations: The Impact of Spectroscopy on an Important Field
Welcome to our “Advancing Agriculture for Future Generations” content series!
Below is a compilation of news stories, Q&As, and technical articles that spotlight the current and ongoing spectroscopic research in the field of agriculture.
Click an article below to begin your journey!
Spectroscopy in Agriculture: An Interview with Dmitry Kurouski
Dmitry Kurouski of Texas A&M University speaks to Spectroscopy Editor Patrick Lavery about Raman spectroscopy's role in determining crop yield of key food items as the world population continues to increase.
Author: Patrick Lavery
Link: https://www.spectroscopyonline.com/view/spectroscopy-agriculture-interview-dmitry-kurouski
Reviewing the Impact of Raman Spectroscopy on Crop Quality Assessment: An Interview with Miri Park
Miri Park of the Fraunhofer Institute for Environmental, Safety, and Energy Technologies is examining how Raman spectroscopy could aid non-destructive sensing in agricultural science. Recently, Park sat down with Spectroscopy to discuss micro-Raman spectroscopy's role in assessing crop quality, particularly secondary metabolites, across different contexts (in vitro, in vivo, and in situ), while suggesting future research for broader application possibilities.
Author: Will Wetzel
Monitoring Soil Quality Using MIR and NIR Spectral Models: An Interview with Felipe Bachion de Santana
Felipe Bachion de Santana of Teagasc in Wexford, Ireland, is exploring new ways to monitor soil quality through using spectroscopic techniques. Spectroscopy spoke to him about his team’s work in monitoring the quality of soil to improve agricultural efficiency.
Author: Will Wetzel
Q&A: Portable FT-IR Empowers On-Site Food Quality Assurance
Exploring the transformative capabilities of handheld FT-IR spectrometers, a review from Yıldız Technical University and The Ohio State University emphasizes their pivotal role in ensuring food integrity and safety across the entire supply chain. Read the Q&A about this review article here.
Author: Patrick Lavery
Revolutionizing Orchard Management: Deep Learning Yields Precise Fruit Tree Segmentation
A recent study from Jeonbuk National University introduces a novel technique for orchard management: tackling intertwined fruit trees' precise segmentation using deep learning models.
Author: Spectroscopy Staff
Revolutionizing Agriculture: Machine Learning Unveils Optimal Microbial Strains for Drought Mitigation
Researchers from the University of Szczecin and other Polish institutions have applied the power of machine learning, employing various models, to forecast optimal microbial strains for mitigating drought impacts on crops, marking a leap toward sustainable agriculture to ensure global food security.
Author: Spectroscopy Staff
Cutting-Edge Technology Safeguards Apple Quality: Hyperspectral Imaging and Machine Learning to Combat Codling Moth Infestation
Researchers at the University of Kentucky employ non-destructive hyperspectral imaging and machine learning to predict and manage the physicochemical quality attributes of apples during storage, addressing the impact of codling moth infestation and revolutionizing apple quality assurance.
Author: Spectroscopy Staff
Revolutionizing Lettuce Farming: Artificial Intelligence and Spectroscopy for Precise Pigment Phenotyping
Researchers in Brazil leverage artificial intelligence algorithms and Vis-NIR-SWIR hyperspectroscopy to achieve precise pigment phenotyping and classification of eleven lettuce varieties, showcasing the potential of integrating advanced technologies in agriculture.
Author: Spectroscopy Staff
Transfer Learning-Assisted LIBS Enhances Crop Traceability in Sample-Limited Conditions
Researchers have developed a transfer learning-assisted laser-induced breakdown spectroscopy (LIBS) method to identify geographical origins of crops with an impressive accuracy by incorporating deep adaptation networks.
Author: Spectroscopy Staff
Hyperspectral Images of Fuji Apples Used as Predictive Data for Fruit Bruise Area
While this technology has been frequently deployed in recent years to evaluate fruit quality, relatively few studies have examined such parameters as variation, damage time, and damage degree.
Author: Patrick Lavery
New Time Series Prediction Model Tested on Measuring Soil Moisture
Scientists from Zhejiang A&F University and Huzhou University in China recently created a new time series prediction model that combines linear and nonlinear prediction methods.
Author: Aaron Acevedo
Persimmon Leaves’ Contents Determined Using Hyperspectral Imaging
Using visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI), scientists were able to determine macro- and micronutrient contents rapidly and non-destructively in persimmon leaves.
Author: Aaron Acevedo
Study on Estimating Total Nitrogen Content in Sugar Beet Leaves Under Drip Irrigation Based on Vis-NIR Hyperspectral Data and Chlorophyll Content
This article explores the relationship between the leaf nitrogen content (LNC) and hyperspectral remote sensing imagery (HYP) to construct an estimation model of the LNC of drip-irrigated sugar beets.
Authors: Zong-fei Li, Bing Chen, Hua Fan, Cong Fei, Ji-xia Su, Yang-yang Li, Ning-ning Liu, Hong-liang Zhou, Li-juan Zhang, Kai-yong Wang
Detection of the Early Fungal Infection of Citrus by Fourier Transform Near-Infrared Spectra
The results in this study indicate that FT-NIR spectroscopy, combined with chemometric methods, is able to distinguish early fungal infections in citrus.
Authors: Maopeng Li, Yande Liu, Jun Hu, Chengtao Su, Zhen Xu, Huizhen Cui
Soil Organic Matter Estimation Modeling Using Fractal Feature of Soil for vis-NIR Hyperspectral Imaging
A novel intelligent inversion model integrating multiscale fractal analysis, PCA, and machine learning techniques (RF and SVM) was devised to accurately estimate soil organic matter (SOM) using hyperspectral data.
Author: Shaofang He, Qing Zhou, Fang Wang, Luming Shen, Jing Yang
Trends in Infrared Spectroscopic Imaging
September 13th 2013An interview with Rohit Bhargava, winner of the 2013 Craver Award. This interview is part of the 2013 podcast series presented in collaboration with the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS), in connection with SciX 2013, the federation?s North American conference.
The 2024 Emerging Leader in Atomic Spectroscopy Award
January 1st 2024This year’s Emerging Leader in Atomic Spectroscopy Award recipient is Eduardo Bolea-Fernández. For the past decade, Bolea-Fernández’s research has focused on the development of a newly introduced technique, termed tandem ICP-mass spectrometry (ICP-MS/MS), for ultra-trace elemental and isotopic analysis. Senior technical editor Jerome Workman discusses Bolea-Fernández’s work here.
