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Variable selection for the prediction of TSS, pH and TA of intact berries of Thompson seedless grapes from their NIS reflection – SoftCOM 2022, Split, Croatia

24/09/2022

2022, Publications, Tegea

Abstract Wavenumbers of high absolute value of correlation coefficient to Total Soluble Solids (TSS), pH, or Titratable Acidity (TA) were selected from reflection Fourier transform near infrared (FT-NIR) spectra of intact grape berries of the white variety Thompson Seedless. Multiple linear regression (MLR) and partial least squares (PLS) regression were applied to the spectra to construct trained regression models able to predict TSS, pH, and TA. Square Pearson’s correlation coefficient (R2) and the Mean Square Error (MSE) were used to…

Δείτε περισσότερα από τους συγγραφείς:

A. J. Daniels C. Bazinas C. Chariskou H. H. Nieuwoudt U. L. Opara V. G. Kaburlasos

Variable Selection on Reflectance NIR Spectra for the Prediction of TSS in Intact Berries of Thompson Seedless Grapes – Agronomy 2022, vol. 12, no. 9, 2113

05/09/2022

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2022, Journals, Publications, ΕΒΤΑΡ

Abstract Fourier-transform near infrared (FT-NIR) reflection spectra of intact berries of the grape variety Thompson seedless were used to predict total soluble solids (TSS) content. From an initial dataset, 12 subsets were considered by applying variable selection to extract the reflectance values at wavenumbers most correlated to the chemometrically measured TSS content. The datasets were processed by both multiple linear regression (MLR) and partial least squares (PLS) methods towards predicting the TSS content from the reflection values of each spectrum.…

Δείτε περισσότερα από τους συγγραφείς:

A. J. Daniels C. Chariskou E. Vrochidou V. G. Kaburlasos

Fuzzy lattice reasoning (FLR) for decision-making on an ontology of constraints toward agricultural robot harvest – FLINS 2022 on Machine learning, Multi agent and Cyber physical systems, Tianjin, China (Best Paper Award)

28/08/2022

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2022, Publications, Tegea

Abstract A sustainable production of high-quality agricultural products calls for personalized- rather than for massive- operations. The aforementioned (personalized) operations can be pursued by human-like reasoning applicable per case. The interest here is in agricultural grape robot harvest where a binary decision needs to be taken, given a set of ambiguous constraints represented by a Boolean lattice ontology of inequalities. Fuzzy lattice reasoning (FLR) is employed for decision making. Preliminary experimental results on expert data demonstrate the advantages of the…

Δείτε περισσότερα από τους συγγραφείς:

C. Lytridis G. Siavalas S. Theocharis T. Pachidis V. G. Kaburlasos

An Overview of End Effectors in Agricultural Robotic Harvesting Systems – Agriculture 2022, 12(8), 1240

17/08/2022

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2022, Journals, Publications, Tegea

Abstract In recent years, the agricultural sector has turned to robotic automation to deal with the growing demand for food. Harvesting fruits and vegetables is the most labor-intensive and time-consuming among the main agricultural tasks. However, seasonal labor shortage of experienced workers results in low efficiency of harvesting, food losses, and quality deterioration. Therefore, research efforts focus on the automation of manual harvesting operations. Robotic manipulation of delicate products in unstructured environments is challenging. The development of suitable end effectors…

Δείτε περισσότερα από τους συγγραφείς:

E. Vrochidou I. Kalathas T. Gkrimpizis T. Pachidis V. G. Kaburlasos V.N. Tsakalidou

Robot intelligence technology for skillful viniculture based on the lattice computing paradigm – ROBOTMEET2022, Edinburgh, Scotland

13/08/2022

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2022, Publications, Tegea

Download ROBOTMEET2022_KaburlasosSlides.pdf Download ROBOTMEET2022_KaburlasosVideo.mp4 Citation V. G. Kaburlasos, “Robot intelligence technology for skillful viniculture based on the lattice computing paradigm”, International Meet & Expo on Robot Intelligence Technology and Applications (ROBOTMEET2022), Edinburgh, Scotland, 18-20 August 2022.

Δείτε περισσότερα από τους συγγραφείς:

V. G. Kaburlasos