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Site-Specific Seed Yield Prediction of Red Fescue (Festuca rubra L.)

• Authors : Canavari, Maurizio; Vitali, Giuliano; Mattetti, Michele

Subjects: aerial images; creeping red fescue; crop color

• Source: Andreasen , C , Rasmussen , J & Bitarafan , Z 2023 , Site-Specific Seed Yield Prediction of Red Fescue (

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Site-Specific Seed Yield Prediction of Red Fescue (Festuca rubra L.) Based on Drone Imaging and Local Regression Models

• Authors : Andreasen, Christian; Rasmussen, Jesper; Bitarafan, Zahra

Subjects: article

• Source: Andreasen , C , Rasmussen , J & Bitarafan , Z 2023 , ' Site-Specific Seed Yield Prediction of Red Fescue (

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Site-Specific Seed Yield Prediction of Red Fescue (Festuca rubra L.) Based on Drone Imaging and Local Regression Models

• Authors : Christian Andreasen; Jesper Rasmussen; Zahra Bitarafan

Subjects: aerial images; crop color; creeping red fescue

• Source: Agronomy, Vol 13, Iss 2, p 316 (2023)

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Site-Specific Seed Yield Prediction of Red Fescue ( Festuca rubra L.)

• Authors : Andreasen, Christian; Rasmussen, Jesper; Bitarafan, Z. ...

Subjects: aerial images; creeping red fescue; crop color

• Source: Andreasen , C , Rasmussen , J & Bitarafan , Z 2023 , Site-Specific Seed Yield Prediction of Red Fescue (

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Seed Yield Prediction Models of Four Common Moist-Soil Plant Species in Texas

• Authors : Collins, Daniel P.; Conway, Warren C.; Mason, Corey D.

Subjects: barnyard grass; east-central Texas; jungle rice

• Source: Texas Journal of Agriculture and Natural Resources; Vol. 30 (2017); 78-86 ; 2165-1205

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Development of AI methods for seed yield prediction using RGB images: Progress Report

• Authors : Arrechea, Darwin A.; Cardoso, Juan A.

Subjects: seed characteristics; crop modelling; data collection

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Application of machine learning algorithms and feature selection in rapeseed (Brassica napus L.) breeding for seed yield

• Authors : Masoud Shahsavari; Valiollah Mohammadi; Bahram Alizadeh

Subjects: Rapeseed; Machine learning; Feature selection

• Source: Plant Methods, Vol 19, Iss 1, Pp 1-22 (2023)

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Using Machine Learning Methods Combined with Vegetation Indices and Growth Indicators to Predict Seed Yield of Bromus inermis

• Authors : Chengming Ou; Zhicheng Jia; Shoujiang Sun

Subjects: leaf nitrogen content; random forest model; remote vegetation index

• Source: Plants, Vol 13, Iss 6, p 773 (2024)

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RSM and ANN Modeling of Camelina ( Camelina sativa L. Crantz) Seed Yield as Affected by Nitrogen, Sulfur, Cow Manure, and Row Spacing

• Authors : Mohsen Yari; Asad Rokhzadi; Keyvan Shamsi

Subjects: artificial neural network; planting density; response surface methodology

• Source: Horticulturae, Vol 10, Iss 1, p 66 (2024)

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High-Resolution Flowering Index for Canola Yield Modelling.

• Authors : Fernando, Hansanee¹ (AUTHOR); Ha, Thuan¹ (AUTHOR); Attanayake, Anjika¹ (AUTHOR)

• Source: Remote Sensing. Sep2022, Vol. 14 Issue 18, pN.PAG-N.PAG. 15p.

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