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Vertical farming operators eye Peterborough region for expansion - Peterborough

Peterborough and Kawarthas Economic Development says several European producers are eyeing the region for expansion into vertical farming. An issue is finding land for a facility.

Rhonda keenanRobert lothianThomas grahamMatt andersonGuelph universitySchool of environmentalKawarthas economic developmentChemong city greensOwner matt andersonEnvironmental studiesVertical farmingChemong city greensOntario agricultureOntario farmingNtario vertical farmingEterborough and kawarthas economic development

Vertical farming operators eye Peterborough region for expansion

Peterborough and Kawarthas Economic Development says several European producers are eyeing the region for expansion into vertical farming. An issue is finding land for a facility.

Matt andersonRhonda keenanThomas grahamKawarthas economic developmentGuelph universitySchool of environmentalChemong city greensOwner matt andersonEnvironmental studiesChemong city greensOntario agricultureOntario farmingNtario vertical farmingEterborough and kawarthas economic developmentVertical farmingErtical growing

Artificial intelligence can now estimate rice yields, according to new study

Artificial intelligence can now estimate rice yields, according to new study
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Yu tanakaKazuki saitoOkayama universityAfrica rice centerInternational rice research instituteSchool of environmentalAssociate professorGraduate schoolNatural science

Estimating Rice Yield with a Convolutional Neural Network Model

The demand for rice across the world has been projected to increase considerably by 2050, thereby needing viable intensification of present croplands.

Yu tanakaKazuki saitoMegan craigConvolutional neural network modelSchool of environmentalAfrica rice centerOkayama universityInternational rice research institutePrice yieldStudy lead authorAssociate professorGraduate schoolNatural scienceAutomation industry focusDeep learning enables instantVersatile estimation

Artificial intelligence can now estimate rice

The global demand for rice is projected to rise significantly by 2050, necessitating sustainable intensification of existing croplands. Now, Japanese researchers have made significant progress by developing deep-learning algorithms that can rapidly estimate rice yield through the analysis of thousands of photographs. The model exhibited high precision across diverse conditions and cultivars, surpassing previous methods, while effectively detecting yield differences between cultivars and also with different water management practices.

Yu tanakaKazuki saitoOkayama universityInternational rice research instituteSchool of environmentalAfrica rice centerMethod of researchAssociate professorGraduate schoolNatural scienceAssociate professor yu tanakaLearning enables instantVersatile estimationRice yield using ground based