Dataset of photosynthesis and photosynthetic factors measurements of greenhouse tomato
Jorge Manjarrez Sánchez, Gerardo Martinez-Carrillo
Abstract
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Jorge Manjarrez Sánchez, Gerardo Martinez-Carrillo
Abstract
Open-access reader
This article presents a set of photosynthetic responses and related environmental variables from greenhouse tomato plants (Lycopersicum esculentum). The dataset was obtained by direct in situ measurement of functional leaves of 100 different plants with a portable photosynthesis system. The measurements were taken for six hours at different time intervals in 16 different days during the cycle of November 2019 to January 2020. This dataset can be used to understand the physiology of greenhouse tomato plants and for the design of photosynthesis forecasting models. It is also useful in precision agriculture and for designing automatic controllers for optimal temperature, humidity, and CO2 enrichment, with the purpose of maximizing productivity and avoiding waste of resources. Additionally, this dataset can be used for research in time series analysis.
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This article presents a set of photosynthetic responses and related environmental variables from greenhouse tomato plants (Lycopersicum esculentum). The dataset was obtained by direct in situ measurement of functional leaves of 100 different plants with a portable photosynthesis system. The measurements were taken for six hours at different time intervals in 16 different days during the cycle of November 2019 to January 2020. This dataset can be used to understand the physiology of greenhouse tomato plants and for the design of photosynthesis forecasting models. It is also useful in precision agriculture and for designing automatic controllers for optimal temperature, humidity, and CO2 enrichment, with the purpose of maximizing productivity and avoiding waste of resources. Additionally, this dataset can be used for research in time series analysis.
Key concepts: Greenhouse, Photosynthesis, Humidity, Environmental science, Agricultural engineering, Agriculture, Computer science, Productivity