A Sustainability Assessment of the Greenseeker N Management Tool: A Lysimetric Experiment on Barley

Carolina Fabbri, Marco Napoli, Leonardo Verdi, Marco Mancini, Simone Orlandini and Anna Dalla Marta
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Carolina Fabbri: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy
Marco Napoli: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy
Leonardo Verdi: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy
Marco Mancini: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy
Simone Orlandini: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy
Anna Dalla Marta: Department of Agriculture, Food, Environment and Forestry (DAGRI)—University of Florence, Piazzale delle Cascine, 18-50144 Florence, Italy

Sustainability, 2020, vol. 12, issue 18, 1-16

Abstract: A preliminary study was conducted to analyze the sustainability of barley production through: (i) investigating sensor-based nitrogen (N) application on barley performance, compared with conventional N management (CT); (ii) assessing the potential of the Normalized Difference Vegetation Index (NDVI) at different growth stages for within-season predictions of crop parameters; and (iii) evaluating sensor-based fertilization benefits in the form of greenhouse gasses mitigation. Barley was grown under CT, sensor-based management (RF) and with no N fertilization (Control). NDVI measurements and RF fertilization were performed using a GreenSeeker™ 505 hand-held optical sensor. Gas emissions were measured using a static chamber method with a portable gas analyzer. Results showed that barley yield was not statistically different under RF and CF, while they both differed significantly from Control. Highly significant positive correlations were observed between NDVI and production parameters at harvesting from the middle of stem elongation to the medium milk stage across treatments. Our findings suggest that RF is able to decrease CO 2 emission in comparison with CF. The relationship between N fertilization and CH 4 emission showed high variability. These preliminary results provide an indication of the benefits achieved using a simple proximal sensing methodology to support N fertilization.

Keywords: nitrogen management; precision farming; static chambers; GHGs (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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