README file
Data Set Title: “An open access dataset of dynamic nitrogen fertigation guided by the green vegetation index”
Data Set Author: Vito Aurelio Cerasola (University of Bologna), ORCID 0000-0002-8565-8236; Stefano Bona (University of Padova), ORCID 0000-0002-8023-0687; Daniele Borsato (University of Padova); Luca Gavioli (University of Bologna); Gaia Moretti (University of Bologna), ORCID 0009-0003-8767-9270; Luigi Manfrini (University of Bologna), ORCID 0000-0003-4776-0608; Giuseppina Pennisi (University of Bologna), ORCID 0000-0001-9377-4811; Francesco Orsini (University of Bologna), ORCID 0000-0001-6956-7054; Enrico Buscaroli (University of Bologna), ORCID 0000-0002-8414-0814; Paolo Sambo (University of Padova), ORCID 0000-0003-4348-8838; Giorgio Gianquinto (University of Bologna), ORCID 0000-0002-6548-5526
Data Set Contact Person: Vito Aurelio Cerasola (University of Bologna), ORCID 0000-0002-8565-8236, vito.cerasola@unibo.it  
Data Set License: this data set is distributed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, https://creativecommons.org/licenses/by/4.0/  
Publication Year: 2025
Project Info: 
•	FrontAg Nexus (Impact of Climate-Smart & Water-Saving Frontier Agriculture on WEFE Nexus in Arid Mediterranean Regions), funded by European Union, PRIMA Programme, Grant Agreement num. 2242; https://frontagnexus.eu/. 
•	Piano Nazionale di Ripresa e Resilienza (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022, Agritech National Research Center (https://agritechcenter.it/it/).
Data set Contents
The data set consists of: 
•	1 quantitative data file saved in .csv format
“Dataset_Dynamic_N_Fertigation_OA.csv”
•	1 README file saved in .rtf format
“README_Dynamic_N_Fertigation_OA.rtf”
Data set Documentation
Abstract
The following dataset was used for the publication "Exploring dynamic nitrogen (N) fertigation guided by multispectral sensors: a sustainable optimization of N fertilization in processing tomato" (DOI doi.org/10.1016/j.scienta.2025.114124). The dataset includes the data collected from the on-field validation of different dynamic nitrogen (N) fertilisation strategies in processing tomato cultivation guided by a multispectral sensor. The experiment was carried out in Bologna (BO, Italy) in 2023, where five fertilization strategies (including a well fertilized control with 180 kg N ha-1) where four times replicated and randomized in the experimental field according to a complete randomized design. The reader is invited to read the specific published paper to discover in detail the different fertilization strategies. The data were generated in the framework of the “FrontAg Nexus” project and also received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022) within the Agritech National Research Center.
Content of the file
The file Dataset_Dynamic_N_Fertigation_OA.csv contains one sheet reporting the different variables collected at the harvest of the tomato crop per each observation (the experimental plot): each row represents one experimental unit (a plot measuring 5 m x 4 m), while Each column represents the specific variable measured at the harvest. The first row report the name of the column, including the treatment, replicate, and variable collected, while the first column indicate the different fertilization strategies, and the second column the different replicate (from letter a to letter d).
File specifics
The file is in .csv format and can be used on several software (excel, R, Python, Matlab). The .csv file has the following specifics:
•	Character set UTF-8
•	Field delimiter « ; » (semicolon)
Notes 
The data are presented in the following publication:
Cerasola, V. A., Bona, S., Borsato, D., Gavioli, L., Moretti, G., Manfrini, L., Pennisi, G., Orsini, F., Buscaroli, E., Sambo, P., Gianquinto, G. (2025). Exploring dynamic nitrogen (N) fertigation guided by multispectral sensors: a sustainable optimization of N fertilization in processing tomato. Scientia Horticulturae, 345, 114124. https://doi.org/10.1016/j.scienta.2025.114124 
Methodologies 
A crop of processing tomato was grown in 2023 at the experimental farm of the University of Bologna located in Cadriano (BO, Italy). A complete randomized experiment with 4 replicates was conducted, where five nitrogen management strategies were compared. The well fertilized control N100, where 180 kg ha-1 of N was supplied, was compared with four dynamic N fertilization strategies guided by a multispectral sensor. In these dynamic strategies, the N fertilizer was supplied whenever the green vegetation index (GVI) fell below a given threshold, optimizing the optimal moment to supply the fertilizer via fertigation. Data on different agronomic variables were measured at the harvest (at 100 days after the transplant), where 8 plants were sampled in each experimental plot. Physiological measurements were taken 67 days after the transplant on three plants per experimental plot, while the lycopene was measured on a subsample from 500 g of homogenized tomatoes randomly selected in each experimental plot.
List of variables 
Parameter	Description	
treatment	Treatments with different nitrogen fertilization levels:
-	N100 (the 100% of the crop N requirements, calculated in 180 kg ha-1 of N, is supplied via fertigation supplied at 7 times)
-	N_SPY (N supplied when the GVI of the N_SPY is below the 90% of the GVI of N180)
-	N_THR (N supplied when the GVI is below a critical threshold. Read the paper to find more details)
-	N_THR_N30 (The same of N_THR but the N calculated to be supplied is reduced by 30%)
-	N_SPY_EVO (N supplied when the GVI is below a threshold developed using GVI historical data of a well-fertilized plot)	
replicate	four replicates for each analyzed sample, named “a”, “b”, “c”, “d”	
N_supplied	Total N supplied in kg N ha-1	
N_saved	Total N saved in percentage (%)	
biomass	Total green biomass (leaves and stems, t ha-1) at the harvest	
mkt_y	Marketable yield (t ha-1)	
mkt_n	Marketable fruits number (N° plant-1)	
mkt_fw	Marketable fruit weight (g fruit-1)	
tot_y	Total yield (t ha-1)	
tot_n	Total fruits number (N° plant-1)	
tot_fw	Total fruits weight (g fruit-1)	
BER_weight	Total weight of fruits affected by blossom end rot (BER, t ha-1)	
BER_n	Number of fruits affected by BER (N plant-1)	
BER_i	Incidence of fruits affected by BER on the total weight (%)	
green_weight	Total weight of unripe (i.e., green) fruits (t ha-1)	
green_n	Number of unripe fruits (N° plant-1)	
green_i	Incidence of unripe fruit on the total weight (%)	
rest_weight	Remaining non-marketable fruits in weight (t ha-1)	
rest_n	Number of remaining non-marketable fruits (N° plant-1)	
rest_i	Incidence of remaining non-marketable fruits on the total weight (%)	
HI	Harvest index, calculated as the ratio between the marketable production on the total biomass (including leaves, stem, marketable and non marketable fruits), expressed in percentage (%)	
NUE	Nitrogen Use Efficiency, calculated as the ratio between the marketable yield and the kg of N supplied per hectare (t of fruits kg-1 N)	
brix	Total soluble solids measured with digital refractometer	
lycopene	Lycopene content in the fresh fruit weight (FW) expressed in mg kg-1 FW	
dm	Dry matter content, e.g., the percentage of dry weight on the fresh weight (%)	
A	Net photosyntesys (μmol m-2 s-1)	
Emm	Transpiration (mmol m-2 s-1)	
gsw	Stomatal conductance (mol m-2 s-1)