Hydroponic greenhouse-grown and store-bought cultivars of tomato (cherry and beefsteak), cucumbers, bibb lettuce, and arugula were investigated to see if they could be distinguished based on sensory qualities and phytonutrient composition. Only the more dominant sensory criteria were sufficiently robust to distinguish between cultivars and could form the core of a consolidated number of criteria in a more discriminating sensory evaluation test. Strong determinants for cultivar selection within each crop included the following: mineral analysis (particularly Cu, Fe, K, Mg, and P); total carotenoids (particularly
Modern agriculture aims to maximize yield and quality of plants with efficient use of resources and labor. Growing plants in a soilless environment on a supportive substrate (e.g., coir, peat, or rockwool) conserves water, nutrients, and space and is defined as hydroponics [
Important considerations for hydroponically grown greenhouse (GH) produce are microclimate and fertigation components that could potentially affect various plant characteristics. It is our contention that if these are held constant, selection of nutritionally optimal cultivars can be performed, based on a combination of sensory and phytonutrient characteristics. The latter includes biochemical composition and proximate traits. Fruits and vegetables are rich in phytonutrients including anthocyanins, carotenoids, minerals, organic acids, polyphenolics, and vitamins (e.g., vitamins C and E) [
Four salad crops were examined in this study including tomato, cucumber, and the leafy greens arugula and bibb lettuce. Tomato consumption in Canada in 2007 was 87 g/capita/d or 32 kg/capita/yr [
Few studies have been conducted on the phytonutrient composition of hydroponically produced vegetables. As these are grown under defined conditions of light, temperature, and fertigation, the nutritional content of specific cultivars may not vary widely from crop to crop. Although there may be some differences in nutritional composition related to season, differences are primarily related to light effects [
Selection of the most pleasing and nutritious cultivars for each food species would contribute to maximum consumer satisfaction and health. Following sensory characterization and phytonutrient analysis, a method was developed to highlight the most revealing factors for high-throughput cultivar selection within each species (cherry and beefsteak tomato, cucumber, arugula, and bibb lettuce). A range of complex statistical methods was considered. Among the methods examined for data classification and mining were partial least squares or projection to latent structures (PLS), principal component analysis (PCA), variable clustering, classification trees, linear and quadratic discriminant analysis, neural networks, and support vector machines [
So the objectives of this research were to (1) utilize taste panels to assess the appearance, taste, and texture acceptability of different cultivars of GH tomato (cherry and beefsteak types), cucumber, and two leafy green crops (arugula and bibb lettuce), (2) compare the phytonutrient composition of different cultivars of these fresh GH crops with store-bought (SB) produce, and (3) identify the most revealing factors (including sensory and phytonutrient data) that could be used in a high-throughput screening of a large number of cultivars, within each crop species, to expediently identify the most appealing and nutritious ones.
Six cherry tomato cultivars including ‘Apero’, ‘Favorita’, and ‘Juanita’ were grown hydroponically in the greenhouse. Seeds of ‘Apero’ and ‘Favorita’ were bought from Johnny’s Selected Seeds (ME, USA) while seeds of ‘Juanita’ were bought from De Ruiter Seeds (Monsanto; Montreal, QC, Canada). Fruit of three cherry tomato cultivars were purchased from local stores and tested under their trade names: Jardino (product of EU; from an IGA store on Louis-Menard St.), Fruiterie (product of Mexico; from Inter-Marche on Cote Vertu Blvd.), and Cherries (product of Mexico; from Inter-Marche on Saint Laurence St.).
Four cultivars of beefsteak tomato including ‘Arbason’, ‘Caramba’, ‘Geronimo,’ and ‘Trust’ were grown hydroponically in the greenhouse. Seeds of ‘Arbason,’ ‘Geronimo,’ and ‘Trust’ were bought from Johnny’s Selected Seeds and seeds of ‘Caramba’ were bought from De Ruiter Seeds. Fruit of three beef steak tomatoes were bought from local grocery stores and tested under their trade names: Kaliroy (produced in Mexico; from IGA on Louis-Menard St.), BionatureL (produced in Mexico; from Loblaws on Jean-Talon St.), and BionatureP (produced in Mexico; from Provigo on St. Urbain St.). ‘Diva’ Mini Cucumber was hydroponically grown in the greenhouse from seed bought from Johnny’s Selected Seed. Three SB cultivars were tested under their trade names: Cool Cukes, Lebanese, and Mini cucumber.
Four cultivars of arugula and three of bibb lettuce were evaluated. The arugula ‘Astro’ was grown hydroponically from seeds bought from Johnny’s Selected Seeds. Three arugula were SB and tested under their trade names: ADO (bought from Adonis) and BW and PRO (bought from Provigo). The bibb lettuce ‘RexMT0’ was grown in the greenhouse from seeds purchased from Johnny’s Selected Seeds. Two store-bought bibb lettuce were tested under their trade names: ADO (bought from Adonis) and IGA (bought from IGA).
Hydroponically grown cherry tomato, cucumber, and leafy vegetables were stored in a household fridge (4°C) for 0, 3, and/or 6 d (based on produce availability). This enabled comparison of “fresh” and cold-stored produce.
Taste tests were carried out at McGill University in a taste test laboratory (McGill University Research Ethics Board Approval # 953-1110). Fifty persons were recruited and went through two rounds of training, and then individuals with consistent ratings were selected. Panelists included 25 males and females from 18 to 52 years of age with no known allergies to any of the tested fruits and vegetables. They tested hydroponic greenhouse grown and store-purchased produce, including tomato, cucumber, arugula, and lettuce. Before each taste test session, panelists were instructed regarding terminology, test procedures, and the nature of the samples. The sensory analysis taste test for each crop was conducted over several sessions during 1 d, with a variable number of 10–20 panelists per session and results were subjected to statistical analysis.
Hydroponically grown and SB tomato, cucumber, arugula, and bibb lettuce were rinsed well under tap water and air-dried for at least 15 min. Tomatoes were cut into thin round slices about 6 mm thick and then into halves, just before serving. Cucumber samples were cross-sliced (2-3 mm) just before serving. Panelists were served a plate containing, in the following order, 2-3 whole fruit of each cherry tomato cultivar, 2-3 slices of each cucumber cultivar, 2-3 half slices of each beefsteak tomato cultivar, and finally 2-3 leaves of each leafy green cultivar. Panelists were individually supplied with plain soda crackers and directed to have a bite after sampling and then sip some water to rinse their palate between each sample. More samples were given upon request and retasting was conducted when necessary.
Panelists scored their responses onto a print-out paper sheet that was prepared specifically for each crop. After sensory evaluation, panelists were asked to answer demographic questions (multiple choice), which included age, gender, and frequency of fresh vegetable consumption. Tomato ripeness, sweetness/saltiness, juiciness, and general acceptability of cherry or beefsteak varieties were scored on 9-point hedonic scales, where 9: ripe, 5: neutral, 1: unripe. The same scale was used for sweetness/saltiness and responses were scored: 1: salty; 5: not salty or sweet; 9: sweet. Juiciness was scored on a 9-point score where 1: dislike; 5: neutral; and 9: like. General acceptability also was given scores from 1 to 9, where 1: dislike and 9: like.
Cucumber sensory characteristics including flesh color and firmness, aroma of the fruit, and flesh taste sweetness/bitterness traits were scored on a 9-point scale, where 1: dislike and 9: like for flesh color, firmness, and fresh aroma of the fruit. Sweetness/bitterness were scored on a 9-point scale, where 1: bitter, 5: not bitter or sweet, and 9: sweet. Arugula sensory characteristics including green/grassy, intensity of bitterness, astringent, and overall liking were rated on a 9-point hedonic scale, where 1 was the lowest and 9 was the strongest taste and liking. Bibb lettuce was evaluated for color, sogginess/freshness, off-odor, and overall quality. Sensory evaluation of lettuce was done using the same hedonic 9-point scale.
Greenhouse and SB produce were hand-rinsed under running tap water and then blotted onto paper towels and air-dried for 1-2 h. Samples consisted of 1 g cross-sectional slices from the middle of each of 7–12 whole fruit or up to 20 leaves of leafy vegetables. These were incubated overnight in 3 mL nitric acid (trace metal analysis grade, Fisher Scientific Co., ON, Canada) in a 10 mL Oak Ridge centrifuge tube (Thermo Scientific, NY, USA) placed in a fume hood. On the following day, samples were digested using a heating block (Thermolyne heater type 16500 Dri Bath model DB16525; Thermolyne, Dubuque, IA 52001, USA). The samples were heated to 105°C until no nitrous oxide gases (brown gases) were evolved. Samples were diluted (1 : 4) with Type-1 water (18 Ωcm) and mixed thoroughly (flipping tubes over) prior to injection into the ICP-OES apparatus for analysis. Control elemental stock standard solution (J. T. Baker, St. Louis, MO, USA) was used to calibrate the instrument before sample injection. The inductively coupled argon plasma optical emission spectrometer (ICP-OES) used for mineral analysis in this study was a model VISTA-MPX CCD Simultaneous ICP-OES (Varian Australia PTY Ltd., Australia). The settings were as follows: power 1.2 kW, plasma flow 15 Lmin−1, argon pressure 32 L min−1 (600 kPa), nebulizer flow 0.75 Lmin−1, auxiliary flow 1.5 L min−1, pump rate 15 rpm, viewing height 10 mm, replicate reading time 10 s, and instrument stabilization delay 15 s [
Plant samples (about 1 kg of beef-steak, cherry tomato, or cucumber and 0.5 kg of arugula and bibb-lettuce leafy vegetables; all randomly selected, 3 replicates/variety) were homogenized and cut into thin slices (0.5–1 cm) and fast-frozen on aluminum plates (diameter of 25 cm) using liquid nitrogen and then freeze-dried at −60 to −70°C for up to 4 d in a freeze-dryer (Christ Freeze-Dryer, Gamma 1-16 LSC, Osterode, Germany). Freeze-dried samples (2 samples/replicate) were ground into a fine powder in liquid nitrogen and stored in a −80 C Freezer (Thermo Electron Corporation, OH, USA). Sample weights were recorded before (fresh weight) and after (dry weight) freeze-drying to calculate the sample dry matter content. Freeze-dried samples were used for phytonutrient analyses.
About 100 mg of freeze-dried powder was extracted with 2 mL of 90% methanol (MeOH). Samples were vortexed at maximum speed for 60 s, sonicated (Branson 2200, Branson Ultrasonics Corporation, CT, USA) for 30 min, and centrifuged at 3,500 rpm for 15 min at 4°C. Supernatants were collected into 15 mL Falcon tubes. The remaining pellet was reextracted with 1 mL of 90% MeOH and supernatants were combined. Crude extract was used to measure total soluble phenolics (Folin Ciocalteu or FC test), the antioxidant scavenging capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH), and 2,2′-azino-bis-3-ethylbenzothiazoline-6-sulphonic acid (ABTS) (hydrophilic phase) [
Total extractable phenolic contents of GH or SB produce were evaluated with Folin-Ciocalteu (FC) reagent according to [
ABTS (7 mM) stock solution was prepared in 18 Ωcm−1 water. Radical cation of ABTS (
Radical scavenging capacity assay was performed as described by [
Total anthocyanin content was extracted following the method previously described [
Total carotenoids were extracted using hexane as described by [
Total carotenoids were assayed following the method of [
The carotenoid compounds in freeze-dried produce samples were extracted using a modified method from [
Solvents and the HPLC running method under isocratic conditions were as described by [
The organic acids, ascorbic, citric, fumaric, and malic, were determined following [
About 20 mg of freeze-dried sample was added to 5 mL of 1 M HCl and placed into a preheated shaker water bath at 100°C for 2 h [
Freeze-dried samples were analyzed for soluble and insoluble fiber using the method of AOAC (1995) [
Statistical analysis was performed using the statistical analysis systems (SAS) software (version 9.2, 2009). Analysis of variance (ANOVA) was used to detect significant differences between varieties for individual attributes. Sensory evaluations were analyzed using the general linear model (GLM) procedure of SAS (Version 9.2, Cary, NC, USA). The data were first analyzed to determine panelist’s age and gender effects in a randomized complete block design (RCBD). Least square means of panelists’ responses were separated when effects were significant in the ANOVA table (
Phytonutrients were analyzed using the GLM procedure of SAS (Version 9.2, Cary, NC, USA, 2011). Analysis of variance (ANOVA) was used to differentiate between main factors for cultivars within each crop and between crops for individual phytonutrient characteristics. The data were first analyzed for normality using PROC UNIVARIATE. When effects were significant in the ANOVA table (
Identification of the dominant variables was done after running the variable cluster analysis (VARCLUS), principal component analysis (PCA), and partial least square (PLS) statistical analysis. Based on the hierarchical clustering patterns, classification of variables in nonoverlapping clusters was estimated by analyzing the correlation or the covariance matrices subsequently.
Cluster analysis is a separation method that divides the data set into a number of groups or clusters (tree dendrogram; tree leaves and leaflets) based on similarity. The data points within each group (cluster; one major leaf with one or several leaflets) are more similar to one another than they are to the data points within other clusters. The distance between clusters on the
Then PCA and PLS were run to confirm and visualize in space the cluster (group) classification of variables based on the weight of each variable in relation to the variance (PLS) and covariance (PLS and PCA) matrices [
Correlation loading plot is a circular graph showing the variation accounted for by each extracted factor (of one or more variable(s)) and is generated by partial least square (PLS) analysis. The amount of variation in the data points is relative to their distance from the origin. So, the outside circle shows the data points that are most similar and grouped together (highly correlated). Each successive circle working from the outside to the inside indicates decreasing levels of explained variation. The correlation between any two variables is relative to the length of the projection of the point corresponding to one variable on a line through the origin passing through the other variable. The sign of the correlation (negative or positive) corresponds to which side of the origin the projected point falls on.
Multidimensional preference analysis is another mapping technique for the two principal components that show most of the variance and is generated by the principal component analysis (PCA). A biplot displays the independent and dependent variables in a single plot by projecting them onto the plane that accounts for the most variance. Points that are tightly clustered and point in the same direction share the most attributes in common. Pointing in the opposite direction suggests negative correlation. The longer the projection, the relatively more important the variable.
For data mining and discriminant analysis, statistical analysis was done on two steps: (1) significant variation among the 34 variables was identified (based on MANOVA table) and the nondiscriminant variables were identified for a drop-list. (2) Variable clustering analysis was done according to the contribution of each variable to the overall variance using the VARCLUS procedure. Then, their possible interrelationships were studied through visualization of a network structure using both principal component analysis (PCA) and partial least squares regression (PLS).
Data presented in Table
LS mean score values
Cultivar | Ripeness |
Sweetness/saltiness | Juiciness | Mouth feeling | General acceptability |
---|---|---|---|---|---|
Cherry tomato | |||||
|
|||||
Apero | 8.36 ± 0.183 |
8.08 ± 0.197 |
8.27 ± 0.185 |
8.02 ± 0.209 |
8.22 ± 0.204 |
Favorita | 8.15 ± 0.183 |
7.50 ± 0.192 |
7.81 ± 0.185 |
7.35 ± 0.209 |
7.83 ± 0.204 |
Juanita | 8.11 ± 0.183 |
6.94 ± 0.193 |
6.64 ± 0.196 |
6.96 ± 0.222 |
6.94 ± 0.215 |
Fruterie | 7.99 ± 0.183 |
7.49 ± 0.198 |
8.31 ± 0.185 |
7.12 ± 0.225 |
7.42 ± 0.220 |
Jardino | 6.81 ± 0.197 |
5.80 ± 0.192 |
6.07 ± 0.218 |
5.59 ± 0.226 |
5.82 ± 0.215 |
|
|||||
Beefsteak tomato | |||||
|
|||||
Arbason | 8.27 ± 0.287 |
5.37 ± 0.292 |
6.27 ± 0.280 |
5.82 ± 0.297 |
5.96 ± 0.303 |
Caramba | 6.72 ± 0.287 |
5.72 ± 0.292 |
6.87 ± 0.280 |
6.07 ± 0.297 |
6.26 ± 0.303 |
Geronimo | 7.77 ± 0.287 |
5.77 ± 0.292 |
6.32 ± 0.280 |
6.12 ± 0.297 |
6.41 ± 0.303 |
Trust | 7.77 ± 0.287 |
5.82 ± 0.292 |
7.07 ± 0.280 |
6.62 ± 0.297 |
6.66 ± 0.303 |
CHS | 7.92 ± 0.287 |
6.57 ± 0.292 |
7.37 ± 0.280 |
6.42 ± 0.297 |
6.71 ± 0.303 |
del Campo | 6.17 ± 0.287 |
6.02 ± 0.292 |
6.47 ± 0.280 |
6.22 ± 0.297 |
6.01 ± 0.303 |
Plain Jane | 4.97 ± 0.287 |
5.17 ± 0.292 |
5.32 ± 0.280 |
5.32 ± 0.297 |
4.91 ± 0.303 |
There was no effect of panelist gender or age on cherry tomato ripening classification. No differences occurred in ripeness score between the GH cherry tomatoes ‘Apero,’ ‘Favorita,’ ‘Juanita,’ and the SB Fruiterie while SB Jardino was scored as less ripe than the others. Sweetness or saltiness of tomato is a trait related to soluble sugars and mineral content of tomato [
No differences in sensory traits were found between GH beefsteak tomato cultivars (Table
Results of sensory characterization of cucumber cultivars were presented in Table
LS mean score values
Cultivar | Flesh color |
Firmness | Aroma | Sweetness/bitterness |
---|---|---|---|---|
Diva | 7.50 ± 0.253 |
7.81 ± 0.260 |
6.77 ± 0.319 |
6.80 ± 0.276 |
Lebanese | 5.99 ± 0.267 |
6.69 ± 0.304 |
6.47 ± 0.308 |
6.14 ± 0.304 |
Mini Cucumber | 5.61 ± 0.257 |
5.54 ± 0.276 |
6.33 ± 0.324 |
5.51 ± 0.305 |
Results of sensory characterization of arugula (Rocket salad) cultivars are presented in Table
LS mean score values1 ± SE of panelist responses to different sensory traits of greenhouse-grown (‘Astro’) and store-bought (ADO, BW, and PRO) arugula.
Cultivar | Overall quality |
Intensity of bitterness | Green/grassy | Astringency |
---|---|---|---|---|
Astro | 6.07 ± 0.262 |
6.40 ± 0.378 |
7.47 ± 0.225 |
6.40 ± 0.309 |
ADO | 6.92 ± 0.255 |
4.27 ± 0.370 |
7.42 ± 0.229 |
4.35 ± 0.308 |
BW | 6.91 ± 0.258 |
4.09 ± 0.402 |
6.74 ± 0.212 |
3.61 ± 0.315 |
PRO | 6.62 ± 0.274 |
5.10 ± 0.369 |
6.63 ± 0.231 |
4.07 ± 0.288 |
Overall quality and freshness were not different between GH ‘RexMT0’ and the SB bibb lettuce cultivars and all had acceptable odor (Table
LS mean score values1 ± SE of panelist responses to different sensory traits of greenhouse-grown (‘RexMT0’) and store-bought (ADO and IGA) bibb lettuce.
Cultivar | Overall quality |
Color | Sogginess/freshness | Off-odor |
---|---|---|---|---|
RexMT0 | 6.75 ± 0.237 |
7.19 ± 0.212 |
3.23 ± 0.348 |
1.59 ± 0.163 |
ADO | 6.51 ± 0.235 |
5.86 ± 0.226 |
4.32 ± 0.325 |
1.67 ± 0.170 |
IGA | 7.23 ± 0.212 |
7.11 ± 0.198 |
3.67 ± 0.311 |
1.38 ± 0.159 |
Least squares means results for the macro mineral (Ca, Mg, K, and P; g/100 g FW) contents of three hydroponically grown GH and three SB cherry tomato varieties are presented in Table
LS mean values1 of macrominerals (Ca, K, Mg, and P; g/100 g DW) and microminerals (Cu, Fe, and Na; mg/100 g DW) in hydroponically grown (GH) and store-bought (SB) cherry and beefsteak tomato, cucumber, arugula, and lettuce cultivars.
Crops | Varieties | Macrominerals | Microminerals | |||||
---|---|---|---|---|---|---|---|---|
Ca | K | Mg | P | Cu | Fe | Na | ||
|
||||||||
GH | Apero | 0.08 |
5.51 |
0.40 |
1.14 |
1.93 |
13.81 |
65.90 |
GH | Apero-6 |
0.09 |
6.10 |
0.41 |
1.11 |
1.72 |
12.35 |
73.86 |
GH | Favorita | 0.03 |
2.92 |
0.15 |
0.50 |
0.71 |
5.48 |
23.98 |
GH | Favorita-6 | 0.03 |
2.95 |
0.16 |
0.50 |
0.72 |
5.12 |
26.23 |
GH | Juanita | 0.07 |
4.88 |
0.31 |
1.03 |
1.37 |
10.08 |
38.13 |
GH | Juanita-6 | 0.08 |
5.25 |
0.35 |
1.14 |
1.61 |
13.86 |
47.54 |
SB | Jardino | 0.08 |
1.20 |
0.11 |
0.16 |
0.51 |
1.35 |
20.96 |
SB | Cherries | 0.17 |
2.33 |
0.24 |
0.54 |
1.45 |
7.20 |
52.24 |
SB | Fruiterie | 0.15 |
3.21 |
0.18 |
0.42 |
0.17 |
4.27 |
19.83 |
|
||||||||
Mean | 0.09 |
3.82 |
0.26 |
0.73 |
1.13 |
8.17 |
40.96 | |
|
||||||||
|
||||||||
GH | Arbason | 0.11 |
3.50 |
0.28 |
0.57 |
1.16 |
6.97 |
23.81 |
GH | Caramba | 0.14 |
7.94 |
1.07 |
0.22 |
6.67 |
22.04 |
144.00 |
GH | Geranimo | 0.23 |
5.49 |
0.67 |
0.22 |
4.92 |
15.34 |
90.58 |
GH | Trust | 0.21 |
5.80 |
0.64 |
0.30 |
4.66 |
12.68 |
75.23 |
SB | Kaliroy | 0.10 |
1.64 |
0.07 |
0.24 |
0.27 |
1.69 |
19.26 |
SB | BionatureL | 0.11 |
1.39 |
0.07 |
0.22 |
0.02 |
1.63 |
18.04 |
SB | BionatureP | 0.11 |
1.79 |
0.06 |
0.16 |
0.04 |
1.34 |
11.97 |
|
||||||||
Mean | 0.14 |
3.94 |
0.41 |
0.28 |
2.53 |
8.81 |
54.70 | |
|
||||||||
|
||||||||
GH | Diva | 0.20 |
2.70 |
0.14 |
0.53 |
0.65 |
3.27 |
24.51 |
GH | Diva-3 | 0.23 |
2.52 |
0.24 |
0.75 |
0.61 |
3.51 |
40.46 |
GH | Diva-6 | 0.22 |
2.70 |
0.24 |
0.85 |
0.75 |
4.12 |
38.99 |
SB | Cool Cukes | 0.18 |
1.56 |
0.11 |
0.25 |
0.11 |
1.28 |
15.60 |
SB | Lebanese | 0.25 |
2.09 |
0.14 |
0.39 |
0.04 |
2.68 |
20.55 |
SB | Mini Cucumber | 0.24 |
1.96 |
0.11 |
0.32 |
0.12 |
2.48 |
16.01 |
|
||||||||
Mean | 0.22 |
2.25 |
0.17 |
0.52 |
0.38 |
2.89 |
26.02 | |
|
||||||||
|
||||||||
GH | Astro | 2.21 |
3.61 |
0.28 |
0.62 |
0.47 |
6.23 |
70.25 |
GH | Astro-6 | 1.45 |
3.80 |
0.34 |
0.54 |
0.31 |
4.06 |
49.35 |
SB | ADO | 2.18 |
2.67 |
0.42 |
0.64 |
0.69 |
10.89 |
573.67 |
SB | BW | 1.57 |
2.67 |
0.29 |
0.61 |
1.22 |
10.63 |
637.72 |
SB | PRO | 1.62 |
2.45 |
0.30 |
0.38 |
0.47 |
10.00 |
459.03 |
|
||||||||
Mean | 1.81 |
3.04 |
0.33 |
0.56 |
0.63 |
8.36 |
358.00 | |
|
||||||||
|
||||||||
GH | RexMT0 | 0.42 |
3.90 |
0.24 |
0.96 |
0.71 |
5.34 |
31.45 |
GH | RexMT0-6 | 0.35 |
3.26 |
0.16 |
0.76 |
0.52 |
3.16 |
36.41 |
SB | ADO | 0.46 |
3.71 |
0.31 |
1.40 |
1.85 |
13.14 |
243.60 |
SB | IGA | 0.42 |
4.08 |
0.18 |
0.84 |
0.39 |
3.79 |
37.66 |
|
||||||||
Mean | 0.41 |
3.74 |
0.22 |
0.99 |
0.87 |
6.36 |
87.28 |
Levels of microminerals Cu, Fe, and Na (Table
LS mean values1 of microminerals, including Al, As, Cd, Cr, Pb, Se, and Zn (mg/100 g DW) of greenhouse-grown (GH) and store-bought (SB) cherry tomato, beefsteak tomato, cucumber, arugula, and bibb lettuce.
Crops | Varieties | Al | As | Cd | Cr | Pb | Se | Zn |
---|---|---|---|---|---|---|---|---|
|
||||||||
GH | Apero | 2.51 |
0.24 |
0.02 |
0.05 |
0.29 |
11.32 |
4.90 |
GH | Apero-6 |
3.57 |
1.29 |
0.04 |
0.08 |
0.34 |
0.79 |
4.35 |
GH | Favorita | 2.30 |
0.32 |
— | 0.05 |
0.25 |
41.64 |
1.96 |
GH | Favorita-6 | 3.46 |
0.03 |
— | 0.04 |
0.27 |
0.94 |
1.87 |
GH | Juanita | 3.70 |
0.86 |
0.02 |
0.06 |
0.23 |
36.73 |
4.26 |
GH | Juanita-6 | 3.05 |
0.67 |
0.01 |
0.05 |
0.21 |
0.91 |
5.03 |
SB | Jardino | 10.22 |
— |
— | 0.03 |
0.20 |
24.59 |
1.16 |
SB | Cherries | 34.91 |
— | — | 0.06 |
0.16 |
— | 2.73 |
SB | Fruiterie | 24.67 |
— | — | 0.03 |
0.32 |
23.10 |
1.18 |
|
||||||||
Mean | 9.82 |
0.57 |
0.02 |
0.05 |
0.25 |
17.50 |
3.05 | |
|
||||||||
|
||||||||
GH | Arbason | 4.31 |
0.41 |
0.01 |
0.12 |
0.17 |
— | 2.70 |
GH | Caramba | 3.10 |
— | — | 0.08 |
0.23 |
19.93 |
43.29 |
GH | Geronimo | 2.32 |
— | — | 0.04 |
0.37 |
23.68 |
29.74 |
GH | Trust | 2.23 |
— | — | 0.12 |
0.13 |
— | 28.39 |
SB | Kaliroy | 13.96 |
— | — | 0.16 |
0.17 |
— | 0.71 |
SB | BionatureL | 11.33 |
— | — | 0.14 |
0.22 |
— | 0.68 |
SB | BionatureP | 16.95 |
— | — | 0.18 |
0.11 |
— | 0.50 |
|
||||||||
Mean | 7.74 |
0.41 |
0.01 |
0.12 |
0.20 |
21.81 |
15.15 | |
|
||||||||
|
||||||||
GH | Diva | 28.55 |
— | — | 0.04 |
0.19 |
— | 2.83 |
GH | Diva-3 | 2.72 |
0.54 |
0.03 |
0.06 |
0.14 |
32.99 |
3.41 |
GH | Diva-6 | 2.11 |
0.38 |
— | 0.03 |
0.09 |
28.60 |
4.02 |
SB | Cool Cukes | 10.24 |
— | — | 0.03 |
0.15 |
21.66 |
1.21 |
SB | Lebanese | 19.82 |
— | — | 0.03 |
0.16 |
24.53 |
1.73 |
SB | Mini Cucumber | 16.95 |
— | — | 0.02 |
0.19 |
13.80 |
1.08 |
|
||||||||
Mean | 13.40 |
0.50 |
0.03 |
0.04 |
0.15 |
24.32 |
2.38 | |
|
||||||||
|
||||||||
GH | Astro | 5.76 |
0.25 |
— | 0.02 |
0.34 |
28.36 |
3.44 |
GH | Astro-6 | 5.54 |
0.15 |
— | — | — | — | 2.36 |
SB | ADO | 13.38 |
0.56 |
— | 0.03 |
0.42 |
34.77 |
6.74 |
SB | BW | 11.26 |
0.14 |
— | 0.04 |
0.47 |
40.09 |
13.07 |
SB | PRO | 9.80 |
— | 0.04 |
— | 0.47 |
22.92 |
3.13 |
|
||||||||
Mean | 9.15 |
0.27 |
0.04 |
0.03 |
0.43 |
31.54 |
5.75 | |
|
||||||||
|
||||||||
GH | RexMT0 | 2.87 |
0.81 |
0.03 |
— | — | — | 6.78 |
GH | RexMT0-6 | 2.24 |
0.42 |
0.01 |
— | — | — | 4.63 |
SB | ADO | 8.58 |
0.57 |
0.16 |
— | — | — | 9.08 |
SB | IGA | 4.90 |
0.88 |
0.07 |
— | — | — | 3.61 |
|
||||||||
Mean | 4.64 |
0.67 |
0.07 |
— | — | — | 6.03 |
Concentrations of macrominerals (Ca, K, Mg, and P; g/100 g FW) of the four GH beefsteak tomato cultivars (Arbason, Caramba, Geronimo, and Trust) and the three SB varieties (Kaliroy, BionatureL, and BionatureP) are presented in Table
Microminerals (mg/100 g FW), Cu, Fe, and Na (Table
Results of least square means of Ca, K, Mg, and P (g/100 g FW) of one GH cultivar (Diva) and three SB cultivars of cucumber are presented in Table
Arugula from the GH (1 cultivar) and SB (3 cultivars) were similar in both macro- and micromineral content, except for Fe, Na, and Al, where all of the SB cultivars had consistently greater levels (Tables
Data presented in Tables
Cherry tomato cultivars had the greatest dry matter percentages (9.22%) followed by arugula (7.79%), then beefsteak tomato (5.11%), cucumber (4.91%), and bibb lettuce (4.71%) (Table
LS mean values1 of dry matter content (%), total dietary fiber (%), and total carbohydrate content mg glucose/100 g DW equivalents of greenhouse-grown (GH) and store-bought (SB) cherry tomato, beefsteak tomato, cucumber, arugula, and bibb lettuce.
Crops | Varieties | Dry matter (%) | Total carbohydrates | Total dietary fiber (%) |
---|---|---|---|---|
|
||||
GH | Apero | 11.02 |
55.48 |
1.37 |
GH | Apero-6 |
11.06 |
52.27 |
1.79 |
GH | Favorita | 9.57 |
53.81 |
1.35 |
GH | Favorita-6 | 10.14 |
60.87 |
1.46 |
GH | Juanita | 10.28 |
64.10 |
1.80 |
GH | Juanita-6 | 10.16 |
49.76 |
1.88 |
SB | Jardino | 6.00 |
78.80 |
1.70 |
SB | Cherries | 6.28 |
57.06 |
1.82 |
SB | Fruiterie | 8.50 |
76.92 |
1.65 |
|
||||
Mean | 9.22 |
61.00 |
1.65 | |
|
||||
|
||||
GH | Arbason | 6.45 |
49.02 |
2.14 |
GH | Caramba | 5.79 |
49.01 |
2.08 |
GH | Geronimo | 4.91 |
62.71 |
1.72 |
GH | Trust | 4.65 |
41.68 |
1.65 |
SB | Kaliroy | 5.18 |
50.24 |
1.66 |
SB | BionatureL | 2.81 |
55.14 |
1.90 |
SB | BionatureP | 5.95 |
55.76 |
1.84 |
|
||||
Mean | 5.11 |
51.94 |
1.86 | |
|
||||
|
||||
GH | Diva | 5.20 |
75.03 |
2.68 |
GH | Diva-3 | 4.69 |
70.18 |
1.87 |
GH | Diva-6 | 5.10 |
66.72 |
1.64 |
SB | Cool Cukes | 4.81 |
92.07 |
1.65 |
SB | Lebanese | 5.00 |
81.89 |
1.70 |
SB | Mini Cucumber | 4.64 |
60.75 |
1.67 |
|
||||
Mean | 4.91 |
74.44 |
1.87 | |
|
||||
|
||||
GH | Astro | 8.47 |
24.95 |
3.12 |
GH | Astro-6 | 7.64 |
13.54 |
2.69 |
SB | ADO | 8.32 |
10.65 |
2.92 |
SB | BW | 8.55 |
9.80 |
3.43 |
SB | PRO | 5.79 |
9.38 |
2.07 |
|
||||
Mean | 7.79 |
13.67 |
2.85 | |
|
||||
|
||||
GH | RexMT0 | 4.57 |
32.53 |
2.03 |
GH | RexMT0-6 | 4.65 |
42.21 |
2.14 |
SB | ADO | 5.25 |
44.53 |
2.19 |
SB | IGA | 4.39 |
27.49 |
2.16 |
|
||||
Mean | 4.71 |
36.69 |
2.23 |
Total carbohydrates of GH and SB crops were expressed as mg glucose equivalent/100 g DW (Table
Percentages of total dietary fiber (TDF) of GH and SB produce are presented in Table
Antioxidant scavenging capacity of GH and SB vegetables was evaluated using two oxidizing agents: 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) (Table
LS mean values1 of antioxidant scavenging capacity of hydrophilic and lipophilic phases using oxidizing agents ABTS (mg trolox equivalent (TE)/100 g DW) and DPPH (hydrophilic phase) (mg ascorbic acid equivalent (AAE)/100 g DW) of hydroponically grown (GH) and store-bought (SB) cherry tomato, beefsteak tomato, cucumber, arugula, and bibb lettuce.
Crops | Varieties | ABTS | DPPH | ||
---|---|---|---|---|---|
Hydrophilic | Lipophilic | Total | |||
|
|||||
GH | Apero | 0.67 |
0.29 |
0.96 |
11.71 |
GH | Apero-6 |
0.69 |
0.30 |
0.99 |
14.20 |
GH | Favorita | 0.71 |
0.32 |
1.04 |
13.33 |
GH | Favorita-6 | 0.69 |
0.30 |
0.99 |
11.57 |
GH | Juanita | 0.68 |
0.31 |
0.99 |
11.75 |
GH | Juanita-6 | 0.69 |
0.29 |
0.99 |
12.12 |
SB | Jardino | 0.71 |
0.32 |
1.03 |
12.82 |
SB | Cherries | 0.69 |
0.31 |
0.99 |
12.21 |
SB | Fruiterie | 0.70 |
0.31 |
1.01 |
12.53 |
|
|||||
Mean | 0.69 |
0.31 |
1.00 |
12.47 | |
|
|||||
|
|||||
GH | Arbason | 0.69 |
0.30 |
0.99 |
15.55 |
GH | Caramba | 0.68 |
0.31 |
0.99 |
14.81 |
GH | Geronimo | 0.69 |
0.27 |
0.96 |
14.82 |
GH | Trust | 0.69 |
0.31 |
1.00 |
14.57 |
SB | Kaliroy | 0.63 |
0.30 |
0.93 |
14.86 |
SB | BionatureL | 0.68 |
0.33 |
1.01 |
15.50 |
SB | BionatureP | 0.69 |
0.29 |
0.97 |
12.03 |
|
|||||
Mean | 0.68 |
0.30 |
0.98 |
14.59 | |
|
|||||
|
|||||
GH | Diva | 0.47 |
0.30 |
0.77 |
17.22 |
GH | Diva-3 | 0.36 |
0.32 |
0.68 |
17.83 |
GH | Diva-6 | 0.30 |
0.29 |
0.59 |
17.22 |
SB | Cool Cukes | 0.30 |
0.30 |
0.60 |
18.15 |
SB | Lebanese | 0.25 |
0.30 |
0.55 |
17.07 |
SB | Mini Cucumber | 0.33 |
0.30 |
0.63 |
17.48 |
|
|||||
Mean | 0.34 |
0.30 |
0.64 |
17.50 | |
|
|||||
|
|||||
GH | Astro | 0.70 |
0.49 |
1.19 |
15.52 |
GH | Astro-6 | 0.67 |
0.47 |
1.14 |
14.51 |
SB | ADO | 0.67 |
0.47 |
1.14 |
9.94 |
SB | BW | 0.72 |
0.43 |
1.14 |
11.46 |
SB | PRO | 0.74 |
0.52 |
1.26 |
14.81 |
|
|||||
Mean | 0.70 |
0.48 |
1.18 |
13.25 | |
|
|||||
|
|||||
GH | RexMT0 | 0.41 |
0.43 |
0.84 |
15.06 |
GH | RexMT0-6 | 0.39 |
0.28 |
0.68 |
14.70 |
SB | ADO | 0.67 |
0.29 |
0.95 |
12.70 |
SB | IGA | 0.48 |
0.44 |
0.92 |
15.35 |
|
|||||
Mean | 0.49 |
0.36 |
0.85 |
14.45 |
Antioxidant activity based on ABTS (hydrophilic) (mg TE/100 g DW) showed that, overall, arugula, beefsteak tomato, and cherry tomato had greater activity than bibb lettuce and cucumber. Bibb lettuce showed greater antioxidant activity than cucumber (Table
Total phenolic content of GH and SB vegetables was expressed as mg of gallic acid equivalent (GAE) per 100 g DW (Table
LS mean values1 of total phenolics (mg/100 g DW gallic acid (GAE) equivalent), total carotenoids (mg/100 g DW
Crops | Varieties | Total phenolics | Total anthocyanins | Total carotenoids | |
---|---|---|---|---|---|
Hexane | Ethanol | ||||
|
|||||
GH | Apero | 10.60 |
4.91 |
1170.88 |
8.17 |
GH | Apero-6 |
11.00 |
16.04 |
1420.39 |
8.92 |
GH | Favorita | 11.06 |
18.42 |
1332.90 |
9.72 |
GH | Favorita-6 | 12.11 |
12.24 |
1157.47 |
7.44 |
GH | Juanita | 10.43 |
10.37 |
1175.16 |
8.51 |
GH | Juanita-6 | 13.60 |
3.81 |
1212.27 |
8.71 |
SB | Jardino | 11.10 |
10.96 |
1282.42 |
14.82 |
SB | Cherries | 8.59 |
6.43 |
1221.45 |
14.87 |
SB | Fruiterie | 9.91 |
10.52 |
1252.70 |
11.27 |
|
|||||
Mean | 10.99 |
10.41 |
1247.30 |
10.27 | |
|
|||||
|
|||||
GH | Arbason | 8.31 |
4.93 |
1554.79 |
11.83 |
GH | Caramba | 7.23 |
11.47 |
1480.51 |
14.35 |
GH | Geronimo | 8.26 |
11.03 |
1481.94 |
11.73 |
GH | Trust | 9.29 |
10.48 |
1457.40 |
12.51 |
SB | Kaliroy | 9.55 |
4.97 |
1486.47 |
8.73 |
SB | BionatureL | 8.90 |
3.29 |
1549.62 |
9.11 |
SB | BionatureP | 9.26 |
2.17 |
1203.18 |
8.49 |
|
|||||
Mean | 8.68 |
6.91 |
1459.13 |
10.96 | |
|
|||||
|
|||||
GH | Diva | 9.65 |
3.90 |
1721.66 |
3.84 |
GH | Diva-3 | 8.72 |
11.13 |
1782.82 |
3.46 |
GH | Diva-6 | 9.87 |
2.22 |
1722.46 |
4.73 |
SB | Cool Cukes | 6.69 |
9.95 |
1815.45 |
7.90 |
SB | Lebanese | 6.99 |
16.66 |
1707.20 |
6.95 |
SB | Mini Cucumber | 6.38 |
7.24 |
1748.34 |
6.05 |
|
|||||
Mean | 8.05 |
8.52 |
1749.66 |
5.49 | |
|
|||||
|
|||||
GH | Astro | 12.33 |
59.56 |
1552.25 |
1.23 |
GH | Astro-6 | 11.01 |
31.63 |
1450.70 |
1.48 |
SB | ADO | 13.06 |
38.26 |
994.12 |
0.97 |
SB | BW | 15.92 |
27.40 |
1145.93 |
1.99 |
SB | PRO | 15.68 |
40.84 |
1480.76 |
3.16 |
|
|||||
Mean | 13.60 |
39.54 |
1324.75 |
1.77 | |
|
|||||
|
|||||
GH | RexMT0 | 6.59 |
2.72 |
1505.92 |
2.82 |
GH | RexMT0-6 | 7.06 |
1.60 |
1469.75 |
5.80 |
SB | ADO | 7.78 |
0.69 |
1270.19 |
13.79 |
SB | IGA | 7.47 |
1.63 |
1534.99 |
5.28 |
|
|||||
Mean | 7.22 |
1.66 |
1445.21 |
6.92 |
The only GH cucumber, ‘Diva,’ had greater total phenolic content compared with the three SB varieties. Similar content of total phenolics was found in GH and SB arugula and bibb lettuce cultivars. Vegetable crops, arranged in descending order based on their total phenolic contents (mg/100 g GAE), were arugula, cherry tomato, beefsteak tomato and cucumber, and bibb lettuce and cucumber, respectively. Lettuce was also reported to have greater content of total phenolics than cucumber by Chu et al. [
Comparing between crops revealed that arugula had the greatest TAC content followed by cherry tomato and cucumber, which had TAC similar to beefsteak tomato while bibb lettuce had the least TAC content (Table
Fridge-storage affected TAC content of the crops in different ways. For example, storage of GH cherry tomato did not affect TAC content of ‘Favorita’ and ‘Juanita’ but increased the TAC of ‘Apero.’ Storage (3 d) increased the TAC of cucumber ‘Diva’ but it was decreased again after 6 d storage (Table
Total carotenoid levels of GH and SB varieties were estimated in two different extracts: hexane or ethanol (Table
For the ethanol extract, GH cherry tomato had lesser concentrations of carotenoids compared with the SB cultivars (Table
The HPLC analysis of the major carotenoid compounds (
LS mean values1 of
Crops | Varieties |
|
Lutein | Lycopene |
---|---|---|---|---|
|
||||
GH | Apero | 166.16 |
4.03 |
73.55 |
GH | Apero-6 |
107.43 |
2.56 |
60.74 |
GH | Favorita | 235.53 |
5.00 |
119.75 |
GH | Favorita-6 | 152.43 |
5.49 |
75.00 |
GH | Juanita | 171.30 |
4.18 |
76.60 |
GH | Juanita-6 | 147.70 |
4.07 |
83.80 |
SB | Jardino | 146.55 |
3.95 |
72.36 |
SB | Cherries | 390.34 |
9.12 |
139.74 |
SB | Fruiterie | 311.53 |
6.52 |
89.56 |
|
||||
Mean | 203.22 |
4.99 |
87.90 | |
|
||||
|
||||
GH | Arbason | 54.25 |
3.65 |
39.00 |
GH | Caramba | 146.88 |
5.79 |
66.07 |
GH | Geronimo | 111.99 |
4.69 |
45.92 |
GH | Trust | 86.56 |
3.35 |
67.00 |
SB | Kaliroy | 107.23 |
2.85 |
32.17 |
SB | BionatureL | 139.89 |
2.98 |
40.74 |
SB | BionatureP | 153.32 |
3.62 |
32.03 |
|
||||
Mean | 114.30 |
3.88 |
46.13 | |
|
||||
|
||||
GH | Diva | 37.09 |
10.74 |
— |
GH | Diva-3 | 22.25 |
5.26 |
— |
GH | Diva-6 | 33.11 |
13.63 |
— |
SB | Cool Cukes | 56.29 |
23.38 |
— |
SB | Lebanese | 93.19 |
19.11 |
— |
SB | Mini Cucumber | 139.05 |
22.95 |
— |
|
||||
Mean | 63.50 |
15.89 |
— | |
|
||||
|
||||
GH | Astro | 445.22 |
33.76 |
— |
GH | Astro-6 | 615.75 |
58.22 |
— |
SB | ADO | 1365.03 |
75.47 |
— |
SB | BW | 842.91 |
72.14 |
— |
SB | PRO | 1080.80 |
95.22 |
— |
|
||||
Mean | 869.94 |
66.96 |
— | |
|
||||
|
||||
GH | RexMT0 | 223.77 |
19.97 |
— |
GH | RexMT0-6 | 85.70 |
9.89 |
— |
SB | ADO | 55.00 |
14.78 |
— |
SB | IGA | 290.27 |
28.38 |
— |
|
||||
Mean | 163.69 |
18.26 |
— |
Store-bought cucumber variety Mini Cucumber showed greater
Fridge-storage of GH vegetables depressed the content of
Lutein concentration in arugula was the greatest among tested crops and ranged from 33.76 to 95.22 mg/100 g DW: manyfold greater than in the other vegetables (Table
Lycopene is the most predominant carotenoid pigment in tomatoes (about 83%) [
Concentrations of ascorbic acid were similar for GH and SB cherry tomato (Table
LS mean values1 of organic acids (mg/100 g DW) of hydroponically grown (GH) and store-bought (SB) cherry tomato, beefsteak tomato, cucumber, arugula, and bibb lettuce evaluated using high pressure liquid chromatography (HPLC).
Crops | Varieties | Ascorbic acid | Malic acid | Citric acid | Fumaric acid |
---|---|---|---|---|---|
|
|||||
GH | Apero | 108.15 |
25.48 |
2.04 |
0.14 |
GH | Apero-6 |
317.52 |
5.30 |
5.60 |
0.24 |
GH | Favorita | 85.01 |
11.93 |
4.10 |
0.16 |
GH | Favorita-6 | 44.94 |
4.45 |
2.01 |
0.13 |
GH | Juanita | 81.74 |
18.99 |
4.82 |
0.19 |
GH | Juanita-6 | 241.30 |
3.21 |
1.60 |
0.15 |
SB | Jardino | 82.82 |
37.44 |
4.20 |
0.24 |
SB | Cherries | 119.29 |
58.92 |
1.59 |
0.09 |
SB | Fruiterie | 84.28 |
32.98 |
0.50 |
0.16 |
|
|||||
Mean | 129.45 |
22.08 |
2.97 |
0.17 | |
|
|||||
|
|||||
GH | Arbason | 117.72 |
4.33 |
2.59 |
0.26 |
GH | Caramba | 125.16 |
6.38 |
2.71 |
0.26 |
GH | Geronimo | 46.46 |
109.65 |
0.09 |
0.16 |
GH | Trust | 178.78 |
4.11 |
1.04 |
0.21 |
SB | Kaliroy | 497.97 |
6.34 |
3.54 |
0.10 |
SB | BionatureL | 306.23 |
10.14 |
3.92 |
0.18 |
SB | BionatureP | 119.00 |
1.21 |
2.10 |
0.08 |
|
|||||
Mean | 198.76 |
20.31 |
2.29 |
0.18 | |
|
|||||
|
|||||
GH | Diva | 55.41 |
85.43 |
14.15 |
0.50 |
GH | Diva-3 | 4.92 |
102.27 |
16.22 |
0.02 |
GH | Diva-6 | 87.50 |
19.67 |
4.72 |
0.14 |
SB | Cool Cukes | 20.32 |
104.46 |
18.11 |
0.30 |
SB | Lebanese | 43.18 |
93.04 |
11.04 |
0.34 |
SB | Mini Cucumber | 15.60 |
108.31 |
7.67 |
0.01 |
|
|||||
Mean | 37.82 |
85.53 |
11.98 |
0.22 | |
|
|||||
|
|||||
GH | Astro | 87.07 |
67.20 |
1.21 |
0.06 |
GH | Astro-6 | 56.91 |
183.18 |
0.15 |
0.01 |
SB | ADO | 31.45 |
12.18 |
1.21 |
0.02 |
SB | BW | 112.97 |
4.81 |
0.25 |
0.004 |
SB | PRO | 80.21 |
82.89 |
0.08 |
0.14 |
|
|||||
Mean | 73.72 |
70.05 |
0.36 |
0.05 | |
|
|||||
|
|||||
GH | RexMT0 | 65.72 |
221.80 |
0.04 |
0.02 |
GH | RexMT0-6 | 85.29 |
814.06 |
0.08 |
0.06 |
SB | ADO | 54.30 |
1028.70 |
0.11 |
0.12 |
SB | IGA | 63.38 |
1323.56 |
0.14 |
0.07 |
|
|||||
Mean | 67.17 |
847.03 |
0.09 |
0.07 |
Based on average vitamin C content of cultivars within each crop, beefsteak tomato had the greatest vitamin C content (198.76 mg/100 g DW) followed by cherry tomato (129.45), arugula (73.72), bibb lettuce (67.17), and finally cucumber (37.82). Curiously, fridge-storage of GH ‘Apero’ and ‘Juanita’ for 6 d increased vitamin C concentrations but these were decreased in ‘Favorita.’ Similarly, storing ‘Diva’ for 6 d increased the ascorbic acid content compared with fresh cucumber. The observed increased vitamin C content with storage could be due to an increase in ascorbic acid synthesis. No effect of 6 d storage occurred on the vitamin C content of arugula ‘Astro’ or bibb lettuce ‘RexMT0’ compared with fresh produce.
Malic acid contributes a sour taste to vegetables and tends to be present in greater concentrations in unripe fruit. Organic acids, especially malic and citric acids, were reported as the major organic acids in tomato [
Surprisingly, fridge-storage (6 d) of GH arugula ‘Astro’ and bibb lettuce ‘RexMT0’ increased the concentration of malic acid by 172.60 and 267.02%, respectively. In contrast, fridge-storage of GH cherry tomato (6 d) did not make any difference in terms of malic acid content for ‘Favorita’ (Table
Citric acid is a natural preservative and often used as a food additive for its flavor. It contributes to vegetables’ acidity, color, and taste [
As with malic acid, different trends occurred in the citric acid content of hydroponically grown vegetables that were stored for 6 d (Table
Fumaric acid (trans-butenedioic acid) is an acidulent agent that contributes a sour taste to food. Vegetable crops had different fumaric acid content (mg/100 g DW) (Table
For cucumber, GH ‘Diva’ had greater fumaric acid content than ‘Mini Cucumber’ but similar content to ‘Cool Cukes’ and ‘Lebanese’ (Table
The effect of fridge-storage on fumaric acid content was inconsistent between GH vegetables as seen with other organic acids (Table
Fridge-storage of cherry tomato for 6 d resulted in increased content of Fe and vitamin C in ‘Juanita’ and As, TAC, vitamin C, and citric acid content in ‘Apero’ while levels of Se, vitamin C, and lycopene were reduced in ‘Favorita.’ Generally storage of GH cherry tomato depressed the content of
Also, fridge-storage of the cucumber ‘Diva’ for 3 or 6 d increased its mineral content. It increased the TAC of cucumber ‘Diva’ after 3 d in storage but decreased it again after 6 d storage. Six-day storage of ‘Diva’ increased its the ascorbic acid content and decreased its hydrophilic and total ABTS scavenging activity, the content of malic acid (by 66.64%), citric acid (by 66.6%), and fumaric acid content.
Fridge-storage for 6 d of GH arugula ‘Astro’ resulted in greater Ca and Fe but Cr and Pb were not detected in stored produce but decreased the total carbohydrate and TAC levels. Storage of GH arugula ‘Astro’ for 6 d increased the concentration of malic and fumaric acids but dramatically decreased malic (by 79.20%) and citric acids (by 87.6%). Storage of GH bibb lettuce ‘RexMT0’ for 6 d had reduced Al, Cd, Mg, Zn, and
The observed variations in plant metabolites and antioxidant capacity following storage can be attributed to a variety of factors that include biosynthesis during storage, as well as losses due to degradation caused by enzymatic (i.e., polyphenoloxidase, ascorbate oxidase) and nonenzymatic oxidation reactions. Additionally, a slight drop in tissue dry weight during storage could account for slightly more efficient extraction, particularly minerals.
Assessing traits that contribute to define the most nutritious variety is of great importance for long-term breeding programs for vegetables. The graphical representation of the interrelationships among various sensory and phytonutrient parameters is useful to visualize essential relationships [
Drop-list. Nonsignificant variables (sensory and phytonutrient) that were excluded after the first statistical selection step because these variables do not differentiate among tested varieties of each select crop.
Crop | Variables (ANOVA |
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Cherry tomato |
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Beefsteak tomato |
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Cucumber |
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Arugula |
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Bibb lettuce |
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Based on the output after running ANOVA for each of the tested populations separately (cherry tomato, beefsteak tomato cucumber, arugula, and bibb lettuce), a first selection process among assayed variables was done (Table
Similarly, some mineral elements were not different in varieties of SB and GH produce (Table
Taste test components including fruit ripeness, sweetness, juiciness, mouth feeling, and general acceptability of beefsteak tomato were similar. Dry matter, malic acid, and flesh aroma were not able to distinguish varieties of cucumber. The overall quality term could not distinguish arugula varieties. Ascorbic acid and the sensory variables, odor, sogginess and freshness, and overall quality, were not discriminating variables among bibb lettuce varieties (Table
Figure
Tree dendrogram of the clustering patterns and their proportion of explained variance (9 clusters explained 100% of the variation) using VARCLUS procedure for phytonutrient variables that were used to differentiate among cherry tomato store-bought and greenhouse-grown varieties. CarotenoidsH: carotenoids, hydrophilic fraction.
The PLS and PCA output showed that the eigenvalues of the first 2 components (PLS factors 1 and 2 and PCA components 1 and 2) were responsible for 76.4% of the variance and 69.5% of the covariance, so plotting PLS 1 versus PLS 2 (Figure
Figures
Results in Figure
Tree dendrogram of the clustering patterns and their proportion of explained variance (9 clusters explained 100% of the variation) using VARCLUS procedure for phytonutrient variables that were used to differentiate among beefsteak tomato store-bought and greenhouse-grown varieties. CarotenoidsH: carotenoids, hydrophilic fraction.
The PLS and PCA output showed that the eigenvalues of the first 2 components (PLS factors 1 and 2 and PCA factors 1 and 2) are responsible for 87.92% of the variance, so plotting PLS 1 versus PLS 2 (Figure
Data presented in Figure
Tree dendrogram of the clustering patterns and their proportion of explained variance (11 clusters explained 100% of the variation) using VARCLUS procedure for phytonutrient variables that were used to differentiate among cucumber store-bought and greenhouse-grown varieties. CarotenoidsH: carotenoids, hydrophilic fraction; ABTSH: ABTS, hydrophilic fraction; ABTST: ABTS, total hydrophilic and lipophilic fractions.
The PLS and PCA output showed that the eigenvalues of the first 2 components (PLS factors 1 and 2 and PCA factors 1 and 2) are responsible for 100% of the variance and 85.4% of the covariance, so plotting PLS 1 versus PLS 2 (Figure
Approximately 13 clusters explained close to 100% of variation among arugula varieties (Figure
Tree dendrogram of the clustering patterns and their proportion of explained variance (13 clusters explained 100% of the variation) using VARCLUS procedure for phytonutrient variables that were used to differentiate among arugula store-bought and greenhouse-grown varieties. CarotenoidsH: Carotenoids, hydrophilic fraction; CarotenoidsL: carotenoids, lipophilic fraction.
Of all of the sensory variables, the fresh leaf color was the most dominant factor, which clearly differentiated the three tested bibb lettuce varieties (Figure
Tree dendrogram of the clustering patterns and their proportion of explained variance (13 clusters explained 100% of the variation) using VARCLUS procedure for phytonutrient variables that were used to differentiate among bibb lettuces store-bought and greenhouse-grown varieties. CarotenoidsH: carotenoids, hydrophilic fraction; ABTSL: ABTS, lipophilic fraction.
Multidimensional preference analysis plot of the PCA procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate cherry tomato varieties: greenhouse cvs TFA: Favorita, TCJ: Juanita, and TCA: Apero, and the store-bought cv TFR: Fruiterie.
Multidimensional preference analysis plot of the PCA procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate beefsteak tomato varieties: greenhouse cvs BGER: Geronimo, BCAR: Caramba, BTRU: Trust, and BARA: Arbason, and the store-bought cv BTBI: BionatureL.
Multidimensional preference analysis plot of the PCA procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate cucumber varieties greenhouse cv CGH: Diva and store-bought cvs LC: Labenese, and MC: Mini Cucumber.
Multidimensional preference analysis plot of the PCA procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate arugula varieties: greenhouse cv AGH: Astro and store-bought cvs AP: PRO, AF: BW, and AA: ADO.
Multidimensional preference analysis plot of the PCA procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate bibb lettuce varieties: greenhouse cv LGH: RexMT and store-bought cvs LM: IGA and LA: ADO.
Correlation loading plot of the PLS procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate cherry tomato varieties: greenhouse cvs TFA: Favorita, TCJ: Juanita, and TCA: Apero and the store-bought cv TFR: Fruiterie.
Correlation loading plot of the PLS procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate beefsteak tomato varieties: greenhouse cvs BGER: Geronimo, BCAR: Caramba, BTRU: Trust, and BARA: Arbason and the store-bought cv BTBI: BionatureL.
Correlation loading plot of the PLS procedure. A visual illustration tool that shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate cucumber varieties greenhouse cv CGH: Diva and store-bought cvs LC: Lebanese and MC: Mini Cucumber.
Correlation loading plot of the PLS procedure. A visual illustration tool, which shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate arugula varieties: greenhouse cv AGH: Astro and store-bought cvs AP: PRO, AF: BW, and AA: ADO.
Correlation loading plot of the PLS procedure. A visual illustration tool, which shows similarity classification of the dependent and independent variables but in different space dimension for variables used to differentiate bibb lettuce varieties: greenhouse cv LGH: RexMT and store-bought cvs LM: IGA and LA: ADO.
Figure
For bibb lettuce, total anthocyanins, total phenolics, total carbohydrates, citric acid, malic acids, fumaric acid, lutein, and
In this study, we examined the possibility of discriminating cultivars of several crop species, both hydroponically grown and store-bought, based on taste panels’ sensory analysis, phytonutrient analysis of a long list of phytonutrients, and complex statistical analysis. Our hope was that this strategy could provide plant breeders with sufficient information to both choose the best varieties and design long-term strategies to improve crop breeding programs towards improved human health.
Based on our panelists’ responses, the variables we chose for cultivar selection among greenhouse-grown crops (also between these and store-bought crops) were in most cases insufficiently robust to help distinguish between cultivars. The exceptions were the more dominant sensory characteristics such as the “astringent” and “grassy” traits of arugula cultivars, the “juiciness” and “general acceptability” of cherry tomato cultivars, and the “freshness” and “sweetness” of cucumber cultivars. These dominant characteristics could form the core of a consolidated number of criteria in a more discriminating sensory evaluation test.
Among the phytonutrient tests, mineral analysis was powerful for crop cultivar differentiation; in particular, the minerals Cu, Fe, K, Mg, and P were more useful than others to discriminate between cultivars within each crop. Total carotenoids, particularly
Our data supports the use of hierarchical cluster analysis, used efficiently in past studies to compare between different types of foods through the analysis of data sets [
The effect of fridge-storage under ideal circumstances (picked fresh, packed into zip-lock plastic bags, and placed at 4°C for 3 or 6 d) did not have a dramatic effect on phytonutrient status. As long as produce is handled well after harvest, it seems that it does not deteriorate too much during this time frame. There are various implications of this to consider. Foremost is that while “fresh-picked” is perceived by consumers to be very important, “freshness” under ideal storage conditions, such as the 6 d of fridge-storage used in our study, did not affect phytonutrient quality. It is apparent that the effect of cultivar is more important than the effect of short-term storage under ideal storage conditions. This is reassuring for suppliers and customers who may be concerned about relative freshness of their produce. For example, the effects of various phenolic and organic acids that were affected by storage in some cultivars are taste-related components that could have an impact on sensory quality. There are many unknowns related to the effects of storage on sensory parameters (this was not done) and phytonutrient characteristics, which could now be explored. Apart from GH arugula that had relatively more intense bitter flavor, GH produce generally had rankings of sensory traits that were either superior or equal to SB produce. The importance of cultivar selection towards improved sensory traits is evident for cherry tomatoes, where ‘Apero’ showed consistently better sensory characteristics relative to the other GH cherry tomatoes in addition to the SB produce. The advantage of GH cucumbers relative to the two other tested SB produce is apparent for flesh color and flesh firmness indicating a superior product in terms of sensory characteristics.
The current study provides new information concerning key relationships and correlation among sensory analysis, phytonutrient content, and data mining statistics of arugula, bibb lettuce, cucumber, and tomato (beef-steak and cherry) to enable better visualization of essential relationships among vegetable and fruit traits. Plant breeders can use this study to select the more discriminating sensory criteria and strategize to find others and to better select among phytochemical assays and eliminate the often costly analyses with lesser utility for discrimination between genotypes. Ultimately, consumers will benefit by identification and promotion of cultivars with superior phytonutrient content and antioxidant capacity.
The authors have no conflict of interests to declare regarding the publication of this paper.
Thanks are due to Ms. Lauren Rathmell of Lufa Farms for help growing the hydroponic greenhouse produce in the Macdonald campus research greenhouse, purchasing the store-bought produce and other materials for the taste tests, and assisting with plate preparation and other matters during the taste tests. The authors also thank Drs. Z. Farook and M. Baig (Arid Agriculture University, Rawalpindi, Pakistan) for their assistance with the taste and phytonutrient tests and paper review. Thanks are due to Mr. Simon Hebert and his staff for their assistance with greenhouse help during the crop growth and harvesting phases. Thanks are also due to Dr. G. Marquis, Chair, and the other members of McGill’s Ethics Board, for their helpful suggestions towards the detailed planning necessary to conduct the Taste Tests (McGill Ethics certificate REB File #: 953-1110). The authors also thank the School of Dietetics & Human Nutrition for use of their sensory analysis facility for conducting the taste tests. Thanks are also due to Drs. M. Lefsrud and Dr. S. Prasher (Bioresource Engineering Dept.), A. Mustafa (Animal Sciences Dept.), and J. Singh (Plant Science Dept.) for the use of the freeze-dryer, ICP OES, LECO, and −80°C freezer, respectively. Authors D. J. Donnelly and S. Kubow are also grateful to the NSERC Discovery Grant program.