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. 2023 Apr 19;11(7):3858–3874. doi: 10.1002/fsn3.3371

Morphological characterizations of parsnip (Pastinaca sativa L.) to select superior genotypes

Ali Khadivi 1,✉, Farhad Mirheidari 1, Younes Moradi 1
PMCID: PMC10345681  PMID: 37457187

Abstract

Parsnip (Pastinaca sativa L.) is an edible root that has long been used in cooking and preparing baby food and livestock. The present study was performed to evaluate the phenotypic diversity of 69 accessions of this species to select superiors in terms of root quality in Paykan village, Isfahan province, Iran, in the year 2022. There were significant differences among the accessions investigated (ANOVA, p < .01). Coefficient of variation (CV) was more than 20.00% in the majority of measured characters (64 out of 66 characters), indicating high diversity among the accessions. Foliage width (crown) ranged from 10 to 55 cm with an average of 32.32 cm. Root shape was tapering (33), obtriangular (10), narrow oblong (5), wide oblong (5), obovate (13), and fusiform (3). Root length ranged from 81.2 to 294 mm with an average of 166.44 mm. Root diameter at its middle point ranged from 15.58 to 125.12 mm with an average of 51.83 mm. Root weight ranged from 15 to 1200 g with an average of 315.36 g. Inner core (xylem) pigmentation/color was cream yellow (11 accessions), light yellow (12), yellow (42), dark yellow (2), and yellow–light orange (2). In the cluster analysis based on Ward's method, the accessions were divided into two main clusters according to morphological traits. This is despite the fact that parsnip is part of the medicinal plant native and valuable in most farms in tropical cities. Compared with carrots, parsnip plants are more adaptable to different environmental conditions. The accessions studied here showed high phenotypic diversity. Based on ideal values of the important and commercial characters of parsnip, such as root length, root weight, inner core (xylem) pigmentation/color, root shape, flesh color intensity, flesh palatability, and total soluble solids, 14 genotypes, including Parsnip‐3, Parsnip‐9, Parsnip‐24, Parsnip‐32, Parsnip‐32, Parsnip‐48, Parsnip‐51, Parsnip‐52, Parsnip‐58, Parsnip‐60, Parsnip‐62, Parsnip‐65, Parsnip‐67, and Parsnip‐69, were promising and are recommended for cultivation.

Keywords: conservation, cultivation, parsnip, Pastinaca sativa L., quality, superior

Parsnip (Pastinaca sativa L.) is an edible root that has long been used in cooking and preparing baby food and livestock. The present study was performed to evaluate the phenotypic diversity of 69 accessions of this species to select the superior one in terms of root quality. Based on ideal values of the important and commercial characters of parsnip, such as root length, root weight, inner core (xylem) pigmentation/color, root shape, flesh color intensity, flesh palatability, and total soluble solids, 14 genotypes, including Parsnip‐3, Parsnip‐9, Parsnip‐24, Parsnip‐32, Parsnip‐32, Parsnip‐48, Parsnip‐51, Parsnip‐52, Parsnip‐58, Parsnip‐60, Parsnip‐62, Parsnip‐65, Parsnip‐67, and Parsnip‐69, were promising and are recommended for cultivation.

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1. INTRODUCTION

Parsnip (Pastinaca sativa L.) is an edible root that has long been used in cooking and preparing baby food and livestock (Castro et al., 2012). It can also have therapeutic applications depending on the dosage and method of cooking (Stannard, 1982). Parsnip root is high in dietary fiber about 4.70–4.90% (Stannard, 1982). Being rich in starch and sugar, the parsnip root is used for human consumption (in soups, cakes, muffins, and puddings), animal feed, and winemaking. Its fresh leaves and buds are also used as vegetables for food and soups. It has various nutritional and therapeutic applications in different countries. For instance, parsnip is used as an appetizer, digestive, and diuretic in some countries. The seeds of parsnip contain bitter aromatic substances that increase milk in lactating mothers and are also used as food spices; it tastes like dill (Matejić et al., 2014).

Pastinaca sativa has different conventional names in different languages such as Zardak and wild carrot in Persian, parsnip in English, Cujtive and Panipainais in French, Jazar in Arabic, and Kajer in India (Emami et al., 2010). From botanical point of view, there is much controversy about distinguishing the parsnip from carrot. Some historians believe the color and taste of the carrots are gradually changed over time; the wild carrots were pale white or yellow and the native carrots were pale yellow or purple. Pale white and yellow carrots may come from mutations in the colored carrot gene. In the 18th century, Linnaeus for the first time provided separate scientific names for them, naming the carrot Daucus carota L. and parsnip Pastinaca sativa. Galen was the first who explicitly separated carrot from parsnip in his writings (Bahrami et al., 2018; Grant, 2000; Stolarczyk & Janick, 2011).

Wild parsnip is an herbaceous biennial (or more correctly, a monocarpic perennial) within the Apiaceae (Umbelliferae) (carrot, parsley) (Zomlefer, 1994), subfamily Apioideae, tribe Peucedaneae, and subtribe Ferulinae (Peucedaninae), based on Drude (1897–1898) classification of the Apiaceae (Downie et al., 1998). However, Theobald (1971) noted that Pastinaca shares most floral and fruit anatomical characteristics with members of the genus Heracleum, which are classified in the Tordyliinae subtribe. This taxonomic similarity suggests distinct differences within the subtribes of the Peucedaneae.

Wild parsnip is a tall, stout, herbaceous plant with a long, thick, and deep taproot (Gleason & Cronquist, 1991). Wild parsnip is widely distributed in Europe and temperate Asia, where it originated. Wild parsnip is commonly found in waste areas, old fields, and along roadsides and railroad embankments. It grows best in rich, alkaline, and moist soils, but can survive under poor soil conditions (Gleason & Cronquist, 1991). Under summer drought conditions in Oxfordshire, UK, Sternberg et al. (1999) found that the growth of wild parsnip plants in an old field increased and the growth of perennial grasses decreased. This tolerance to drought by wild parsnip may be due to its deep tap root, which allows access to water and nutrients from deeper soil layers (Tutin, 1980).

Wild parsnip plants contain at least seven classes of secondary compounds, including terpenes, flavonoids, polyacetylenes, coumarins, and furanocoumarins (Berenbaum, 1985). Some of the compounds are phenylpropanoids, such as myristicin, which, when combined with xanthotoxin, is synergistically toxic to some insects (Berenbaum, 1985); monoterpenes, which are attractants for pollinators and antimicrobial agents (Harrewijn et al., 1994); sesquiterpenes, which are known to be toxic and deterrents to insects; and fatty acid esters, which are toxic to the larvae of some lepidopterans (Zangerl & Berenbaum, 1993).

Morphological traits are important parameters for the identification and selection of favorable genotypes as plant breeders can use this information for the development of breeding populations (Greene et al., 2004). Both qualitative and quantitative morphological characteristics are useful for germplasm studies. Generally, qualitative parameters are useful for varietal identification, while quantitative parameters are required for the development of new varieties (Luitel et al., 2018). There are no reports about the morphological traits of parsnip. Therefore, a detailed analysis of morphological variability in parsnip core collection is required to understand the diversity in both the qualitative and quantitative parameters. This characterization of morphological parameters is considered an important step in the description and classification of germplasm. Thus, the main objective of the present study was to evaluate morphological characteristics of P. sativa in Isfahan province, Iran, to select superiors.

2. MATERIALS AND METHODS

2.1. Plant material

The present study was performed to evaluate the phenotypic diversity of 69 accessions of parsnip (P. sativa) to select superiors in terms of root quality. The accessions studied were cultivated in Paykan village in Isfahan province, Iran, in the year 2022, under homogeneous conditions in loamy clay soil. Paykan village is located at 32°15′50″ N latitude and 52°10′40″ E longitude. The soil of the researched field was analyzed to determine the amount of elements and check the non‐uniformity of the soil. The present experiment was conducted based on a randomized complete block design.

2.2. The characteristics evaluated

The phenotypic diversity of the accessions was investigated using 66 morphological traits (Table 1). The traits related to dimensions of leaf and root were measured using a digital caliper. A digital scale with an accuracy of 0.01 g was used to measure the weight of root. Total soluble solids (TSS) were determined using a refractometer (pocket PAL‐1 ATAGO Corporation, Tokyo, Japan), in Brix. The qualitative traits (Table 2) were visually examined and coded according to descriptor of the wild and cultivated carrots (Daucus carota) (IPGRI, 1998).

TABLE 1.

Statistical descriptive parameters for morphological traits used to study P. sativa accessions.

No. Character Abbreviation Unit Min. Max. Mean SD CV (%)
1 Foliage coverage V2 Code 1 5 3.52 1.63 46.36
2 Foliage width (crown) V3 cm 10.00 55.00 32.32 9.15 28.31
3 Leaf growth habit (attitude) V4 Code 1 5 1.55 0.96 62.13
4 Number of mature leaves per plant V5 Number 5 47 18.42 8.13 44.13
5 Mature leaf length V6 mm 110.00 356.00 236.04 51.47 21.81
6 Mature leaf width V7 mm 40.15 194.34 102.50 31.24 30.48
7 Leaf hairiness V8 Code 1 7 4.45 1.41 31.66
8 Leaf type V9 Code 1 7 3.20 1.15 35.78
9 Leaf dissection V10 Code 1 5 2.07 1.26 61.06
10 Leaflet apex shape V11 Code 1 5 3.84 1.21 31.46
11 Leaf color V12 Code 1 9 6.48 2.49 38.41
12 Leaf color intensity V13 Code 1 5 3.43 1.41 41.08
13 Number of leaflets on lower mature leaf V14 Number 7 17 10.83 2.63 24.28
14 Length of basal primary leaflet V15 mm 6.24 141.68 76.09 28.61 37.59
15 Number of segment tips on lower primary leaflet V16 Number 3 15 6.94 2.50 35.97
16 Petiole length V17 mm 29.00 201.00 88.48 38.65 43.68
17 Petiole width V18 mm 2.35 4.90 3.42 0.62 18.24
18 Petiole thickness V19 mm 1.06 4.45 2.71 0.62 22.67
19 Petiole shape in transverse section V20 Code 1 5 2.42 1.14 47.23
20 Anthocyanin coloration in petiole V21 Code 0 5 1.59 1.49 93.58
21 Petiole hairiness V22 Code 1 7 4.62 1.34 29.03
22 Stem development in first year V23 Code 1 3 1.03 0.24 23.40
23 Root axis V24 Code 1 3 2.77 0.65 23.29
24 Root branching V25 Code 0 3 0.25 0.74 294.40
25 Lateral (secondary) root growth in accession V26 Code 0 5 0.30 0.83 276.00
26 Emergence of lateral (secondary) roots on fleshy root V27 Code 0 5 0.51 1.16 227.06
27 Hairy roots on storage root V28 Code 1 5 1.38 0.99 71.52
28 Emergence of hairy roots on fleshy root V29 Code 1 5 4.13 1.11 26.88
29 Root length V30 mm 81.20 294.00 166.44 48.47 29.12
30 Root diameter at the middle point of the root V31 mm 15.58 125.12 51.83 22.73 43.85
31 Root maximum transverse diameter V32 mm 20.43 127.33 61.28 23.00 37.53
32 Root maximum transverse diameter position V33 Code 1 5 1.72 1.49 86.86
33 Root ratio length/diameter V34 Ratio 1.24 8.34 2.96 1.10 37.09
34 Taproot length V35 mm 8.73 130.11 49.61 25.80 52.01
35 Neck diameter V36 mm 8.01 48.77 20.22 7.70 38.09
36 Collar diameter V37 mm 11.72 76.19 33.97 13.97 41.13
37 Root diameter at shoulder V38 mm 17.39 103.87 53.89 19.26 35.74
38 Root shoulder shape V39 Code 1 9 3.93 2.07 52.77
39 Extent of green color of skin on shoulder V40 Code 0 5 0.68 1.16 170.15
40 Extent of purple color of skin on shoulder V41 Code 0 5 2.70 2.06 76.30
41 Root weight V42 g 15 1200 315.36 297.87 94.45
42 Root surface V43 Code 1 7 2.97 2.18 73.50
43 Root splitting/cracking tendency V44 Code 0 5 0.23 0.93 402.61
44 Root shape V45 Code 1 11 3.96 3.49 88.16
45 Root tapering V46 Code 0 5 3.23 1.81 55.98
46 Root tip/end shape V47 Code 1 5 4.33 1.07 24.62
47 Root skin pigmentation/color V48 Code 1 21 12.16 7.30 60.07
48 Root skin color intensity V49 Code 1 3 2.07 1.01 48.55
49 Inner core (xylem) diameter at shoulder V50 mm 6.02 64.57 19.74 11.51 58.29
50 Inner core (xylem) diameter at root maximum transverse diameter V51 mm 6.70 71.88 21.64 13.34 61.67
51 Root diameter of core (xylem) relative to total diameter V52 Code 1 5 1.55 1.13 73.03
52 Outer core (phloem) thickness at shoulder V53 mm 3.32 20.32 11.15 4.45 39.90
53 Outer core (phloem) thickness at root maximum transverse diameter V54 mm 2.88 23.32 12.65 4.97 39.29
54 Outer core (cortex) thickness at root maximum transverse diameter V55 mm 2.70 14.50 7.54 2.46 32.64
55 Inner core (xylem) pigmentation/color V56 Code 1 9 4.19 1.79 42.79
56 Outer core (phloem) pigmentation/color V57 Code 1 21 6.94 4.24 61.12
57 Outer core (cortex) pigmentation/color V58 Code 1 17 11.64 5.63 48.38
58 Green coloration of interior of the top (xylem) V59 Code 0 3 0.83 0.82 99.04
59 Green color of outer core (phloem+cortex) at shoulder V60 Code 0 3 0.64 1.01 158.44
60 White color in outer core (phloem+cortex) V61 Code 0 1 0.87 0.34 38.97
61 Homogeneity of core pigmentation/coloring throughout root length V62 Code 1 5 4.59 1.01 21.90
62 Flesh color distribution in transverse section V63 Code 1 5 2.54 1.20 47.05
63 Homogeneity of flesh coloring throughout root length V64 Code 1 5 3.72 1.57 42.23
64 Flesh color intensity V65 Code 1 5 4.30 1.45 33.67
65 Flesh palatability V66 Code 1 5 3.84 1.47 38.33
66 Total soluble solids V67 % 7.30 16.50 10.04 1.71 17.02
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TABLE 2.

Frequency distribution for the measured qualitative morphological characteristics in the studied P. sativa accessions.

Character 0 1 3 5 7 9 11 13 15 17 19 21
Foliage coverage ‐ 16 19 34 ‐ ‐ ‐ ‐
Leaf growth habit (attitude) ‐ Prostrate (51) Semi‐erect (17) Erect (1) ‐ ‐ ‐ ‐
Leaf hairiness ‐ Sparse (2) Intermediate (23) Dense (36) Very dense (8) ‐ ‐ ‐ ‐
Leaf type ‐ 5 55 6 3 ‐ ‐ ‐ ‐
Leaf dissection ‐ Slightly dissected (37) Intermediate (27) Highly dissected (5) ‐ ‐ ‐ ‐
Leaflet apex shape ‐ Round (4) Semi‐acute (32) Acute (33) ‐ ‐ ‐ ‐
Leaf color ‐ Yellow–green (5) Green (6) Gray‐green (16) Blue–green (17) Purple–green (25) ‐ ‐ ‐
Leaf color intensity ‐ Light (11) Intermediate (32) Dark (26) ‐ ‐ ‐ ‐
Petiole shape in transverse section ‐ Round (24) Semi‐round (41) Flat (4) ‐ ‐ ‐ ‐
Anthocyanin coloration in petiole None (15) Slightly colored (32) Intermediate (16) Strongly colored (6) ‐ ‐ ‐ ‐
Petiote hairiness ‐ Sparse (1) Intermediate (20) Dense (39) Very dense (9) ‐ ‐ ‐ ‐
Stem development in first year ‐ Stem consists of a small plate‐like crown (68) Stem elongates and forms branches (1) ‐ ‐ ‐ ‐
Root axis ‐ Not straight (8) Straight (61) ‐ ‐ ‐ ‐ ‐
Root branching None (60) Sparse (5) Intermediate (4) ‐ ‐ ‐ ‐ ‐
Lateral (secondary) root growth in accession None (56) Low (10) Medium (2) High (1) ‐ ‐ ‐ ‐
Emergence of lateral (secondary) roots on fleshy root None (56) Mostly on upper portion (3) Mostly on lower portion (9) All over (1) ‐ ‐ ‐ ‐
Hairy roots on storage root ‐ Low (59) Medium (7) High (3) ‐ ‐ ‐ ‐
Emergence of hairy roots on fleshy root ‐ Mostly on upper portion (2) Mostly on lower portion (26) All over (41) ‐ ‐ ‐ ‐
Root maximum transverse diameter position ‐ Upper portion (55) Middle (3) All over (11) ‐ ‐ ‐ ‐
Root shoulder shape ‐ Flat (13) Flat to rounded (23) Rounded (24) Rounded to conical (6) Conical (3) ‐ ‐ ‐
Extent of green color of skin on shoulder None (42) Low (19) Intermediate (6) High (2) ‐ ‐ ‐ ‐
Extent of purple color of skin on shoulder None (15) Low (14) Intermediate (14) High (26) ‐ ‐ ‐ ‐
Root surface ‐ Smooth (30) Dimpled (21) Ridged (7) Raised at the exit of the roots (11) ‐ ‐ ‐ ‐
Root splitting/cracking tendency None (63) Low (3) Intermediate (1) High (2) ‐ ‐ ‐ ‐
Root shape ‐ Tapering (33) Obtriangular (10) Narrow oblong (5) Wide oblong (5) Obovate (13) Fusiform (3) ‐ ‐ ‐
Root tapering None (6) Slight (13) Intermediate (20) Acute (30) ‐ ‐ ‐ ‐
Root tip/end shape ‐ Blunt (2) Rounded (19) Pointed (48) ‐ ‐ ‐ ‐
Root skin pigmentation/color ‐ Yellow–cream (8) Light yellow (6) Yellow–light orange (8) Cream–purple (2) Yellow–purple (4) Light orange–purple (1) Purple–cream (6) Purple–yellow (8) Purple–light orange (3) Purple (10) Dark purple (13)
Root skin color intensity ‐ Light (32) Dark (37) ‐ ‐ ‐ ‐ ‐
Root diameter of core (xylem) relative to total diameter ‐ Small (54) Intermediate (11) Large (4) ‐ ‐ ‐ ‐
Inner core (xylem) pigmentation/color ‐ Cream–yellow (11) Light yellow (12) Yellow (42) Dark yellow (2) Yellow–light orange (2) ‐ ‐ ‐
Outer core (phloem) pigmentation/color ‐ Cream (2) Cream–yellow (16) Light yellow (13) Yellow (23) Dark yellow (4) Cream–light orange (1) Yellow–light orange (4) Cream–purple (2) Yellow–purple (2) Purple–yellow (1) Dark purple (1)
Outer core (cortex) pigmentation/color ‐ Cream–yellow (7) Yellow–cream (1) Yellow (10) Yellow–light orange (3) Purple–cream (2) Purple–yellow (2) Light purple (10) Purple (13) Dark purple (21) ‐
Green coloration of interior of the top (xylem) None (24) Weak (39) Intermediate (6) ‐ ‐ ‐ ‐ ‐
Green color of outer core (phloem+cortex) at shoulder None (43) Weak (17) Intermediate (9) ‐ ‐ ‐ ‐ ‐
White color in outer core (phloem+cortex) Absent (9) Present (60) ‐ ‐ ‐ ‐ ‐
Homogeneity of core pigmentation/coloring throughout root length ‐ Low (3) Intermediate (8) High (58) ‐ ‐ ‐ ‐
Flesh color distribution in transverse section ‐ Color in two distinct outer and inner cores (22) Color radially distributed in stellate pattern (41) Color radially distributed from inner core (61) ‐ ‐ ‐ ‐
Homogeneity of flesh coloring throughout root length ‐ Low (13) Intermediate (8) High (38) ‐ ‐ ‐ ‐
Flesh color intensity ‐ Pale/dull (10) Intermediate (4) Bright/intense (55) ‐ ‐ ‐ ‐
Flesh palatability ‐ Low (10) Intermediate (20) High (39) ‐ ‐ ‐ ‐
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2.3. Statistical analysis

Analysis of variance (ANOVA) was performed to evaluate the variation among accessions based on the traits measured using SAS software (SAS® Procedures., 1990). Simple correlations between traits were determined using Pearson correlation coefficients (SPSS Inc; Norusis, 1998). Principal component analysis (PCA) was used to investigate the relationship between accessions and determine the main traits effective in genotype segregation using SPSS software. The PCA is the simplest of the true eigenvector‐based multivariate analyses. Often, its operation can be thought of as revealing the internal structure of the data in a way that best explains the variance in the data (Iezzoni & Pritts, 1991). Hierarchical cluster analysis (HCA) was performed using Ward's method and Euclidean coefficient with PAST software (Hammer et al., 2001). The first and second principal components (PC1/PC2) were used to create a scatter plot with PAST software.

3. RESULTS AND DISCUSSION

There were significant differences among the accessions investigated (ANOVA, p < .01). Coefficient of variation (CV) was more than 20.00% in the majority of measured characters (64 out of 66 characters), indicating high diversity among the accessions. The range of CV was from 17.02 (in total soluble solids) to 402.61% (in root splitting/cracking tendency) with an average of 64.69 (Table 1).

Foliage width (crown) ranged from 10 to 55 cm with an average of 32.32 (Table 1). Number of mature leaves per plant ranged from 5 to 47 with an average of 18.42. Leaf growth habit (attitude) was prostrate (51 accessions), semi‐erect (17), and erect (1) (Table 2; Figure 1). Mature leaf length varied between 110 and 356 mm. Mature leaf width ranged from 40.15 to 194.34 mm. The average value of petiole length, width, and thickness was 88.48, 3.42, and 2.71 mm, respectively.

FIGURE 1.

FIGURE 1

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Diversity between P. sativa accessions studied in terms of leaf characteristics, including shape; (a) celery, (b) celery but fern form, (c) parsley, (d) carrot.

Root shape was tapering (33), obtriangular (10), narrow oblong (5), wide oblong (5), obovate (13), and fusiform (3) (Figures 2 and 3). Root length ranged from 81.2 to 294 mm with an average of 166.44 mm. Root diameter at its middle point ranged from 15.58 to 125.12 mm with an average of 51.83 mm. Taproot length varied from 8.73 to 130.11 mm with an average of 49.61 mm. Root weight ranged from 15 to 1200 g with an average of 315.36 g.

FIGURE 2.

FIGURE 2

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Diversity between P. sativa accessions studied in terms of root length, width, and shape.

FIGURE 3.

FIGURE 3

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Diversity between P. sativa accessions studied in terms of root shape.

Inner core (xylem) diameter at shoulder ranged from 6.02 to 64.57 mm, while outer core (phloem) thickness at shoulder varied from 3.32 to 20.32 mm. Total soluble solids varied between 7.30 and 16.50% with an average of 10.04%. Outer core (phloem) pigmentation/color was predominantly yellow (23 accessions), while outer core (cortex) pigmentation/color was predominantly dark purple (21 accessions). Inner core (xylem) pigmentation/color was cream yellow (11 accessions), light yellow (12), yellow (42), dark yellow (2), and yellow–light orange (2) (Figure 4). The different root color in carrot (D. carota) was conferred by the Y and Y2 loci in chromosomes 5 and 7, respectively, in which Y_Y2_, yyY2_, Y_y2y2, and yyy2y2 genotypes represent white, yellow, pale orange, and orange root color, respectively (Cavagnaro et al., 2011; Ellison et al., 2017). Moreover, the purple root color was due to the deposition of anthocyanin, which was regulated by the genes in the P1 and P3 regions of chromosome 3 (Bannoud et al., 2019, 2021). Color is an important quality parameter of fruits and vegetables evaluated by consumers as it highly affects their marketability (Pathare et al., 2013). In the present study, root color varied greatly among the genetic resources. Most of the accessions showed a differential range of color attributes between the outer and inner parts of the root. This information might be useful for selecting the desired colored carrots because an appropriate color increases consumer acceptance (Nisha et al., 2011).

FIGURE 4.

FIGURE 4

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Inner sections of root of P. sativa accessions studied showing diversity in color.

Significant correlations were observed among some variables (Table 3). Foliage width (crown) showed significant and positive correlations with mature leaf length (r = 0.54), mature leaf width (r = 0.64), length of basal primary leaflet (r = 0.50), and petiole width (r = 0.51). Root length was significantly and positively correlated with root diameter at the middle point of the root (r = 0.55), root maximum transverse diameter (r = 0.53), taproot length (r = 0.35), neck diameter (r = 0.40), and collar diameter (r = 0.29). Root weight showed significant and positive correlations with foliage width (r = 0.52), mature leaf width (r = 0.54), length of basal primary leaflet (r = 0.35), petiole width (r = 0.43), petiole thickness (r = 0.52), root length (r = 0.66), and root diameter at the middle point of the root (r = 0.89). Total soluble solids were significantly and negatively correlated with root diameter at the middle point of the root (r = −0.39), root maximum transverse diameter (r = −0.42), taproot length (r = −0.32), root diameter at shoulder (r = −0.43), and root weight (r = −0.43).

TABLE 3.

Simple correlations among the quantitative morphological variables utilized in the studied P. sativa accessions.

Character V3 V6 V7 V15 V17 V18 V19 V30 V31 V32 V35 V36 V37 V38 V42 V51 V53 V54 V55 V67
V3 1
V6 0.54** 1
V7 0.64** 0.51** 1
V15 0.50** 0.58** 0.51** 1
V17 0.02 0.65** 0.00 0.29* 1
V18 0.51** 0.18 0.61** 0.20 −0.32** 1
V19 0.57** 0.07 0.60** 0.37** −0.44** 0.63** 1
V30 0.35** 0.19 0.21 0.19 −0.08 0.14 0.33** 1
V31 0.51** 0.09 0.51** 0.28* −0.45** 0.43** 0.55** 0.46** 1
V32 0.59** 0.26* 0.55** 0.35** −0.29* 0.38** 0.53** 0.57** 0.93** 1
V35 0.41** 0.16 0.35** 0.25* −0.27* 0.38** 0.35** 0.27* 0.51** 0.49** 1
V36 0.42** 0.28* 0.32** 0.37** −0.10 0.34** 0.40** 0.56** 0.55** 0.59** 0.47** 1
V37 0.42** 0.35** 0.39** 0.42** 0.04 0.24* 0.29* 0.51** 0.61** 0.73** 0.38** 0.76** 1
V38 0.49** 0.23 0.40** 0.38** −0.16 0.29* 0.42** 0.55** 0.82** 0.87** 0.46** 0.76** 0.89** 1
V42 0.52** 0.23 0.54** 0.35** −0.28* 0.43** 0.52** 0.66** 0.89** 0.92** 0.50** 0.67** 0.75** 0.86** 1
V51 0.48** 0.26* 0.45** 0.34** −0.14 0.35** 0.40** 0.61** 0.82** 0.86** 0.46** 0.75** 0.80** 0.90** 0.92** 1
V53 0.40** 0.00 0.29* 0.24* −0.33** 0.23 0.43** 0.39** 0.77** 0.75** 0.43** 0.49** 0.60** 0.81** 0.67** 0.64** 1
V54 0.36** 0.06 0.29* 0.23 −0.28* 0.22 0.38** 0.30* 0.69** 0.67** 0.37** 0.50** 0.57** 0.73** 0.57** 0.56** 0.81** 1
V55 0.29* 0.25* 0.32** 0.25* 0.06 0.19 0.14 0.08 0.36** 0.39** 0.20 0.39** 0.47** 0.52** 0.36** 0.38** 0.23 0.16 1
V67 −0.23* −0.22 −0.22 −0.07 0.03 −0.09 0.03 −0.18 −0.39** −0.42** −0.32** −0.20 −0.29* −0.35** −0.43** −0.36** −0.30* −0.24* −0.26* 1
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Note: For the explanation of the character symbols, see Table 1.

*, **. Correlation is significant at p ≤ .05 and 0.01 levels, respectively.

The PCA showed 18 independent components that explained 81.98% of the total variance (Table 4). The PC1 showed positive correlations with number of mature leaves per plant, root length, root diameter at the middle point of the root, root maximum transverse diameter, neck diameter, collar diameter, root diameter at shoulder, root weight, inner core (xylem) diameter at shoulder, inner core (xylem) diameter at root maximum transverse diameter, root diameter of core (xylem) relative to total diameter, outer core (phloem) thickness at shoulder, and outer core (phloem) thickness at root maximum transverse diameter that explained 22.25% of the total variance. Root shape, root tapering, and root tip/end shape were loaded on PC2 and accounted for 7.45% of the total variance. The PC3 was correlated with mature leaf length, length of basal primary leaflet, number of segment tips on lower primary leaflet, and petiole length, accounting for 6.98% of the total variance. Based on the scatter plot generated using PC1 and PC2, the accessions were placed into four groups and most of them were placed in the center of plot (Figure 5). PCA has been previously used to investigate the phenotypic diversity of most plants (Khadivi et al., 2021; Khadivi, Mirheidari, & Moradi, 2022; Khadivi, Mirheidari, Saeidifar, & Moradi, 2022; Khadivi & Mirheidari, 2021; Moradi et al., 2022; Safdari & Khadivi, 2021).

TABLE 4.

Eigenvalues of the principal component axes from the PCA of the morphological characters in the studied P. sativa accessions.

Character Component
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
V2 0.35 0.24 −0.01 0.01 0.77 −0.05 0.04 0.14 −0.14 −0.09 0.09 −0.05 −0.01 −0.02 0.10 0.03 −0.02 0.01
V3 0.45 0.06 0.52 −0.01 0.43 0.05 −0.04 0.10 −0.09 −0.02 0.21 0.16 0.01 0.04 0.05 −0.21 −0.17 −0.12
V4 −0.24 −0.20 0.26 0.00 −0.53 −0.14 0.49 0.10 0.03 −0.13 −0.21 0.01 −0.21 0.08 −0.06 0.04 −0.11 −0.13
V5 0.59 −0.08 −0.17 0.05 0.57 −0.03 −0.04 0.07 0.01 −0.06 0.00 −0.16 −0.20 −0.07 0.05 0.06 −0.02 0.00
V6 0.23 −0.08 0.83 −0.07 −0.07 0.02 0.14 0.19 0.07 0.02 −0.01 0.07 −0.07 −0.03 −0.10 0.07 −0.08 −0.16
V7 0.34 0.20 0.55 0.11 0.38 0.04 −0.07 0.37 −0.10 0.08 0.09 0.03 −0.13 0.04 −0.15 −0.15 0.08 0.03
V8 0.16 0.02 0.00 0.14 0.02 0.03 −0.13 0.89 0.07 0.07 −0.02 −0.02 0.13 −0.12 0.05 0.01 0.10 −0.05
V9 −0.33 −0.14 0.01 −0.22 −0.12 −0.01 0.08 0.03 −0.24 0.05 0.10 0.07 0.14 0.69 −0.17 −0.09 0.13 −0.02
V10 −0.28 −0.20 0.27 0.21 0.02 −0.23 0.20 −0.13 −0.05 −0.04 −0.17 0.07 −0.23 0.63 0.11 0.03 0.04 −0.06
V11 0.11 0.17 −0.07 0.10 0.04 0.07 −0.04 0.03 −0.14 0.02 0.17 0.08 0.85 −0.06 0.04 −0.05 0.04 0.08
V12 0.17 0.01 0.09 0.06 0.13 0.04 0.06 −0.13 0.07 0.07 0.81 −0.15 0.16 −0.06 0.00 0.09 −0.08 0.05
V13 0.12 0.27 −0.15 −0.09 0.28 −0.28 0.00 0.04 −0.02 0.04 0.70 0.16 0.04 0.07 −0.02 −0.18 0.07 −0.06
V14 0.44 0.25 0.40 0.00 0.09 0.12 −0.02 0.09 −0.09 −0.04 0.23 −0.01 0.02 0.07 0.41 −0.21 0.16 0.03
V15 0.31 −0.06 0.71 0.10 0.16 −0.27 −0.10 0.06 0.08 −0.03 −0.03 −0.01 0.23 0.06 0.06 −0.02 0.07 0.16
V16 0.09 0.09 0.72 0.00 −0.03 0.00 −0.29 −0.32 0.11 0.03 0.11 0.06 −0.02 0.18 0.11 0.13 0.00 0.13
V17 −0.16 −0.24 0.64 −0.12 −0.40 −0.15 0.31 −0.07 0.16 0.08 −0.24 0.02 −0.12 −0.01 0.01 0.02 −0.04 −0.08
V18 0.25 0.19 0.09 0.12 0.55 −0.02 −0.03 0.38 0.07 0.09 0.25 0.34 −0.16 −0.12 −0.15 0.08 0.04 −0.04
V19 0.33 0.12 0.12 0.27 0.66 0.00 −0.15 0.26 0.05 −0.03 0.20 0.07 0.22 −0.07 −0.03 −0.06 0.04 0.08
V20 −0.03 0.07 0.55 −0.22 −0.07 0.08 −0.14 0.05 0.00 0.23 −0.05 0.17 −0.25 −0.04 0.38 −0.32 0.13 −0.04
V21 −0.09 −0.13 0.16 −0.08 0.10 0.05 0.25 0.38 −0.09 0.17 0.38 0.28 −0.31 −0.09 0.22 −0.33 0.17 −0.10
V22 0.05 −0.06 0.08 −0.05 0.21 −0.09 −0.03 0.86 0.05 0.01 −0.07 −0.11 −0.07 0.16 0.00 0.10 0.01 0.04
V23 −0.05 0.01 −0.05 −0.01 −0.08 0.10 0.85 −0.15 −0.05 −0.22 0.11 0.03 −0.09 0.16 −0.01 0.07 −0.04 0.03
V24 0.04 0.01 −0.02 0.09 0.23 0.08 0.09 0.09 −0.37 −0.04 −0.01 0.02 −0.05 0.06 −0.15 −0.07 0.72 0.10
V25 0.02 0.19 −0.01 0.00 −0.24 −0.03 −0.05 0.15 0.69 −0.07 0.11 −0.06 −0.18 −0.07 −0.03 −0.08 −0.24 0.07
V26 0.25 0.05 0.05 0.01 −0.04 −0.13 0.07 −0.03 0.88 0.05 −0.04 0.01 −0.04 −0.10 0.00 0.01 0.01 0.08
V27 0.06 −0.02 0.11 0.04 0.11 0.21 −0.03 0.03 0.87 −0.09 0.00 0.00 0.03 0.01 0.00 0.10 −0.07 −0.07
V28 −0.07 0.01 −0.02 0.11 0.21 0.30 0.17 −0.08 0.01 −0.04 0.02 −0.13 −0.09 −0.02 −0.17 −0.02 ### 0.12
V29 0.17 0.00 −0.02 0.06 0.02 −0.04 0.09 −0.03 0.05 −0.10 0.00 −0.01 0.06 −0.05 −0.03 0.03 −0.04 0.84
V30 0.67 −0.25 0.04 0.05 0.19 0.21 0.41 −0.01 −0.09 −0.06 0.13 −0.18 0.18 −0.06 0.08 0.05 −0.01 0.11
V31 0.80 0.36 −0.02 0.11 0.28 0.11 −0.19 0.03 −0.07 0.02 0.14 −0.04 −0.02 0.04 0.04 −0.03 0.07 0.00
V32 0.87 0.19 0.12 0.11 0.20 0.10 −0.15 0.06 −0.11 −0.01 0.14 0.00 −0.01 0.08 0.09 −0.04 0.03 −0.04
V33 −0.13 0.56 −0.10 −0.17 0.26 0.06 −0.08 −0.09 −0.05 −0.07 0.07 −0.06 −0.13 −0.19 −0.39 −0.07 0.07 0.02
V34 −0.35 −0.38 −0.09 −0.10 −0.07 −0.02 0.72 −0.07 0.11 −0.07 −0.05 −0.16 0.11 −0.05 −0.03 0.06 −0.02 0.16
V35 0.46 0.19 0.09 0.10 0.16 −0.03 −0.17 0.20 −0.01 −0.08 0.25 −0.04 −0.23 0.04 0.19 0.17 −0.19 0.25
V36 0.79 −0.02 0.10 −0.04 0.07 −0.07 0.03 0.08 0.17 0.05 0.10 0.08 0.14 −0.25 −0.17 0.12 −0.15 0.09
V37 0.87 0.01 0.22 −0.01 −0.11 −0.08 −0.10 −0.01 0.10 0.05 −0.06 0.10 0.04 −0.01 0.01 0.07 −0.01 0.07
V38 0.93 0.20 0.10 0.08 0.03 −0.02 −0.09 −0.01 0.06 0.06 −0.02 0.05 0.06 −0.07 0.11 0.00 −0.04 0.04
V39 0.00 0.29 0.14 0.19 0.43 0.30 −0.12 −0.07 0.02 0.24 0.17 −0.28 0.10 −0.01 −0.16 0.10 −0.09 −0.05
V40 0.19 −0.02 −0.09 −0.24 −0.10 0.80 0.18 0.05 −0.04 0.00 0.00 −0.11 0.00 0.03 0.11 0.03 −0.13 −0.02
V41 0.14 0.05 −0.01 0.87 −0.03 −0.20 0.10 −0.01 0.02 0.13 0.09 −0.02 0.02 −0.07 −0.01 −0.03 −0.04 −0.01
V42 0.90 0.15 0.08 0.08 0.20 0.10 −0.02 0.11 0.03 0.00 0.09 −0.01 0.02 0.11 0.01 −0.05 0.11 0.06
V43 0.33 −0.06 −0.02 0.12 −0.25 0.13 0.11 0.02 0.06 −0.23 0.22 −0.03 0.04 0.08 −0.03 0.49 −0.09 0.22
V44 0.27 0.06 0.05 −0.03 0.00 −0.02 −0.05 −0.28 −0.03 −0.08 0.08 0.05 0.19 0.22 0.06 −0.61 0.00 −0.03
V45 0.27 0.69 −0.02 0.10 0.10 0.09 −0.17 0.05 0.09 −0.04 0.27 0.13 0.09 −0.05 −0.03 0.20 0.01 −0.13
V46 −0.38 −0.81 −0.01 0.02 −0.11 −0.01 0.07 0.00 −0.11 −0.02 0.04 −0.04 −0.18 0.01 −0.14 0.09 −0.06 −0.03
V47 −0.30 ### −0.01 0.00 −0.07 0.12 0.00 0.01 −0.06 −0.02 0.00 0.04 −0.03 −0.02 −0.07 0.11 0.09 −0.10
V48 0.19 0.04 −0.07 0.83 0.14 −0.38 −0.01 0.09 0.08 0.01 0.05 −0.02 −0.01 −0.02 −0.03 0.05 0.04 0.10
V49 0.03 −0.02 0.03 0.83 0.03 0.12 −0.11 0.06 −0.14 0.01 −0.12 0.07 0.20 0.04 0.06 0.01 −0.02 −0.03
V50 0.92 0.03 0.05 0.06 0.06 −0.05 0.03 0.05 0.22 0.09 0.02 0.02 −0.02 −0.06 −0.07 −0.06 0.10 0.07
V51 0.94 0.13 0.08 0.05 0.06 0.02 0.04 0.04 0.13 0.06 0.03 −0.02 −0.02 −0.03 −0.06 −0.08 0.08 0.03
V52 0.62 −0.05 −0.09 0.09 −0.07 0.04 0.45 0.11 −0.06 −0.02 0.04 0.03 0.05 0.01 −0.44 0.02 0.10 0.15
V53 0.69 0.29 −0.05 0.03 0.16 0.08 −0.19 −0.03 −0.02 0.01 0.03 −0.01 0.13 −0.13 0.47 −0.08 −0.06 −0.01
V54 0.58 0.46 0.07 −0.10 0.20 0.01 −0.20 −0.14 0.06 −0.04 0.05 −0.09 0.05 −0.24 0.32 0.12 −0.03 −0.07
V55 0.43 0.17 0.22 0.19 −0.14 0.00 −0.12 0.15 −0.14 0.35 −0.17 0.27 −0.03 0.11 −0.15 0.06 −0.18 0.07
V56 0.19 0.04 0.01 0.20 0.00 0.01 0.07 0.11 −0.04 0.31 −0.04 0.36 0.08 −0.06 0.42 −0.02 0.20 0.44
V57 0.01 0.03 0.13 0.08 0.00 −0.10 −0.06 −0.12 −0.02 −0.02 −0.02 0.82 0.08 0.03 0.03 −0.01 0.09 −0.01
V58 0.04 −0.08 −0.04 0.80 0.11 −0.36 −0.03 −0.02 0.12 −0.05 0.01 0.10 −0.12 −0.03 −0.01 0.00 0.01 0.10
V59 −0.08 −0.12 −0.11 −0.14 0.25 0.71 −0.04 −0.06 0.06 −0.17 −0.20 −0.02 −0.03 −0.14 −0.14 −0.07 0.16 0.02
V60 0.05 0.08 0.00 −0.27 −0.04 0.85 −0.05 −0.04 0.04 −0.02 0.04 −0.01 0.08 0.03 0.04 0.03 −0.11 −0.02
V61 0.16 0.15 −0.25 0.26 0.03 0.12 −0.11 −0.16 0.09 −0.18 −0.01 −0.32 −0.27 0.17 −0.23 0.34 0.20 0.24
V62 0.03 −0.05 0.13 −0.30 0.32 −0.13 0.15 −0.16 0.02 0.22 −0.05 0.12 0.16 0.14 0.09 0.55 −0.02 −0.26
V63 0.50 0.27 −0.04 0.19 0.20 −0.16 −0.13 −0.12 −0.01 −0.29 0.01 −0.01 0.13 −0.29 0.05 0.14 −0.10 0.03
V64 0.06 0.09 0.04 −0.05 0.02 −0.04 −0.05 0.16 −0.14 0.69 0.26 −0.31 0.09 −0.04 0.09 0.16 0.12 −0.18
V65 0.03 −0.10 0.04 0.02 0.04 0.05 −0.10 −0.06 0.03 0.84 −0.04 −0.03 0.04 0.03 −0.01 −0.09 −0.03 −0.07
V66 0.08 0.05 0.00 0.13 −0.07 −0.29 −0.16 0.09 −0.02 0.72 0.03 0.30 −0.13 0.06 0.03 0.06 −0.03 0.12
V67 −0.39 −0.22 −0.06 0.11 0.05 −0.11 0.01 −0.15 −0.01 −0.17 0.04 0.21 0.19 −0.46 −0.14 −0.01 0.16 0.13
Total 14.68 4.92 4.61 4.33 3.36 2.81 2.48 2.16 2.12 1.96 1.75 1.52 1.43 1.33 1.27 1.17 1.15 1.08
% of variance 22.25 7.45 6.98 6.56 5.09 4.25 3.76 3.27 3.21 2.97 2.65 2.30 2.16 2.02 1.92 1.78 1.74 1.63
Cumulative % 22.25 29.70 36.68 43.24 48.32 52.58 56.34 59.60 62.82 65.79 68.44 70.74 72.90 74.92 76.84 78.62 80.35 81.98
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Note: Bold values indicate the characteristics most influencing PCs.

For the explanation of the character symbols, see Table 1.

FIGURE 5.

FIGURE 5

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Scatter plot for the studied P. sativa accessions based on PC1/PC2.

In the cluster analysis based on Ward's method, the accessions were divided into two main clusters according to morphological traits (Figure 6). The first cluster (I) consisted of 27 accessions, forming two sub‐clusters. Sub‐cluster I‐A consisted of 12 accessions and sub‐cluster I‐B contained 15 accessions. The rest of the accessions were classified into the second cluster (I), forming two sub‐clusters. Sub‐cluster II‐A included 28 accessions, while 14 accessions formed sub‐cluster II‐B. The discrepancy between the cluster and scatter dendrograms can be explained by the variability considered for the analysis. Cluster analysis was based on all the morphological data and took into account the whole variability, while the scatter plot was created using the cumulative variance of PC1 and PC2 and was relatively low (29.70%).

FIGURE 6.

FIGURE 6

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Ward cluster analysis of the studied P. sativa accessions based on morphological traits using Euclidean distances.

Forgotten plant species can play a significant role in providing food security and improving the quality level of nutrition which is a herald of food security. By removing these types of plants from the human food basket, its consequences will be determined according to the inevitable effects of climate change on food production (Koocheki et al., 2018). With the expansion of carrot cultivation, the attention to parsnip decreased and the cultivation of this medicinal plant is low. This is despite the fact that parsnip is part of the medicinal native plant and valuable in most farms in tropical cities. Compared with carrots, parsnip plants are more adaptable to different environmental conditions.

Based on ideal values of the important and commercial characters of parsnip, such as root length, root weight, inner core (xylem) pigmentation/color, root shape, flesh color intensity, flesh palatability, and total soluble solids, 14 accessions, including Parsnip‐3, Parsnip‐9, Parsnip‐24, Parsnip‐32, Parsnip‐32, Parsnip‐48, Parsnip‐51, Parsnip‐52, Parsnip‐58, Parsnip‐60, Parsnip‐62, Parsnip‐65, Parsnip‐67, and Parsnip‐69, were promising and are recommended for cultivation. These accessions could be considered for future breeding programs as yield is one of the parameters that is considered in commercial breeding programs (Tabor et al., 2016). However, analysis of seasonal and yearly variations might be useful for gathering information for stable production. The wide variability in both qualitative and quantitative traits found in this study might be useful for identifying genotypes and might be required for the genetic improvement of crops (Hooks et al., 2021; Luitel et al., 2018). It has been reported that differential expression of a number of genes located in chromosomes 1, 2, and 7 is responsible for the differences in root characteristics of carrots (Macko‐Podgorni et al., 2020; Turner et al., 2018). The selected accessions with higher weight and uniform size can be used for future breeding programs. Overall, the results of the present study might be useful for selecting candidate genotypes with better growth performance and higher yield. To the best of our knowledge, this is the first report showing morphological variability in parsnip genetic resources of diverse origins.

4. CONCLUSIONS

The best method of propagation of parsnips is mainly through seed. Parsnip seeds have a high healing power and do not require any treatment for germination, so it is recommended that the seeds of this plant are collected in the middle of summer and planted directly in the field. Due to unique features of this plant, such as adaptability, resistant to drought, heat, and salinity of water and soil, parsnip as an agricultural and medicinal plant is recommended for cultivation in fields with salty desert soils. In addition to numerous uses and applications for food and medicinal value of the roots of this native plant, the ringed leaves of parsnip can also be fed to livestock as fresh winter fodder (with high nutritional value). Also, for each hectare of fields cultivated with parsnip, average of 2 to 3 tons of seeds per hectare is harvested. The accessions studied here showed high phenotypic diversity and some of them can be selected and cultivated. Therefore, the promotion and development of parsnip plant cultivation, as a native plant adaptable to ecological conditions, is recommended. Based on ideal values of the important and commercial characters of parsnip, such as root length, root weight, inner core (xylem) pigmentation/color, root shape, flesh color intensity, flesh palatability, and total soluble solids, 14 genotypes, including Parsnip‐3, Parsnip‐9, Parsnip‐24, Parsnip‐32, Parsnip‐32, Parsnip‐48, Parsnip‐51, Parsnip‐52, Parsnip‐58, Parsnip‐60, Parsnip‐62, Parsnip‐65, Parsnip‐67, and Parsnip‐69, were promising and are recommended for cultivation.

AUTHOR CONTRIBUTIONS

Ali Khadivi: Formal analysis (lead); investigation (equal); methodology (lead); software (lead); validation (lead); writing – original draft (lead); writing – review and editing (lead). Farhad Mirheidari: Investigation (equal). Younes Moradi: Investigation (equal).

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

ACKNOWLEDGMENTS

None.

Khadivi, A. , Mirheidari, F. , & Moradi, Y. (2023). Morphological characterizations of parsnip (Pastinaca sativa L.) to select superior genotypes. Food Science & Nutrition, 11, 3858–3874. 10.1002/fsn3.3371

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

REFERENCES

  1. Bahrami, R. , Ghobadi, A. , Behnoud, N. , & Akhtari, E. (2018). Medicinal properties of Daucus carota in traditional Persian medicine and modern phytotherapy. Journal of Biochemtry of Technoloy, 9, 107–114. [Google Scholar]
  2. Bannoud, F. , Carvajal, S. , Ellison, S. , Senalik, D. , Gomez Talquenca, S. , Iorizzo, M. , Simon, P. W. , & Cavagnaro, P. F. (2021). Genetic and transcription profile analysis of tissue‐specific anthocyanin pigmentation in carrot root phloem. Genes, 12, 1464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bannoud, F. , Ellison, S. , Paolinelli, M. , Horejsi, T. , Senalik, D. , Fanzone, M. , Iorizzo, M. , Simon, P. W. , & Cavagnaro, P. F. (2019). Dissecting the genetic control of root and leaf tissue‐specific anthocyanin pigmentation in carrot (Daucus carota L.). Theoretical and Applied Genetics, 132, 2485–2507. [DOI] [PubMed] [Google Scholar]
  4. Berenbaum, M. R. (1985). Brementown revisited: Interactions among allelochemicals in plants. Recent Advances in Phytochemistry, 19, 139–169. 10.1007/978-1-4757-9658-2_6 [DOI] [Google Scholar]
  5. Castro, A. , Bergenstahl, B. , & Tornberg, E. (2012). Parsnip (Pastinaca sativa L.): Dietary fibre composition and physicochemical characterization of its homogenized suspensions. Food Research International, 48, 598–608. 10.1016/j.foodres.2012.05.023 [DOI] [Google Scholar]
  6. Cavagnaro, P. F. , Chung, S. M. , Manin, S. , Yildiz, M. , Ali, A. , Alessandro, M. S. , Iorizzo, M. , Senalik, D. A. , & Simon, P. W. (2011). Microsatellite isolation and marker development in carrot genomic distribution, linkage mapping, genetic diversity analysis and marker transferability across Apiaceae. BMC Genomics, 2011(12), 386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Downie, S. R. , Ramanath, S. , Katz‐Downie, D. S. , & Llanas, E. (1998). Molecular systematics of Apiaceae subfamily Apioideae: Phylogenetic analyses of nuclear ribosomal DNA internal transcribed spacer and plastid rpoC1 intron sequences. American Journal of Botany, 85, 563–591. 10.2307/2446441 [DOI] [PubMed] [Google Scholar]
  8. Drude, C. G. O. (1897. –1898). Umbelliferae. In Engler A. & Prantl K. (Eds.), Die naturlichen Pflanzenfamilien (Vol. 3, pp. 63–250). Wilhelm Engelmann. [Google Scholar]
  9. Ellison, S. , Senalik, D. , Bostan, H. , Iorizzo, M. , & Simon, P. (2017). Fine mapping, transcriptome analysis, and marker development for Y2, the gene that conditions b‐carotene accumulation in carrot (Daucus carota L.). G3: Genes, Genomes, Genetics, 7, 2665–2675. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Emami, A. , Fasihi, S. , & Mehregan, I. (2010). Reference book on medicinal plants (p. 1002). Islamic and Complementary Medicine at Iran University of Medical Sciences. [Google Scholar]
  11. Gleason, H. A. , & Cronquist, A. (1991). Manual of vascular plants of northeastern United States and adjacent Canada (2nd ed., p. 910). New York Botanical Garden. [Google Scholar]
  12. Grant, M. (2000). Galen on food and diet (p. 151). Routledge. [Google Scholar]
  13. Greene, S. L. , Gritsenko, M. , & Vandewark, G. (2004). Relating morphologic and RAPD marker variation to collecting site environment in wild population of red clover (Trifolium pretense L.). Genetic Resources and Crop Evolution, 51, 643–653. [Google Scholar]
  14. Hammer, Ø. , Harper, D. A. T. , & Ryan, P. D. (2001). PAST: Paleontological statistics software package for education and data analy‐sis. Palaeontologia Electronica, 4(1), 9 http://palaeoelectronica.org/2001_1/past/issue1_01.htm [Google Scholar]
  15. Harrewijn, P. , Minks, A. K. , & Mollema, C. (1994). Evolution of plant volative production in insect–plant relationships. Chemoecology, 5(6), 55–73. 10.1007/BF01259434 [DOI] [Google Scholar]
  16. Hooks, T. , Niu, G. , Masabni, J. , & Sun, Y. (2021). Ganjegunte, G. performance and phytochemical content of 22 pomegranate (Punica granatum) varieties. HortScience, 56, 217–225. [Google Scholar]
  17. Iezzoni, A. F. , & Pritts, M. P. (1991). Applications of principal component analysis to horticultural research. HortScience, 26, 334–338. 10.21273/HORTSCI.26.4.334 [DOI] [Google Scholar]
  18. IPGRI . (1998). Descriptors for wild and cultivated carrots (Daucus carota L.). International Plant Genetic Resources Institute. [Google Scholar]
  19. Khadivi, A. , & Mirheidari, F. (2021). Selection of the promising fig (Ficus carica L.) accessions using fruit‐related characters. Food Science & Nutrition, 10, 2911–2921. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Khadivi, A. , Mirheidari, F. , & Moradi, Y. (2022). Selection of superior accessions of turnip (Brassica rapa var. rapa L.) based on tuber quality‐related characters. Food Science & Nutrition, 10, 2667–2680. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Khadivi, A. , Mirheidari, F. , Moradi, Y. , & Paryan, S. (2021). Identificationof superior jujube (Ziziphus jujuba mill.) genotypes based on mor‐phological and fruit characterizations. Food Sciences and Nutrition, 9, 3165–3176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Khadivi, A. , Mirheidari, F. , Saeidifar, A. , & Moradi, Y. (2022). Selection of the promising accessions of jamun (Syzygium cumini (L.) skeels) based on pomological characterizations. Food Science & Nutrition, 11, 470–480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Koocheki, A. , Rezvani Moghaddam, P. , Asgari, A. , & Rostami, R. (2018). Identification and evaluation of agronomic and ecological neglected crops in agroecosystems of Iran: 2 – introduction of under utilized and neglected crops. Journal of Agroecology, 10, 353–367. [Google Scholar]
  24. Luitel, B. P. , Ro, N.‐Y. , Ko, H.‐C. , Sung, J.‐S. , Rhee, J.‐H. , & Hur, O.‐S. (2018). Phenotypic variation in a germplasm collection of pepper (Capsicum chinense Jacq.) from Korea. Journal of Crop Science and Biotechnology, 21, 499–506. [Google Scholar]
  25. Macko‐Podgorni, A. , Stelmach, K. , Kwolek, K. , Machaj, G. , Ellison, S. , Senalik, D. A. , Simon, P. W. , & Grezebelus, D. (2020). Mining for candidate genes controlling secondary growth of the carrot storage root. International Journal of Molecular Sciences, 21, 4263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Matejić, J. S. , Džamić, A. M. , Mihajilov‐Krstev, T. , Ranđelović, V. N. , Krivošej, Z. Đ. , & Marin, P. D. (2014). Antimicrobial potential of essential oil from Pastinaca sativa L. Biologica Nyssana, 5, 31–35. [Google Scholar]
  27. Moradi, Y. , Khadivi, A. , & Mirheidari, F. (2022). Multivariate analysis of oriental apple (Malus orientalis Uglitzk). Based on phenotypic and pomological characterizations. Food Science & Nutrition, 10, 2532–2541. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Nisha, P. , Singhal, R. S. , & Pandit, A. B. (2011). Kinetic modelling of colour degradation in tomato puree (Lycopersicon esculentum L.). Food and Bioprocess Technology, 4, 781–787. [Google Scholar]
  29. Norusis, M. J. (1998). SPSS/PC advanced statistics. SPSS Inc. [Google Scholar]
  30. Pathare, P. B. , Opara, U. L. , & Al‐Said, F. A. J. (2013). Colour measurement and analysis in fresh and processed foods: A review. Food and Bioprocess Technology, 6, 36–60. [Google Scholar]
  31. Safdari, L. , & Khadivi, A. (2021). Identification of the promising oleaster (Elaeagnus angustifolia l.) genotypes based on fruit quality‐related characters. Food Science & Nutrition, 9, 5712–5721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. SAS® Procedures . (1990). Version 6 (3rd ed.). SAS Institute. [Google Scholar]
  33. Stannard, J. (1982). Medicinal plants and folk remedies in Pliny, Historia naturalis. History and Philosophy of Life Sciences, 4, 3–23. [PubMed] [Google Scholar]
  34. Sternberg, M. , Brown, V. K. , Masters, G. J. , & Clarke, I. P. (1999). Plant community dynamics in a calcareous grassland under climate change manipulations. Plant Ecology, 143, 29–37. 10.1023/A:1009812024996 [DOI] [Google Scholar]
  35. Stolarczyk, J. , & Janick, J. (2011). Carrot: History and iconography. Chron Horticult, 51, 13–18. [Google Scholar]
  36. Tabor, G. , Yesuf, M. , Haile, M. , Kebede, G. , & Tilahun, S. (2016). Performance of some Asian carrot (Daucus carota L. spp. sativa Hoffm.) cultivars under Ethiopian conditions: Carrot and seed yields. Scientia Horticulturae, 207, 176–182. [Google Scholar]
  37. Theobald, W. L. (1971). Comparative anatomical and developmental studies in the Umbelliferae. In Heywood V. H. (Ed.), The biology and chemistry of the Umbelliferae (pp. 177–197). Academic Press. [Google Scholar]
  38. Turner, S. D. , Ellison, S. L. , Senalik, D. A. , Simon, P. W. , Spalding, E. P. , & Miller, N. D. (2018). An automated image analysis pipeline enables genetic studies of shoot and root morphology in carrot (Daucus carota L.). Frontiers in Plant Science, 9, 1703. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Tutin, T. G. (1980). Umbellifers of the British Isles (p. 197). Botanical Society of the British Isles. [Google Scholar]
  40. Zangerl, A. R. , & Berenbaum, M. R. (1993). Plant chemistry, insect adaptations to plant chemistry, and host plant utilization patterns. Ecology, 74, 47–54. 10.2307/1939500 [DOI] [Google Scholar]
  41. Zomlefer, W. B. (1994). Guide to flowering plant families (p. 430). The University of North Carolina Press. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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