Next Article in Journal
Comparative Analysis of Ratoon-Competent and Ratoon-Deficient Sugarcane by Hormonal and Transcriptome Profiling
Previous Article in Journal
Potassium Fulvate Alleviates Salinity and Boosts Oat Productivity by Modifying Soil Properties and Rhizosphere Microbial Communities in the Saline–Alkali Soils of the Qaidam Basin
Previous Article in Special Issue
From Waste to Resource: Mineral and Biochemical Characterization of Hemp By-Products in the Fiber and Seed Supply Chain
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 15
Issue 7
10.3390/agronomy15071675
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Potential Expansion of Root Chicory Cultivation Areas in Chile

by
Donna Cortez
1,
Manuel Paneque
2 and
Celián Román-Figueroa
1,*
1
Bionostra Chile Research Foundation, San Miguel, Santiago 8920033, Chile
2
Facultad de Ciencias Agronómicas, Universidad de Chile, La Pintana, Santiago 8820808, Chile
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(7), 1675; https://doi.org/10.3390/agronomy15071675
Submission received: 27 May 2025 / Revised: 30 June 2025 / Accepted: 5 July 2025 / Published: 10 July 2025
(This article belongs to the Special Issue Industrial Crops Production in Mediterranean Climate)
Browse Figures
Versions Notes

Abstract

Root chicory (Cichorium intybus var. sativum) is a major source of inulin, a fiber with many dietary and medicinal uses. Chile is the only country outside Europe that produces inulin and is the third largest exporter worldwide. Root chicory cultivation has increased by 242% in Chile since 2006, highlighting its potential for expansion into new territories. In this study, land suitability (without restriction, mild restriction, moderate restriction, and unsuitable) for root chicory cultivation and its potential productivity were determined using Geographic Information System (GIS) and analytical hierarchy process (AHP). The regions where root chicory is currently produced (between the Maule and La Araucanía regions) showed the best suitability, as did the Valparaíso and O’Higgins regions. The potential maximum productivity ranged from 20 to 27 t DW ha−1, mainly concentrated in the Los Lagos region, despite the absence of land without restriction. This could be attributed to the high water availability in this region, which is consistent with the expected displacement of crop areas due to climate change. Field studies in the Los Lagos region are recommended to evaluate the feasibility of expanding root chicory cultivation in these areas.

1. Introduction

Chicory (Cichorium intybus L.) is a perennial herb native to the Mediterranean zone of Europe. Currently, chicory is extensively cultivated in its native distribution, northern Africa, Central Asia, Eastern USA, Australia, and other regions [1,2]. Chicory is a multipurpose crop, and its aerial and root parts are utilized by various industries, including the food, nutraceutical, and energy industries [3], four kinds of chicory are recognized: root chicory, witloof chicory or Belgian endive, leaf or salad chicory, and livestock or forage chicory [4]. Root chicory (C. intybus var. sativum) is a biennial plant that requires vernalization to flower. The international market of root chicory had a value of USD 739 million in 2022 and is projected to grow by 6.5% per year [4]. The taproot accumulates inulin during the first year of growth, which is mobilized by the plant during the second year to sustain the reproductive phase, thereby reducing the inulin yield of the root; therefore, to increase inulin production, it is cultivated as an annual crop for industrial purposes [5]. Inulin is a fiber used as a bioactive prebiotic, fat and sugar replacer, texture modifier, food stabilizer, and thickening agent. It also has positive effects on health by influencing lipid metabolism, promoting good digestion, and reducing the risk of gastrointestinal diseases [2,6].
Belgium, the Netherlands, France, and Chile are among the main producers of inulin [7], while Chile, Belgium, and the Netherlands account for 99% of inulin exports [8]. Chile alone exports about 13,000 tons of inulin per year, amounting to approximately USD 50 million FOB [9,10]. In Chile, root chicory is cultivated between the Maule and La Araucanía regions because of the optimal agroclimatic conditions, such as a temperate climate, long frost-free period, abundant sunlight, availability of water for irrigation, and deep, non-stony, acidic soils with low salinity and without drainage limitations [10]. The maximum root chicory yield in these regions increased from 36.30 t fresh weight (FW) ha−1 in the 2006/2007 season to 58.7 t FW ha−1 in the 2023/2024 season, with the planted surface with root chicory increasing by 242.16% over the same period [11].
The gradual increase in root chicory production in Chile highlights the potential to expand this industry to other regions; however, evaluation of land aptitude is necessary to avoid poor site selection and unsuccessful establishment [12,13]. This requires a planned and sustainable utilization of natural resources based on their potential for agriculture [12,14]. Determining suitable sites for developing certain types of crops provides information on the opportunities and limitations of using a given surface area [14,15]. A fundamental part of this process is the selection of critical parameters to determine habitat suitability [16]. Boolean logic has been employed for this purpose, but limitations have been reported, such as threshold sensibility or loss of information [17,18]. The use of multiple criteria makes the analysis more complex due to the integration of sensitivity analysis [12,17].
GIS and multi-criteria decision making (MCDM) are used to solve complex problems in spatial planning [17] as they allow the determination and prioritization of alternative zones by considering different parameters [19]. AHP is a semiquantitative and flexible tool that divides a set of evaluation criteria into a hierarchical structure that involves a matrix-based pairwise comparison to define the contribution of conditioning factors [20,21]. The combination of MCDM and AHP has been widely applied in studies investigating agricultural product-based land suitability [17,19,21,22,23,24] because it enables the weighting of the classification criteria and obtaining of aptitude levels [17,19]. However, despite the potential of GIS and AHP, productivity estimation as a complement to suitability zoning remains underexplored [25,26,27].
This study aimed to determine suitable areas for root chicory production in Chile based on climatic and topographic variables using GIS and AHP to estimate the potential productivity of root chicory in those sites with the best suitability for its development. The findings of this study may be significant for planning sustainable chicory plantations and for expanding the inulin market.

2. Materials and Methods

2.1. Study Area

This study was conducted in continental Chile, which extends from 17° S (Arica y Parinacota region) to 56° S (Magallanes region) and 66° W to 75° W (Figure 1) [28]. The study area encompasses 16 administrative regions and has an area of approximately 75.29 million ha.

2.2. Determination of Climatic and Topographic Conditions for Chicory Growth

A bibliographic review was conducted to identify the locations where chicory naturally grows, as well as where it has been introduced and adapted. Climate data for each location were obtained from weather stations located at a maximum distance of 10′ latitude and longitude. Monthly average maximum (Tx) and minimum (Tn) temperatures (°C), relative average monthly humidity (%), and monthly precipitation (mm) were considered as variables. These data were used to derive the accumulated temperature (DD), potential evapotranspiration (ETo) (using Ivanov’s method), and water deficit (WD) as variables. More details regarding the determination of WD, DD, and ETo using the presence–species methodology can be found in the article by Román-Figueroa et al. [29].
Gridded data of Tx, DD, and WD during the productive cycle of chicory from September to April (sowing to harvesting) and Tn for September and October during crop establishment [30] were obtained from the Bioclimatic Atlas of Chile [31], updated until 2018, and considered as climatic factors in aptitude zoning. Elevation, slope, and aspect derived from a digital elevation model (DEM) were also used as topographic factors. Critical ranges for both climatic and topographic factors were determined based on the data concentration of scatterplots between climatic variables and the literature for topography. Aptitude ranges were categorized as “without restriction,” “mild restriction,” “moderate restriction,” and “unsuitable.”

Description of Evaluation Criteria

The climatic and topographic variables selected for root chicory suitability zoning were assumed to directly influence the crop, leading us to determine the crop’s establishment and development in the study area. The degree of influence of a variable depends on the characteristics of the species and its specific physiological requirements [32,33].
Temperature (T). Temperature is an important variable for crop development, affecting photosynthesis and the generation and dispersion of plant biomass [34]. Minimal temperature (Tn) is a critical factor during the establishment of root chicory in the field, as a Tn below 9 °C has been reported to retard germination [35]. Additionally, Devacht et al. [36] showed that decreasing the temperature from 16 to 4 °C reduced leaf dry mass (93.6%), root dry mass (90.3%), leaf area (92.2%), and specific leaf area (15.3%) of five chicory varieties after 28 days of growth. Conversely, exposing vegetative crops to above-optimal maximum temperature (Tx) can decrease root growth and sucrose accumulation [37]. In general, chicory varieties tolerate extreme temperatures [38]; however, in root chicory, temperatures above 35 °C may induce bolting and flowering, thereby reducing the inulin yield [5].
Accumulated temperature (DD). Heat accumulation in plants influences physiological time and can be used to monitor phenological stages, including harvest [39,40]. Normally, in taproot crops, biomass accumulation is linear during the first stage and then becomes exponential in the later stages, which is directly related to heat accumulation [41]. Additionally, in chicory, higher accumulation may produce bolting [42], which is why root chicory is produced as an annual crop, avoiding heat accumulation over 2300 DD [43].
Water deficit (WD). Chicory must be cultivated under careful irrigation to achieve the highest yield [38]. Although root chicory may have some level of resistance to water stress [44], a progressive decrease in water availability can drastically reduce the weight of the root, affecting inulin production [45]. Furthermore, areas with high WD require higher volumes of irrigation water to avoid increases in soil salinity or reductions in crop yield [46].
Slope. Slope is the most important topographic variable because it can influence soil fertility and crop productivity. When crops are grown on mildly steep and gentle slopes, nutrient loss, irrigation issues, and soil erosion can be reduced [19]. However, slope can also restrict the use of machinery and increase production, maintenance, and transportation costs [12,19].
Elevation. This is a less relevant variable for chicory, as chicory production has been reported at altitudes up to 3000 m [38].
Aspect. Aspect is relevant in environments with water stress, such as arid or semi-arid areas [47]; however, considering the distribution of chicory, it is not one of the most important variables [43].
In summary, for the climatic zoning of chicory roots, Tn is the most important variable as it directly influences crop establishment. This is followed by WD due to its direct contribution to root weight and the amount of inulin that can be produced; DD, which causes changes in physiological state and consequent inulin accumulation; and finally, Tx, as chicory can generally tolerate high temperatures. For topographic zoning, slope is the most important variable for soil fertility, followed by elevation, as limitations exist for growing chicory roots in very high areas. In contrast, aspect is largely only relevant under water stress conditions.

2.3. AHP and Weighted Overlay Method

The AHP method was applied separately to the climatic and topographic factors, ranking the aptitude ranges for root chicory land suitability on a scale of 1 to 4 (most to least suitable). A pairwise comparison following the Saaty method [20] was performed to obtain judgmental matrices and determine the weights of the factors in the range of 0–1 [19,24]. Additionally, the consistency ratio (CR) was evaluated, considering an acceptable value equal to or less than 0.10 [19].
Climatic and topographic maps were generated using the weighted overlay method (Equation (1)) in ArcGIS 10.4 software (Esri, Redland, CA, USA), using the weights of each group of factors. This was then applied again to assemble a final map of root chicory land suitability, considering the same importance in both components [24].
C S I = ∑ i = 1 n W i X i ,
where CSI is the chicory suitability index, W i is the relative importance of factor i, X i is the standardized scale for factor i, and n is the total number of factors [48].

2.4. Limiting Conditions for Chicory Suitability

The limiting conditions were evaluated by removing the possibility of using a territory based on land cover (LC). Based on the LC map of Chile [49], sites with croplands, forests, wetlands, water bodies, impervious surfaces, barren lands, snow and ice, and clouds, as well as protected zones defined in the National System of State Protected Wild Areas, were excluded from the chicory land suitability.

2.5. Productive Aptitude Zoning for Root Chicory

The potential productivity of root chicory was determined in zones previously identified as mild and without restrictions. The spatial distribution of the daily accumulation of dry aerial biomass in tons per hectare was estimated using Equation (2) [50] based on ecophysiological models proposed for different crops [51,52,53,54]. Due to inulin being extracted from the taproot of chicory, the dry weight (DW) was estimated as 64% root and 36% aerial biomass [55]. The growth period was set as 242 days (between September and April) to obtain the total biomass [30]. Root biomass categories were then established to visualize the areas with higher or lower productivity.
P C D = E × R U E × I × T F × W F ,
where PCD is the potential dry aerial biomass productivity in rainfed conditions (kg DW ha−1); E is the solar radiation (MJ m−2 d−1); RUE is the radiation use efficiency (kg ha−1 MJ−1 m2 d), which has a value of 2.3 in root chicory [43]; I is the canopy light interception, which varies with respect to the leaf area index, canopy light extinction coefficient, and maximum leaf area index and has a value of 0.2 in root chicory [56]; TF is the thermal control function with values between 0 and 1 depending on the proximity degree of temperature to the optimal value defined for the species (Equation (3)); and WF is the water function with values ranging from 0 to 1, depending on the crop water balance (Equation (4)).
T F i f   T x ( s a ) = T ( o p t ) ;   T F = 1   i f   T x ( s a ) < T x ( o p t ) ;   F T = 1 − T x o p t − T x s a T x s a s i   T x ( s a ) > T x ( o p t ) ;   F T = 1 + T x o p t − T x s a T x ( s a )
where Tx(opt) is the optimal maximum temperature, with values between 18 and 22 °C in root chicory, and Tx(sa) is the maximum temperature in the study area (°C).
W F i f   E T o s a ≤   E T o ( o p t )   ;   W F = 1 i f   E T o s a > E T o ( o p t ) ;   W F = 1 + E T o ( o p t ) − E T o ( s a ) E T o ( s a )
where ETo(opt) is the referential accumulated evapotranspiration for root chicory, with a value of 620 mm, and ETo(sa) is the accumulated evapotranspiration in the study area (mm).

3. Results

3.1. Climatic and Topographic Zoning

We identified 32 locations where chicory varieties have been recorded (Table A1) and obtained their climatic information. This information was used to determine the aptitude ranges for root chicory climatic factors (Table 1).
The CR was 0.01 and 0.07 for climatic and topographic factors, respectively, which was considered consistent, and Tn and slope were the most important variables in each factor (Table 1). Climatic zoning (Figure 2A) showed that an area of 72.44 million ha (96.22% of Chile) showed some type of suitability for chicory development, except for higher altitude areas located in the pre-mountain and the Andes Mountains between Tarapacá and Metropolitana regions, which were categorized as unsuitable. Land categorized as without restriction occupied 1.12% of the suitable areas between the Valparaíso and La Araucanía regions. Topographic zoning (Figure 2B) showed that 70.78 million ha had some type of topographic suitability for root chicory growth, equivalent to 94.01% of the country’s total landmass. Land categorized as without restriction occupied 35.00% of the suitable area and was distributed in all regions, especially in coastal and inner zones.

3.2. Land Suitability Zoning for Root Chicory Production

The suitability map for root chicory production, considering climatic, topographic, and limiting conditions, indicated that 18.87 million ha had some level of suitability, equivalent to 25.07% of the country’s total area. We observed that 8.42 million ha (11.19%) was classified as moderate restriction, 10.35 million ha (13.75%) as mild restriction, and only 101,200 ha (0.13%) as without restriction (Table 2).
Magallanes presented the largest suitable area for chicory production with 3.99 million ha, located mainly in the southeastern part of the region. It was followed by Coquimbo (2.39 million ha), Aysén (1.87 million ha), Los Lagos (1.28 million ha), La Araucanía (1.18 million ha), and Tarapacá (1.03 million ha); the remaining regions had suitable areas of less than 1 million ha (Figure 3 and Figure 4). The Valparaíso and Coquimbo regions had the highest suitability, with suitable areas occupying 59.71 and 58.83% of the region’s total land area, respectively (Table 2). The best conditions for root chicory cultivation (without restriction) were observed in six of the sixteen regions of Chile, with Biobío presenting 64,900 ha, equivalent to 64.13% of this classification (Table 2; Figure 3 and Figure 4).

3.3. Potential Productivity of Root Chicory

Areas with mild and without restriction were selected to estimate the potential productivity of root chicory, and five categories (0–5, 5–10, 10–15, 15–20, and 20–27 t DW ha−1) were established to analyze their spatial distribution. A maximum of 27 t DW ha−1 (Figure 5) was obtained. The Los Lagos, Los Ríos, and La Araucanía regions had the largest areas with potential productivity of 20–27 t DW ha−1 (1.09 million ha, 401,100 ha, and 264,900 ha, respectively, Table 3), mainly located in sites close to the coast (Figure 5). Conversely, the Magallanes and Aysén regions had the largest areas in the lower productivity range of 0–5 t DW ha−1, at 205,200 ha and 16,100 ha, respectively (Table 3).

4. Discussion

In this study, land suitability zoning for root chicory growth was conducted considering climatic, topographic, and LC-limiting factors. The Biobío region showed the highest surface (64,900 ha) without restriction. The Ñuble, La Araucanía, and Maule regions also had areas without restriction (Table 2). These results were consistent with the current distribution of root chicory cultivation, covering 4886 ha between the Maule and La Araucanía regions [11]. This indicates that multi-criteria evaluation in combination with the AHP method can effectively address crop planning problems based on the hierarchical importance of environmental factors, providing a quantitative analysis of suitability [34]. The Valparaíso and O’Higgins regions also showed high surface without restriction for root chicory, with 14,700 and 12,400 ha, respectively (Table 2), concentrated in the coastal sector of both regions (Figure 4). The best condition for root chicory in Chile was observed in land near the coastline (Figure 4 and Figure 5). This behavior can be attributed to the thermal regulation provided by the Pacific Ocean, with lower thermal oscillation in the coastline than in the inner land [57]. Temperature is one of the most important factors to root development in chicory, and lower and higher temperatures above the Tn or Tx have a negative impact on inulin accumulation [5,36].
The potential productivity of root chicory reached a maximum yield of 27 t DW ha−1. The Los Lagos region had the largest area within 20 and 27 t DW ha−1 (Table 3); a more detailed breakdown reveals that the Biobío region accounted for the largest area (28,800 ha) within the 25–27 t DW ha−1 range. This was followed by the La Araucanía, Valparaíso, Maule, and Ñuble regions, aligning with the current distribution of root chicory, except for the Valparaíso region. The maximum yield obtained from the productivity model was more than double the average value reported by the Beneo-Orafti company since its establishment in these regions (10.7 t DW ha−1), considering an equivalence of 20% FW [11,55]. This overestimation was expected because this productivity model did not include soil chemical properties or aspects, such as crop establishment, fertilization, plant health, and weed control, which are assumed to be optimal during crop development [50]. However, these factors may have a crucial role in field productivity [55] and require specific evaluation based on soil properties [58]. The discrepancy in productivity could also be due to the root chicory growth cycle considered in our study, which was 242 days between September and April [30] for the entire national territory; however, the actual physiological time of the crops and duration of growth can vary spatially and temporally according to the accumulated DD [39,59], increasing or decreasing the productivity depending on the geographical area. It should be noted that the comparison between modeled and actual values was general due to data availability; geolocated data is needed for proper validation of the results.
The high productivity area with 20–27 t DW ha−1 yield in the Los Lagos region (Table 3), mainly in the coastal sector (Figure 5), was notable, despite the absence of restriction zones (Table 2). In this region, the DD used in the climatic zoning was categorized as moderate restriction and unsuitable (Figure A1), which influenced the mild restriction obtained as the final land suitability (Figure 4). Nevertheless, productivity was more than double that of other regions in the north, driven by the higher water availability in this zone. The productivity model was applied under rainfed conditions, and it assumed that hydric demand varies depending on the crop’s location, with a greater water availability in the Los Lagos region; this may have increased productivity, to the detriment of the areas with better aptitude located to the north of this region. However, irrigation application could increase productivity in those zones. De Mastro et al. [60] obtained a yield of 9.3 t DW ha−1 for root chicory growing under optimal irrigation conditions, 33.6% more than that under water deficit conditions (non-irrigated) in a Mediterranean climate in a year without a favorable rainfall pattern.
Changes in precipitation, temperature, and wind patterns, in addition to an increase in the intensity and frequency of extreme weather events owing to climate change, can compromise water availability for irrigation [61]. Summer precipitation decreases of 60–100% have been projected for the period 2046–2065 between the Atacama and Biobío regions [62]. The most vulnerable areas in terms of agricultural production are the regions between Valparaíso and Biobío, with projected changes in crop yields and the displacement of suitable crop areas southward [61], where smaller decreases are projected or even increases of up to 20% in Aysén and Magallanes regions [62]. The results obtained in the Los Lagos region are consistent with this situation and suggest an opportunity to expand root chicory cultivation southward beyond its current distribution. Therefore, field studies are required to evaluate the feasibility of production in the areas suggested by zoning.
The findings of our study highlight the importance of analyzing both suitability and productivity zoning to prioritize cultivation areas for species of interest, including root chicory. Unlike other studies that have determined land suitability for a crop [17,19,21,23,24,29,63], we used an analysis that considered climatic and topographic factors with different levels of importance to identify suitable areas and employed physiological characteristics of the crop to estimate its productivity. We considered Tn and WD to be the most important variables (highest weight) for land suitability. Recently, Zhang et al. [34] determined the suitable land for forage chicory in China using the Maxent model. They evaluated 22 environmental criteria, finding that the most relevant variables in order of importance were the temperature of the coldest month, precipitation of the driest month, and annual mean temperature [34]. Tn has a real impact on root yield in chicory due to the bolting probability, although this is species-dependent [36,64].
The data obtained in this study—including climatic and topographic ranges derived from the presence–species analysis for chicory and the criterion weights assigned through the AHP for land suitability assessment—may serve as a reference framework for evaluating land aptitude for chicory cultivation in other countries, provided that local conditions are appropriately considered. On the other hand, for regional or local studies, the model should be adjusted to consider the spatial variation in root chicory growing days, as well as the inclusion of irrigation to estimate productivity. Soil type, crop variety, market demand, and crop management practices (such as fertilizer application, weed control, and the use of appropriate harvesting machinery) are also significant factors in chicory production [34] and could be used as variables in future studies in locations with potential for expansion. Despite these difficulties, suitability zoning and productivity estimation using our method are replicable on a large scale and provide a general idea of potential root chicory yields and spatial distribution.

5. Conclusions

The suitability map for root chicory production obtained from climatic and topographic zoning using GIS and AHP was consistent with the current distribution of the crop and indicated alternative sites for its expansion.
The Los Lagos region is proposed as an alternative for the expansion of root chicory south of the current distribution of the crop because it presents a higher area with a yield of 20–27 t DW ha−1. The Valparaíso and O’Higgins regions are also suitable for root chicory cultivation, and their productivity can increase with irrigation. However, because of climate change, irrigation water is expected to be limited within the Valparaíso and Biobío regions, and a displacement of crops to the south of the country could occur. Field research in the Valparaiso, O’Higgins, and Los Lagos regions to expand the root chicory production in Chile would be necessary, especially due to the projected demand for this crop.
The findings of our research highlight the importance of analyzing the aptitude and productivity estimations of crops in conjunction and can be useful for planning and expanding the root chicory market in a sustainable way, improving the overall efficiency and utilization value of the crop.

Author Contributions

D.C.: methodology, investigation, visualization, formal analysis, and writing—original draft; M.P.: resources and writing—review and editing; C.R.-F.: conceptualization, methodology, investigation, visualization, formal analysis, writing—review and editing, supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by Agroenergía Ingeniería Genética S.A.

Data Availability Statement

Further enquiries about the data supporting this study can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GIS Geographic information system
AHP Analytical hierarchy process
DW Dry weight
FW Fresh weight
MCDMMulti-criteria decision making
TxMaximum temperature
TnMinimum temperature
DDAccumulated temperature (degree days)
EToPotential evapotranspiration
WDWater deficit
DEMDigital elevation model
TTemperature
CRConsistency ratio
CSIChicory suitability index
WRelative importance of factor
XStandardized scale for factor
LCLand cover
PCDPotential dry aerial biomass
ESolar radiation
RUERadiation use efficiency
ICanopy light interception
TFThermal function
WFWater function
SSouth
SWSouthwest
EEast
WWest
NNorth
NENortheast
NWNorthwest
LULCLand use and land cover
SNASPENational System of Protected Wild Areas of the State

Appendix A

Table A1. Cities or towns where chicory was present were used to determine the climatic ranges for its development.
Table A1. Cities or towns where chicory was present were used to determine the climatic ranges for its development.
CountryCity/TownGeographic CoordinateElevation (masl)Reference
LatLong
AustraliaDownside35°04 S147°35 E219[65]
AustraliaFrogmore34°17 S148°45 E500[65]
AustraliaBorenore33°19 S149°05 E922[66]
BelgiumLeuven50°33 N04°40 E127[67]
BrazilCampinas22°49 S47°03 W660[68]
BrazilConselheiro Paulino22°17 S42°32 W857[69]
ChileLinares35°53 S71°36 W156[70]
EgyptCairo30°02 N31°15 E74[71]
SloveniaLjubljana46°03 N14°30 E361[72]
United StatesWindsor Locks41°50 N72°39 W55[73]
United StatesAtoka34°16 N95°59 W180[74]
United StatesAnsted38°00 N80°59 W395[75]
United StatesState College40°48 N77°51 W365[76]
FranceRennes48°06 N01°47 W36[77]
FranceParis48°48 N02°06 E96[78]
FranceLille50°29 N03°10 E52[79]
FranceBeauvais49°25 N02°04 E109[80]
WalesAberystwyth52°25 N04°04 W99[81]
HollandDe Bilt51°59 N05°39 E5[82]
HollandAmsterdam52°29 N05°28 E2[83]
IranArak34°06 N49°46 E1834[84]
IranShahreza32°02 N50°48 E1809[85]
IranTakestan36°03 N49°41 E1265[86]
ItalyBologna44°29 N11°19 E81[87]
ItalyTreviso45°42 N12°13 E15[88]
ItalyPadova45°24 N11°52 E14[89]
LithuaniaKlaipėda55°52 N21°14 E10[90]
New ZelandKairanga40°23 S175°36 E9[91]
PolandLubpinskilin51°14 N22°32 E239[92]
South AfricaPort Alfred33°32 S26°40 E22[93]
TurkeyKayseri38°53 N35°28 E1053[94]
UkraineKhmelnitskiy49°25 N26°59 E195[95]
Agronomy 15 01675 g0a1
Figure A1. Suitability level for climatic factors: (a) Tn, (b) Tx, (c) DD, and (d) WD. Topographic factors: (e) slope, (f) aspect, and (g) elevation.
Figure A1. Suitability level for climatic factors: (a) Tn, (b) Tx, (c) DD, and (d) WD. Topographic factors: (e) slope, (f) aspect, and (g) elevation.
Agronomy 15 01675 g0a1

References

  1. Al-Snafi, A. Medical importance of Cichorium intybus—A review. IOSR J. Pharm. 2016, 6, 41–56. [Google Scholar]
  2. Perović, J.; Šaponjac, V.T.; Kojić, J.; Krulj, J.; Moreno, D.A.; García-Viguera, C.; Bodroža-Solarov, M.; Ilić, N. Chicory (Cichorium intybus L.) as a food ingredient–Nutritional composition, bioactivity, safety, and health claims: A review. Food Chem. 2021, 336, 127676. [Google Scholar] [CrossRef] [PubMed]
  3. Innocenti, M.; Gallori, S.; Giaccherini, C.; Ieri, F.; Vincieri, F.F.; Mulinacci, N. Evaluation of the phenolic content in the aerial parts of different varieties of Cichorium intybus L. J. Agric. Food Chem. 2005, 53, 6497–6502. [Google Scholar] [CrossRef]
  4. Akram, H.; Zafar, H.; Abbasi, B.H. The chicory root (Cichorium intybus var. sativum) frontier: Pioneering biotechnological advancements. Phytochem. Rev. 2025. [Google Scholar] [CrossRef]
  5. Mathieu, A.S.; Périlleux, C.; Jacquemin, G.; Renard, M.E.; Lutts, S.; Quinet, M. Impact of vernalization and heat on flowering induction, development and fertility in root chicory (Cichorium intybus L. var. sativum). J. Plant Physiol. 2020, 254, 153272. [Google Scholar] [CrossRef]
  6. Shoaib, M.; Shehzad, A.; Omar, M.; Rakha, A.; Raza, H.; Sharif, H.R.; Shakeel, A.; Ansari, A.; Niazi, S. Inulin: Properties, health benefits and food applications. Carbohydr. Polym. 2016, 147, 444–454. [Google Scholar] [CrossRef]
  7. Rambaud, C.; Croy, M.; Choque, E. The great diversity of products from Cichorium intybus L. culture: How to valorize chicory byproducts: A review. Discover Plants 2025, 2, 107. [Google Scholar] [CrossRef]
  8. Hingsamer, M.; Kulmer, V.; de Roode, M.; Kernitzkyi, M. Environmental and socio-economic impacts of new plant breeding technologies: A case study of root chicory for inulin production. Front. Genome Ed. 2022, 4, 919392. [Google Scholar] [CrossRef] [PubMed]
  9. Velasco, V.; Soto, V.H.; Williams, P.; Campos, J.; Astudillo, R.; Rodríguez, H. Meat quality parameters of broiler chickens fed diets containing chicory (Cichorium intybus) vinasse. Chil. J. Agric. Anim. Sci. 2018, 34, 26–32. [Google Scholar] [CrossRef]
  10. Traub, A. Achicoria: Precursora de la Inulina. Oficina de Estudios y Políticas Agrarias (ODEPA). 2014. Available online: https://www.odepa.gob.cl/wp-content/uploads/2014/07/Inulina201407.pdf (accessed on 24 March 2025).
  11. Oficina de Estudios y Políticas Agrarias (ODEPA). Índice Cultivos Anuales Históricos. 2024. Available online: https://bibliotecadigital.odepa.gob.cl/handle/20.500.12650/73501 (accessed on 24 March 2025).
  12. Akıncı, H.; Özalp, A.Y.; Turgut, B. Agricultural land use suitability analysis using GIS and AHP technique. Comput. Electron. Agric. 2013, 97, 71–82. [Google Scholar] [CrossRef]
  13. Román-Figueroa, C.; Cea, M.; Paneque, M. Industrial oilseed crops in Chile: Current situation and future potential. Biofuel. Bioprod. Bior. 2023, 17, 273–290. [Google Scholar] [CrossRef]
  14. Everest, T.; Savaşkan, G.S.; Or, A.; Özcan, H. Suitable site selection by using full consistency method (FUCOM): A case study for maize cultivation in northwest Turkey. Environ. Dev. Sustain. 2024, 26, 1831–1850. [Google Scholar] [CrossRef]
  15. Mokarram, M.; Aminzadeh, F. GIS-based multicriteria land suitability evaluation using ordered weight averaging with fuzzy quantifier: A case study in Shavur Plain, Iran. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2010, 38, 508–512. [Google Scholar]
  16. Al-Shalabi, M.A.; Mansor, S.B.; Ahmed, N.B.; Shiriff, R. GIS based multicriteria approaches to housing site suitability assessment. In Proceedings of the XXIII FIG Congress, Shaping the Change, Munich, Germany, 8–13 October 2006; pp. 8–13. [Google Scholar]
  17. Aghaloo, K.; Sharifi, A. A GIS-based agroecological model for sustainable agricultural production in arid and semi-arid areas: The case of Kerman Province, Iran. Curr. Res. Environ. Sustain. 2023, 6, 100230. [Google Scholar] [CrossRef]
  18. Store, R.; Kangas, J. Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landsc. Urban Plan. 2001, 55, 79–93. [Google Scholar] [CrossRef]
  19. Tercan, E.; Dereli, M.A. Development of a land suitability model for citrus cultivation using GIS and multi-criteria assessment techniques in Antalya province of Turkey. Ecol. Indic. 2020, 117, 106549. [Google Scholar] [CrossRef]
  20. Saaty, T.L. The Analytic Hierarchy Process: Planning, Priority Setting. Resource Allocation; McGraw-Hill International: New York, NY, USA, 1980. [Google Scholar]
  21. Purnamasari, R.A.; Ahamed, T.; Noguchi, R. Land suitability assessment for cassava production in Indonesia using GIS, remote sensing and multi-criteria analysis. Asia-Pac. J. Reg. Sci. 2019, 3, 1–32. [Google Scholar] [CrossRef]
  22. Fathizad, H.; Pakbaz, N.; Sodaiezadeh, H.; Shojaei, S. Exploring canola planting area using AHP associated with GIS in Meymeh–Zarinabad of Iran. Spat. Inf. Res. 2017, 25, 371–379. [Google Scholar] [CrossRef]
  23. Ostovari, Y.; Honarbakhsh, A.; Sangoony, H.; Zolfaghari, F.; Maleki, K.; Ingram, B. GIS and multi-criteria decision-making analysis assessment of land suitability for rapeseed farming in calcareous soils of semi-arid regions. Ecol. Indic. 2019, 103, 479–487. [Google Scholar] [CrossRef]
  24. Tashayo, B.; Honarbakhsh, A.; Akbari, M.; Eftekhari, M. Land suitability assessment for maize farming using a GIS-AHP method for a semi-arid region, Iran. J. Saudi Soc. Agric. Sci. 2020, 19, 332–338. [Google Scholar] [CrossRef]
  25. Rashed, H.S. Classification and mapping of land productivity, capability and suitability for production crops in West El-Minia Governorate, Egypt. J. Soil Sci. Agric. Eng. 2020, 11, 709–717. [Google Scholar] [CrossRef]
  26. Nti, I.K.; Zaman, A.; Nyarko-Boateng, O.; Adekoya, A.F.; Keyeremeh, F. A predictive analytics model for crop suitability and productivity with tree-based ensemble learning. Decis. Anal. J. 2023, 8, 100311. [Google Scholar] [CrossRef]
  27. Sati, V.P. Crop productivity and suitability analysis. In Farming Systems and Sustainable Agriculture in the Himalaya; Sati, V.P., Ed.; Springer Nature: Berlin/Heidelberg, Germany, 2024; pp. 107–116. [Google Scholar]
  28. Instituto Geográfico Militar (IGM). Límites Político Administrativos de Chile. Available online: https://www.igm.cl/?page=descargas-gratuitas-igm&menu=1 (accessed on 15 January 2025).
  29. Román-Figueroa, C.; Cortez, D.; Paneque, M. A comparison of two methodological approaches for determining castor bean suitability in Chile. Agronomy 2020, 10, 1259. [Google Scholar] [CrossRef]
  30. Beneo. Manual Técnico de Achicoria Industrial Temporada 2018–2019. Available online: https://www.orafti.cl/sitio/download/manualtecnicocultivo2019-2020.pdf (accessed on 15 January 2025). (In Spanish).
  31. Uribe, J.; Cabrera, R.; de la Fuente, A.; Paneque, M. Atlas Bioclimático de Chile; Universidad de Chile: Santiago, Chile, 2012. [Google Scholar]
  32. Tandzi, N.L.; Mutengwa, S.C. Factors affecting yields of crops. In Agronomy—Climate Change and Food Security; Amanullah, Ed.; IntechOpen: London, UK, 2020; p. 16. [Google Scholar]
  33. Lisso, L.; Lindsay, J.B.; Berg, A. Evaluating the topographic factors for land suitability mapping of specialty crops in Southern Ontario. Agronomy 2024, 14, 319. [Google Scholar] [CrossRef]
  34. Zhang, H.; Yang, S.; Wei, X.; Wang, L.; Sun, X.; Hou, Z.; Zhong, Q.; Liu, W. Forecasting the favorable growth conditions and suitable regions for chicory (Cichorium intybus L.) on the Qinghai plateau under current climatic conditions. Ecol. Inform. 2023, 78, 102343. [Google Scholar] [CrossRef]
  35. Bala, R.; Dhillon, B.S.; Brar, A.S. Emergence and growth dynamics of chicory (Cichorium intybus L.) in response to sowing method and seed rate. Agric. Res. J. 2020, 57, 363–368. [Google Scholar] [CrossRef]
  36. Devacht, S.; Lootens, P.; Roldán-Ruiz, I.; Carlier, L.; Baert, J.; Van Waes, J.; Van Bockstaele, E. Influence of low temperatures on the growth and photosynthetic activity of industrial chicory, Cichorium intybus L. partim. Photosynthetica 2009, 47, 372–380. [Google Scholar] [CrossRef]
  37. Mathieu, A.S.; Lutts, S.; Vandoorne, B.; Descamps, C.; Périlleux, C.; Dielen, V.; Van Herck, J.C.; Quinet, M. High temperatures limit plant growth but hasten flowering in root chicory (Cichorium intybus) independently of vernalisation. J. Plant Physiol. 2014, 171, 109–118. [Google Scholar] [CrossRef]
  38. Bais, H.P.; Ravishankar, G.A. Cichorium intybus L.—Cultivation, processing, utility, value addition and biotechnology, with an emphasis on current status and future prospects. J. Sci. Food Agric. 2001, 81, 467–484. [Google Scholar] [CrossRef]
  39. Parthasarathi, T.; Velu, G.; Jeyakumar, P. Impact of crop heat units on growth and developmental physiology of future crop production: A review. Res. Rev. A J. Crop Sci. Technol. 2013, 2, 1–11. [Google Scholar]
  40. Verna, P.; Singh, J.; Sharma, S.; Thakur, H. Phenological growth stages and growing degree days of peach [Prunus persica (L.) Batsch] in sub-temperate climatic zone of North-Western Himalayan region using BBCH scale. Ann. Appl. Biol. 2023, 182, 284–294. [Google Scholar] [CrossRef]
  41. Kenter, C.; Hoffmann, C.M.; Märländer, B. Effects of weather variables on sugar beet yield development (Beta vulgaris L.). Eur. J. Agron. 2006, 24, 62–69. [Google Scholar] [CrossRef]
  42. Clapham, W.M.; Fedders, J.M.; Belesky, D.P.; Foster, J.G. Development dynamics of forage chicory. Agron. J. 2001, 93, 443–450. [Google Scholar] [CrossRef]
  43. Monti, A.; Amaducci, M.; Pritoni, G.; Venturi, G. Growth, fructan yield, and quality of chicory (Cichorium intybus L.) as related to photosynthetic capacity, harvest time, and water regime. J. Exp. Bot. 2005, 56, 1389–1395. [Google Scholar] [CrossRef] [PubMed]
  44. Cranston, L.M.; Kenyon, P.R.; Morris, S.T.; Lopez-Villalobos, N.; Kemp, P.D. Morphological and physiological responses of plantain (Plantago lanceolata) and chicory (Cichorium intybus) to water stress and defoliation frequency. J. Agron. Crop Sci. 2016, 202, 13–24. [Google Scholar] [CrossRef]
  45. Vandoorne, B.; Mathieu, A.S.; Van den Ende, W.; Vergauwen, R.; Périlleux, C.; Javaux, M.; Lutts, S. Water stress drastically reduces root growth and inulin yield in Cichorium intybus (var. sativum) independently of photosynthesis. J. Exp. Bot. 2012, 63, 4359–4373. [Google Scholar] [CrossRef] [PubMed]
  46. Fereres, E.; Soriano, M.A. Deficit irrigation for reducing agricultural water use. J. Exp. Bot. 2007, 58, 147–159. [Google Scholar] [CrossRef]
  47. González, J.; Bonet, A.; Echeverría, M. Efecto de la orientación de la ladera sobre algunas comunidades arbustivas del semiárido central de la depresión del Ebro. Mediterránea 1996, 2, 21–31. [Google Scholar] [CrossRef]
  48. Latinopoulos, D.; Kechagia, K. A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece. Renew. Energy 2015, 78, 550–560. [Google Scholar] [CrossRef]
  49. Zhao, Y.; Feng, D.; Yu, L.; Wang, X.; Chen, Y.; Bai, Y.; Hernández, H.J.; Galleguillos, M.; Estades, E.; Biging, G.S.; et al. Detailed dynamic land cover mapping of Chile: Accuracy improvement by integrating multi-temporal data. Remote Sens. Environ. 2016, 183, 170–185. [Google Scholar] [CrossRef]
  50. Oficina de Estudios y Políticas Agrarias (ODEPA). Mapas de Zonificación de Aptitud Productiva del Territorio Nacional de Especies Vegetales con Potencial de Producción de Biocombustibles; Oficina de Estudios y Políticas Agrarias (ODEPA): Santiago, Chile, 2010. [Google Scholar]
  51. Cazanga, R. Correction et validation du Modèle CERES-Maize. Une Approche de la Simulation de la Croissance et du Développement du maïs au Niveau de la Parcelle. Ph.D. Thesis, Université Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium, 1997. (In French). [Google Scholar]
  52. Cazanga, R.; Matus, F.; Schmal, R. Una aproximación deductiva para el manejo de los cultivos. La cebada cervecera un caso particular. Resúmenes IX Congreso Nacional de la Ciencia del Suelo. Boletín 2002, 18, 149–153. [Google Scholar]
  53. Monteith, J.L. The quest for balance in crop modeling. Agron. J. 1996, 88, 695–697. [Google Scholar] [CrossRef]
  54. Williams, J.; Dyke, P.T.; Jones, C.A. EPIC—A model for assessing the effects of erosion on soil productivity. In Developments in Environmental Modelling; Laurenroth, W.K., Ed.; Elsevier Sci. Publ. Co.: New York, NY, USA, 1983; pp. 553–572. [Google Scholar]
  55. Fischer, S.; Wilckens, R.; Vidal, I.; Astete, P.; Maier, J. Respuesta de la achicoria (Cichorium intybus L.) a la aplicación de magnesio. Chil. J. Agric. Anim. Sci. 2016, 32, 3–11. [Google Scholar] [CrossRef]
  56. Lee, J.; Hemmingson, N.; Minneé, E.; Clark, C. Management strategies for chicory (Cichorium intybus) and plantain (Plantago lanceolata): Impact on dry matter yield, nutritive characteristics and plant density. Crop Pasture Sci. 2015, 66, 168–183. [Google Scholar] [CrossRef]
  57. Sarricolea, P.; Herrera-Ossandon, M.; Mesenguer-Ruiz, O. Climatic regionalisation of continental Chile. J. Maps. 2017, 13, 66–73. [Google Scholar] [CrossRef]
  58. Gordon, D.H.; Hughes, J.C.; Manson, A.D. Soil fertility requirements of root chicory (Cichorium intybus var. sativum): A review. J. Plant Nutr. 2018, 41, 2644–2659. [Google Scholar] [CrossRef]
  59. Ritchie, J.T.; Nesmith, D.S. Temperature and crop development. In Modeling Plant and Soil Systems; Hanks, J., Ritchie, J.T., Eds.; American Society of Agronomy, Crop Science Society of America, and the Soil Science Society of America: Madison, WI, USA, 1991; Volume 31, pp. 5–29. [Google Scholar]
  60. De Mastro, G.; Manolio, G.; Marzi, V. Jerusalem artichoke (Helianthus tuberosus L.) and chicory (Cichorium intybus L.): Potential crops for inulin production in the Mediterranean area. Crop Pasture Sci. 2004, 65, 26–34. [Google Scholar] [CrossRef]
  61. Gouveia, C.M.; Justino, F.; Gurjao, C.; Zita, L.; Alonso, C. Revisiting climate-related agricultural losses across South America and their future perspectives. Atmosphere 2023, 14, 1303. [Google Scholar] [CrossRef]
  62. Araya-Osses, D.; Casanueva, A.; Román-Figueroa, C.; Uribe, J.M.; Paneque, M. Climate change projections of temperature and precipitation in Chile based on statistical downscaling. Clim. Dyn. 2020, 54, 4309–4330. [Google Scholar] [CrossRef]
  63. Román-Figueroa, C.; Padilla, R.; Uribe, J.M.; Paneque, M. Land suitability assessment for camelina (Camelina sativa L.) development in Chile. Sustainability 2017, 9, 154. [Google Scholar] [CrossRef]
  64. Dielen, V.; Notté, C.; Lutts, S.; Debavelaere, V.; Van Herck, J.-C.; Kinet, J.-M. Bolting control by low temperatures in root chicory (Cichorium intybus var. sativum). Field Crops Res. 2005, 94, 76–85. [Google Scholar] [CrossRef]
  65. Li, G.; Nie, Z.; Bonython, A.; Boschma, S. Evaluation of Chicory Cultivars and Accessions for Forage in South-Eastern Australia. Crop Pasture Sci. 2010, 61, 554–564. [Google Scholar] [CrossRef]
  66. Upjohn, B.; Parker, M. Chicory—A High Performance Forage. In Agnote DPI-243, 1st ed.; NSW Agriculture: Dubbo, NSW, Australia, 1999. [Google Scholar]
  67. Dauchot, N.; Mingeot, D.; Purnelle, B.; Muys, C.; Watillon, B.; Boutry, M.; Cutsem, P. Construction of 12 EST Libraries and Characterization of a 12,226 EST Dataset for Chicory (Cichorium intybus) Root, Leaves and Nodules in the Context of Carbohydrate Metabolism Investigation. BMC Plant Biol. 2009, 9, 9–14. [Google Scholar] [CrossRef]
  68. Toneli, J.; Park, K.; Negreiros, A. Spray-Drying Process Optimization of Chicory Root Inulin. Dry Technol. 2010, 28, 369–379. [Google Scholar] [CrossRef]
  69. Couri, S.; Gomes, F.; Nogueira, R.; Wilberg, V.; Cabral, M.; Silva, V.; Almeida, D. Determination of Inulin Content of Chicory Roots (Cichorium intybus L.) Cultivated Organically in Three Regions of Rio de Janeiro State; Embrapa Agroindústria De Alimentos: Rio de Janeiro, Brazil, 2005. [Google Scholar]
  70. Carrasco, G.; Carmona, C.; Sandoval, C.; Urrestarazu, M. Plant Density on Yield of Red Chicory Heads—Radiccio Rosso (Cichorium intybus L. var. foliosum Hegi) Grown in South-Central Chile. Acta Hortic. 1998, 467, 269–275. [Google Scholar] [CrossRef]
  71. Helaly, A.; Abdullah, H. Phytochemical Analysis and Yield Characterization of Eight Cichorium intybus L. Landraces. J. Hortic. Sci. Ornam. Plants 2017, 9, 39–51. [Google Scholar]
  72. Znidarcic, D.; Osvald, J.; Trdan, S. Plant Characteristics for Distinction of Red Chicory (Cichorium intybus L. var. silvestre Bisch.) Cultivars Grown in Central Slovenia. Acta Agric. Slov. 2004, 83, 251–260. [Google Scholar]
  73. Hill, D. Witloof Chicory (Belgian Endive) and Radicchio Trials 1987–1988. Bul. Tec. N°871. 1989. Available online: https://n9.cl/rpzml (accessed on 17 April 2025).
  74. Perkins, P.; Russo, V.; Collins, J. Postharvest Changes During Storage of Packaged Radicchio. J. Food Qual. 1992, 15, 111–118. [Google Scholar] [CrossRef]
  75. Belesky, D.; Turner, K.; Fedders, J.; Ruckle, J. Mineral Composition of Swards Containing Forage Chicory. Agron. J. 2001, 93, 468–475. [Google Scholar] [CrossRef]
  76. Skinner, H.; Dell, C. Reestablishing Chicory into Multi-Species Perennial Pastures. Forage Grazinglands 2010, 8, 1–6. [Google Scholar] [CrossRef]
  77. Delagarde, R.; Roca, A.; Peyraud, J. Caractéristiques des Prairies Multispécifiques avec ou Sans Chicorée: Densité Mesurée à l’Herbomètre et Composition Chimique. Fourrages 2014, 218, 177–180. [Google Scholar]
  78. Améziane, R.; Laurent, C.; Rufty, T.; Limami, A. Phosphate Availability in Combination with Nitrate Availability Affects Root Yield and Chicon Yield and Quality of Belgian Endive (Cichorium intybus). Plant Soil 1997, 191, 269–277. [Google Scholar] [CrossRef]
  79. Bahri, M.; Hance, P.; Grec, S.; Quillet, M.; Trotin, J.; Hendriks, T. A “Novel” Protocol for the Analysis of Hydroxycinnamic Acids in Leaf Tissue of Chicory (Cichorium intybus L., Asteraceae). Sci. World J. 2012, 2012, 142983. [Google Scholar] [CrossRef] [PubMed]
  80. Fouldrin, K.; Limami, A. The Influence of Nitrogen (15NO3) Supply to Chicory (Cichorium intybus L.) Plants During Forcing on the Uptake and Remobilization of N Reserves for Chicon Growth. J. Exp. Bot. 1993, 44, 1313–1319. [Google Scholar] [CrossRef]
  81. Marley, C.; Fychan, R.; Davies, J.; Scollan, N.; Richardson, I.; Theobald, V.; Genever, E.; Fober, A.; Sanderson, R. Effects of Chicory/Perennial Ryegrass Swards Compared with Perennial Ryegrass Swards on the Performance and Carcass Quality of Grazing Beef Steers. PLoS ONE 2014, 9, e86259. [Google Scholar] [CrossRef]
  82. Schober, B.; Vermeulen, T. Enzymatic Maceration of Witloof Chicory by the Soft Rot Bacteria Erwinia carotovora subsp. carotovora: The Effect of Nitrogen and Calcium Treatments of the Plant on Pectic Enzyme Production and Disease Development. Eur. J. Plant Pathol. 1999, 105, 341–349. [Google Scholar] [CrossRef]
  83. Peters, A.; Van Amerongen, A. Relationship between Levels of Sesquiterpene Lactones in Chicory and Sensory Evaluation. J. Am. Soc. Hortic. Sci. 1998, 132, 326–329. [Google Scholar] [CrossRef]
  84. Madani, H.; Dordas, C.; Madani, A.; Motasharei, M.-A.; Farri, S. Interactive Effects of Sowing Date and Planting Density on Dry Matter Accumulation and Partitioning of Chicory. Not. Bot. Horti Agrobot. Cluj-Napoca 2012, 40, 183–187. [Google Scholar] [CrossRef]
  85. Minaiyan, M.; Ghannadi, A.; Mahzouni, P.; Abed, A. Preventive Effect of Cichorium intybus L. Two Extracts on Cerulein-Induced Acute Pancreatitis in Mice. Int. J. Prev. Med. 2012, 3, 351–357. [Google Scholar]
  86. Asghari, M.; Farahani, H. Changes in Kaempferol Content of Chicory (Cichorium intybus L.) under Water Deficit Stresses and Planting Densities. J. Med. Plants Res. 2014, 8, 30–35. [Google Scholar]
  87. Baldini, M.; Danuso, F.; Monti, A.; Amanducci, M.; Stevanato, P.; Mastro, G. Chicory and Jerusalem Artichoke Productivity in Different Areas of Italy, in Relation to Water Availability and Time of Harvest. Ital. J. Agron. 2006, 1, 291–307. [Google Scholar] [CrossRef]
  88. Tardugno, R.; Pozzebon, M.; Beggio, M.; Del Turco, P. Polyphenolic Profile of Cichorium intybus L. Endemic Varieties from the Veneto Region of Italy. Food Chem. 2018, 266, 175–182. [Google Scholar] [CrossRef] [PubMed]
  89. Rossetto, M.; Lante, A.; Vanzani, P.; Spettoli, P.; Scarpa, M.; Rigo, A. Red Chicories as Potent Scavengers of Highly Reactive Radicals: A Study on Their Phenolic Composition and Peroxyl Radical Trapping Capacity and Efficiency. J. Agric. Food Chem. 2005, 53, 8169–8175. [Google Scholar] [CrossRef]
  90. Judžentienė, A.; Būdienė, J. Volatile Constituents from Aerial Parts and Roots of Cichorium intybus L. (Chicory) Grown in Lithuania. CHEMIJA 2008, 19, 25–28. [Google Scholar]
  91. Hume, D.; Lyons, T.; Hay, R. Evaluation of ‘Grasslands Puna’ Chicory (Cichorium intybus L.) in Various Grass Mixtures under Sheep Grazing. N. Z. J. Agric. Res. 1995, 38, 317–328. [Google Scholar] [CrossRef]
  92. Patkowska, E.; Konopiński, M. Harmfulness of Soil-Borne Fungi Towards Root Chicory (Cichorium intybus L. var. sativum Bisch.) Cultivated with the Use of Cover Crops. Hortorum Cultus 2013, 12, 3–18. [Google Scholar]
  93. Midgley, J.; Hill, M.; Villett, M. Baited Traps May Be an Alternative to Conventional Pesticides in Integrated Crop Management of Chicory (Compositae) in South Africa. J. Econ. Entomol. 2008, 101, 99–106. [Google Scholar] [CrossRef] [PubMed]
  94. Aksoy, A. Chicory (Cichorium intybus L.): A Possible Biomonitor of Metal Pollution. Pak. J. Bot. 2008, 40, 791–797. [Google Scholar]
  95. Tkach, O.; Ovcharuk, V. Influence of Chicory Plant Density on Size-Mass Root Parameters. Știința Agric. 2020, 1, 63–66. [Google Scholar]
Agronomy 15 01675 g001
Figure 1. Map of the study area: continental Chile.
Figure 1. Map of the study area: continental Chile.
Agronomy 15 01675 g001
Agronomy 15 01675 g002
Figure 2. (A) Climatic and (B) topographic zoning for root chicory suitability in Chile according to the presence–species method and analytical hierarchy process (AHP).
Figure 2. (A) Climatic and (B) topographic zoning for root chicory suitability in Chile according to the presence–species method and analytical hierarchy process (AHP).
Agronomy 15 01675 g002
Agronomy 15 01675 g003
Figure 3. Regional area with and without suitability/excluded for root chicory production in Chile.
Figure 3. Regional area with and without suitability/excluded for root chicory production in Chile.
Agronomy 15 01675 g003
Agronomy 15 01675 g004
Figure 4. Land suitability for root chicory production in Chile.
Figure 4. Land suitability for root chicory production in Chile.
Agronomy 15 01675 g004
Agronomy 15 01675 g005
Figure 5. Potential root chicory productivity in zones with mild and without land suitability restriction in t DW ha−1.
Figure 5. Potential root chicory productivity in zones with mild and without land suitability restriction in t DW ha−1.
Agronomy 15 01675 g005
Table 1. Climatic and topographic critical ranges and limitations for root chicory production in Chile.
Table 1. Climatic and topographic critical ranges and limitations for root chicory production in Chile.
ZoningFactor/LimitationAptitudeRange of AptitudeRankingWeight
ClimaticTn (°C)Restricted<440.38
Moderate restriction4–63
Mild restriction6–82
Without restriction>81
Tx (°C)Restricted<10; >3040.13
Moderate restriction10–13; 27–303
Mild restriction14–17; 23–262
Without restriction18–261
DD (°C)Restricted<700; >260040.14
Moderate restriction700–1000; 2300–26003
Mild restriction1000–1300; 2000–23002
Without restriction1300–20001
WD (mm)Restricted<−100040.35
Moderate restriction−1000–6503
Mild restriction−650−1002
Without restriction>−1001
TopographicSlope (%)Restricted>1540.67
Moderate restriction10–153
Mild restriction5–102
Without restriction0–51
AspectRestrictedS40.10
Moderate restrictionS–SW3
Mild restrictionE–W2
Without restrictionN–NE–NW1
Elevation (masl)Restricted>300040.23
Moderate restriction3000–20003
Mild restriction2000–10002
Without restriction0–10001
LULCUnsuitabilityCroplands, forests, wetlands, waterbodies, impervious surfaces, barren lands, snow and ice, clouds—SNASPE
SuitabilityGrasslands and shrublands
Abbreviations: S, south; SW, southwest; E, east; W, west; N, north (N); NE, northeast; NW, northwest; masl, meters above sea level; LULC, land use and land cover; SNASPE, National System of Protected Wild Areas of the State (Sistema Nacional de Áreas Silvestres Protegidas del Estado, en español).
Table 2. Potential regional area for root chicory production according to land suitability levels.
Table 2. Potential regional area for root chicory production according to land suitability levels.
Region of ChileExcludedWithout RestrictionMild RestrictionModerate RestrictionUnsuitable
Arica947,000053,300598,70086,700
Tarapacá3,069,5000135,400894,000128,800
Antofagasta11,949,5000308,900283,10067,000
Atacama6,332,4000534,900458,200239,700
Coquimbo1,398,30001,065,2001,321,900272,000
Valparaíso562,10014,700377,300562,00081,600
Metropolitana816,4000201,200450,50071,600
O’Higgins975,80012,400340,000277,10030,200
Maule2,017,9001600599,100364,70049,600
Ñuble799,0005000383,500114,4006800
Biobío1,690,70064,900445,800193,2008600
La Araucanía2,004,3002600912,200260,6004900
Los Ríos1,336,3000434,80062,3001600
Los Lagos3,564,10001,109,200167,5004400
Aysén8,812,0000466,0001,405,70021,500
Magallanes9,063,20002,982,4001,007,900700
Table 3. Regional area with different ranges of potential root chicory productivity.
Table 3. Regional area with different ranges of potential root chicory productivity.
Region of ChileRoot Chicory Biomass Range (t DW ha−1)
0–55–1010–1515–2020–27
Area (ha)
Arica0032,20020,500600
Tarapacá00118,60015,8001000
Antofagasta00234,10070,6004200
Atacama00188,600292,40053,900
Coquimbo00193,500644,300227,400
Valparaíso0046,800185,100160,100
Metropolitana00125,30070,5005400
B. O’Higgins00112,100180,80059,500
Maule00311,300227,30062,100
Ñuble200100205,600160,00022,600
Biobío10010042,300296,900171,300
La Araucanía00900649,000264,900
Los Ríos0070033,000401,100
Los Lagos700900340011,2001,093,000
Aysén16,10016,10030,900394,0008900
Magallanes205,200470,8001,485,100821,3000
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cortez, D.; Paneque, M.; Román-Figueroa, C. Potential Expansion of Root Chicory Cultivation Areas in Chile. Agronomy 2025, 15, 1675. https://doi.org/10.3390/agronomy15071675

AMA Style

Cortez D, Paneque M, Román-Figueroa C. Potential Expansion of Root Chicory Cultivation Areas in Chile. Agronomy. 2025; 15(7):1675. https://doi.org/10.3390/agronomy15071675

Chicago/Turabian Style

Cortez, Donna, Manuel Paneque, and Celián Román-Figueroa. 2025. "Potential Expansion of Root Chicory Cultivation Areas in Chile" Agronomy 15, no. 7: 1675. https://doi.org/10.3390/agronomy15071675

APA Style

Cortez, D., Paneque, M., & Román-Figueroa, C. (2025). Potential Expansion of Root Chicory Cultivation Areas in Chile. Agronomy, 15(7), 1675. https://doi.org/10.3390/agronomy15071675

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop