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Volume 38, Issue 1 (2023)
GeoRes 2023, 38(1): 99-106 |
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Received: 2022/12/20 | Accepted: 2023/03/12 | Published: 2023/04/4
Received: 2022/12/20 | Accepted: 2023/03/12 | Published: 2023/04/4
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Farajnia A, Chakherlou S. Agro Climatic Zoning to Quinoa Culture in Harzandat Plain of Marand, Iran, Using Analytic Hierarchy Process. GeoRes 2023; 38 (1) :99-106
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A. Farajnia *1, S. Chakherlou1
1- East Azerbaijan Agriculture and Natural Resources Research and Education Center, Tabriz, Iran
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Introduction
The pressure caused by population growth, particularly in developing countries, has intensified competition for the allocation of agricultural lands to other land uses [Everest et al., 2020]. One of the consequences of population growth, urban expansion, and industrialization is climate change resulting from fossil fuel consumption. Since the pre-industrial era, atmospheric carbon dioxide concentrations have increased by 40%, and greenhouse gas emissions are expected to continue. Global temperature has already risen by 0.6°C in the present century and is projected to increase up to 5.8°C by the year 2100. This phenomenon alters climatic parameters such as humidity, evapotranspiration, and the duration and intensity of precipitation, thereby shifting the growing season and influencing agricultural productivity over time [IPCC, 2013]. Climate change will significantly affect climatic parameters, particularly temperature and precipitation, in the near future. Rising temperatures and declining rainfall will reduce the suitability of lands for crops traditionally cultivated in specific regions, forcing farmers either to adopt new crops compatible with the changing conditions or to abandon their lands and migrate to urban areas.
To mitigate the adverse effects of climate change on the agricultural sector, which could endanger food security, fundamental changes in conventional farming practices are required to ensure adaptability to the new climatic conditions [Bagheri, 2017]. Strategic planning for a gradual shift in regional cropping patterns, including the reduction or elimination of high-water-demand crops and their replacement with drought-tolerant, low-water-demand species, is a crucial step toward climate adaptation in agriculture [Lashkari & Khosravi, 2009]. Global warming is altering prevailing climatic zones (e.g., arid, semi-humid, cold, and dry), leading to an increase in the extent of arid regions and a reduction in semi-humid and humid areas [Bagheri, 2017]. Achieving sustainable agriculture and food security depends on efficient land-use management, scientifically sound yield enhancement per unit area, and the spatial assessment of land suitability through robust analytical and optimization approaches under effective management [Seyedmohamadi et al., 2022].
Iran’s climate is gradually shifting toward warmer and drier conditions, accompanied by increasing soil salinity. Considering quinoa’s high tolerance to drought, salinity, and frost, this crop could serve as an optimal alternative for improving cropping patterns and counteracting the adverse effects of climate change.
Quinoa (Chenopodium quinoa Willd.), a member of the Amaranthaceae family, is recognized as a highly nutritious grain crop [Vidueiros et al., 2015]. Its nutritional value lies in its complete amino acid profile and high levels of calcium, phosphorus, and iron. The protein quality and quantity of quinoa surpass those of wheat and barley, containing 16 essential and non-essential amino acids with a more balanced amino acid composition than cereals. One notable characteristic of quinoa seeds is their high lysine content (1.5–6.4%), approximately 2.5 times that of wheat [Kalate Arabi & Kamali, 2021]. Quinoa is adapted to cold and dry climates and can tolerate temperatures ranging from −1°C to 35°C and pre-flowering frost. It is drought-resistant, and excessive irrigation may cause stem lodging. Although the crop’s water requirement varies across regions and climatic conditions, reports indicate that quinoa can produce acceptable yields with annual rainfall of 100–200 mm [Hosseini et al., 2021]. It can grow in soils with a wide pH range (6–8.5) and prefers sandy loam to loam textures. Being salt-tolerant, quinoa can be cultivated in marginal or degraded lands. Moreover, it is gluten-free and has medicinal properties [Jamali & Ansari, 2015]. Quinoa can withstand prolonged drought and severe frost, growing at elevations up to 3922 m above sea level [Jacobsen, 2003].
Kalate Arabi and Kamali [2021] have investigated cultivation conditions and supplemental irrigation requirements for quinoa and reported that although quinoa is drought-tolerant, yield reduction under severe drought can be compensated through supplemental irrigation. While Razzaghi [2011] has observed up to a 50% yield reduction in quinoa at salinity levels of 25 dS/m, contrary to wheat and barley, Salehi et al. [2018] report a 20% yield reduction under the same salinity. Quinoa demonstrates excellent adaptability to high salinity, extremely low, and high temperatures; hence, its cultivation is recommended for saline soils and both hot and cold regions of Iran [Mamedi et al., 2016]. The crop can tolerate temperatures as low as −8°C, drought, and salinity stress [Ruffino et al., 2010]. It regulates leaf water potential by accumulating salt ions in tissues, enabling maintenance of turgor pressure and reduction of transpiration under saline conditions [Gomez-Pando et al., 2010].
The FAO agroecological zoning model identifies potential land suitability and allocates land uses based on the inherent capacity of the territory, establishing a sustainable balance between environmental potential, human needs, and land use [Farajnia et al., 2021]. Numerous factors affect land suitability for specific crops, though their relative importance varies; therefore, determining the weight of each criterion is essential. Multi-Criteria Decision Analysis (MCDA) techniques are employed for this purpose, involving the evaluation and ranking of criteria according to their significance in decision-making [Saaty, 1987]. Among these techniques, the Analytical Hierarchy Process (AHP) is a powerful decision-making tool that performs pairwise comparisons among criteria to derive relative weights. The pairwise comparison method includes three main steps: constructing a hierarchical structure, calculating weights, and checking consistency [Sys et al., 1991].
Dengiz and Usul [2018] have used the FAO agroecological method and AHP model to identify agricultural suitability zones in Bursa Province, Turkey, reporting that 15% of lands were classified as highly or moderately suitable, while 85% were marginally suitable or unsuitable. Girmay et al. [2018] have assessed land suitability in the Gatenoi Basin, Ethiopia, for wheat, barley, and bean cultivation, finding that only 7% of the land was highly suitable for wheat and barley and moderately suitable for beans. In Bijapur, India, sugarcane suitability mapping using GIS and AHP based on ten factors (rainfall, texture, drainage, soil depth, slope, proximity to roads and sugar factories, erosion, flood risk, and acidity) revealed that 61% of the area was highly suitable, 24% moderately suitable, 7% marginally suitable, and 8% unsuitable [Kamali & Owji, 2016].
Abdel Rahman et al. [2016] have applied the FAO method to assess land suitability in Chamarajanagar, India, considering soil texture, depth, erosion, slope, flooding, and stoniness. They used GIS for mapping. Similarly, Asimeh et al. [2019] have evaluated the suitability of Fars Province for quinoa cultivation, reporting that approximately 102,000 km² were highly suitable, 188,000 km² suitable, 1,690 km² moderately suitable, and only 507 km² marginally suitable. Dehani [2016] investigates quinoa cultivation potential in Sistan and Baluchestan Province, assigning weights to criteria using AHP and integrating results via Fuzzy-AHP overlay analysis.
Halabian and Esmaili [2017] have performed agroclimatic zoning for rapeseed cultivation using fuzzy logic and AHP, dividing the study area into four suitability zones: very good, good, moderate, and poor. Farajnia and Moravej [2018] have assessed land suitability in East Azerbaijan Province for saffron cultivation, concluding that 42% of the area was highly or moderately suitable, 14% marginally suitable, and 42% unsuitable. The main limiting factors were elevation, slope, and temperature. Saadatfar et al. [2017] have identified potential habitats for the medicinal plant Ferula assa-foetida in Chatrood, Kerman, using GIS and AHP. Naseri et al. [2016] have analyzed medicinal plant cultivation potential in the Arasbaran region using GIS-based AHP and weighted linear combination (WLC), identifying suitable cultivation zones. Pakzad and Eslami [2017] have located suitable lands for Prosopis cineraria expansion in Kerman Province using GIS and AHP, while Yazdchi et al. [2018] found that Marand County possesses suitable climatic conditions for saffron production.
The objective of this study is to evaluate the potential for quinoa cultivation in the Harzandat Plain of Marand, considering the crop’s agroecological requirements and employing the Analytical Hierarchy Process (AHP) method.
Methodology
This experimental field study was conducted during the 2021–2022 cropping season in the Harzandat Plain of Marand, located in East Azerbaijan Province, Iran. The plain covers more than 18,000 hectares and lies on the southern slopes of the Arduj Mountains, between Jolfa and Marand counties. It is situated approximately 30 kilometers from Marand city and about 100 kilometers from Tabriz.
The soil characteristics of the study area were obtained from the regional soil survey report. Quinoa was planted in mid-April, germinated from early May to mid-June, flowered during late June, reached maturity in mid-September, and was harvested by the end of September.
Spatial distribution maps and spatial pattern analyses were developed by interpolating point-based soil data across the study area. In this process, the values at unsampled locations were estimated based on data from known sampling points. The spatial data were analyzed in ArcGIS software, and separate land suitability layers were generated for each criterion, including slope, soil texture, gravel content, salinity, and pH.
To determine the relative importance of each criterion, the Analytical Hierarchy Process (AHP) method was used. Expert opinions were collected through questionnaires distributed among 15 specialists with relevant research and professional backgrounds. The resulting weights were analyzed using Expert Choice software, which also provided the consistency ratio of expert judgments. Since the calculated consistency ratio was below the acceptable threshold, the results were deemed reliable.
After determining the final weights, they were assigned to the corresponding layers in the GIS environment. A weighted overlay analysis was then performed to combine the thematic layers according to their importance values. The resulting suitability map classified the study area into five categories based on the degree of land suitability for quinoa cultivation: highly suitable, moderately suitable, marginally suitable, currently unsuitable but improvable, and unsuitable
Findings
The soil texture across the Harzandat Plain varied considerably. In the central, southern, and southeastern parts of the plain, the soil texture was predominantly light to medium, while in the western areas it ranged from medium to heavy. The central section of the plain contained very heavy soils with more than 50% clay content.
The soil pH ranged between 7.9 and 8.2 in the northwestern and, to some extent, the eastern parts of the plain. In the central areas, which covered the largest portion of the region, the pH values varied from 8.2 to 8.5, whereas in the southern and southwestern zones, they ranged between 8.5 and 8.7.
Soil salinity was generally low throughout most of the study area and posed no significant limitation for quinoa cultivation, with electrical conductivity values below 5 dS/m. However, in some central parts, salinity levels reached up to 15 dS/m. This increase was attributed to the concave topography of the region, which led to the accumulation of salts in the lower-lying areas.
The proportion of surface gravel was below 15% in the northern, western, and southern parts of the region, while some sections in the west and east contained more than 15%, reaching up to 40%. In the eastern, northern, and central zones, the gravel content increased substantially, up to 55%, which could cause major restrictions for cultivation activities and machinery movement.
Topographically, the central parts of the plain were almost flat or had a very gentle slope. Moving toward the northern, eastern, and western areas, the land slope gradually increased.
Highly suitable lands for quinoa cultivation were primarily located in the western parts of the plain, particularly around the villages of Galin Qayah and Zal, as well as in smaller patches south of Orian Tappeh village in the east. These highly suitable areas covered approximately 3,850 hectares, accounting for about 21% of the total study area. Moderately suitable lands, with minor limitations for quinoa cultivation, were scattered throughout various parts of the plain and covered around 4,600 hectares, representing roughly 25% of the total area.
Land classified as marginally suitable covered about 5,580 hectares (around 30%), while the “currently unsuitable but improvable” category included approximately 1,540 hectares (about 8%). Permanently unsuitable lands, where cultivation was not feasible due to severe limitations, covered about 2,760 hectares, equivalent to roughly 15% of the total area
Discussion
According to the soil survey report of the Harzandat Plain, the most significant limiting factors for cultivating agricultural crops, including quinoa, are land slope, electrical conductivity (EC), pH, soil texture, and the proportion of surface gravel. The final land suitability analysis indicated that approximately 3,850 hectares of the area were completely suitable for quinoa cultivation, showing no major limitations and offering the potential for maximum yield. In other words, based on the growth requirements of quinoa, the selected evaluation criteria in this study were found to be optimal within these lands, and any existing restrictions were considered minimal.
An additional 4,600 hectares were identified as having minor limitations due to soil-related factors and land slope. In some cases, these constraints were mainly associated with slope, EC, and surface gravel, which could be mitigated with reasonable management interventions and moderate investment. However, limitations arising from pH and soil texture are less amenable to direct correction and would require careful agronomic management to minimize their effects. Despite these challenges, quinoa cultivation in these areas remains both profitable and economically justifiable.
Approximately 5,580 hectares were classified as marginally suitable, or “critical suitability” lands, where cultivation is possible but with low profitability. Considering the extent and number of limiting factors in these areas, quinoa cultivation is not recommended due to the limited economic returns. The remaining lands were categorized as unsuitable because of multiple and severe limitations. These findings are consistent with previous studies that have emphasized allocating highly suitable and moderately suitable lands to quinoa production while recommending further evaluation for marginally suitable areas (Seyed Jalali et al., 2020; Farajnia et al., 2021).
Since 2006, repeated drought events have occurred across different parts of the province, leading to reductions in crop yields of up to 35%. The recession of Lake Urmia is one of the most notable consequences of recent droughts, which has had a detrimental effect on both the quantity and quality of groundwater resources (Jahanbakhsh, 2018). To mitigate the impacts of climate change, it is recommended to incorporate quinoa into the regional crop rotation system, given its low water requirement and high tolerance to heat stress. Further systematic research is necessary to identify quinoa varieties suitable for both irrigated and rain-fed conditions and to determine their specific water and nutrient requirements. With proper management and the introduction of suitable genotypes, quinoa cultivation could play an important role in enhancing food security, increasing farmers’ income, and reducing water consumption, particularly in dryland farming systems
Conclusion
Quinoa can be cultivated in more than 40% of the lands across the Harzandat Plain. These suitable areas are scattered throughout different parts of the plain, with the highest concentration found in the western region. In contrast, the central part of the plain contains the largest portion of unsuitable lands, mainly due to high soil salinity and heavy texture. However, given the presence of a seasonal river flowing through the central plain, these limitations could potentially be alleviated or mitigated through appropriate leaching and drainage practices.
Acknowledgments: None reported by the authors.
Ethical Permission: None declared by the authors.
Conflict of Interest: The authors declare no conflicts of interest.
Authors’ Contributions: Farajnia A (First Author), Principal Researcher/Introduction Writer/Methodologist/ Statistical Analyst (50%); Chakherlou S (Second Author), Assistant Researcher/Discussion Writer/Statistical Analyst (50%).
Funding: No financial support was reported by the authors.
The pressure caused by population growth, particularly in developing countries, has intensified competition for the allocation of agricultural lands to other land uses [Everest et al., 2020]. One of the consequences of population growth, urban expansion, and industrialization is climate change resulting from fossil fuel consumption. Since the pre-industrial era, atmospheric carbon dioxide concentrations have increased by 40%, and greenhouse gas emissions are expected to continue. Global temperature has already risen by 0.6°C in the present century and is projected to increase up to 5.8°C by the year 2100. This phenomenon alters climatic parameters such as humidity, evapotranspiration, and the duration and intensity of precipitation, thereby shifting the growing season and influencing agricultural productivity over time [IPCC, 2013]. Climate change will significantly affect climatic parameters, particularly temperature and precipitation, in the near future. Rising temperatures and declining rainfall will reduce the suitability of lands for crops traditionally cultivated in specific regions, forcing farmers either to adopt new crops compatible with the changing conditions or to abandon their lands and migrate to urban areas.
To mitigate the adverse effects of climate change on the agricultural sector, which could endanger food security, fundamental changes in conventional farming practices are required to ensure adaptability to the new climatic conditions [Bagheri, 2017]. Strategic planning for a gradual shift in regional cropping patterns, including the reduction or elimination of high-water-demand crops and their replacement with drought-tolerant, low-water-demand species, is a crucial step toward climate adaptation in agriculture [Lashkari & Khosravi, 2009]. Global warming is altering prevailing climatic zones (e.g., arid, semi-humid, cold, and dry), leading to an increase in the extent of arid regions and a reduction in semi-humid and humid areas [Bagheri, 2017]. Achieving sustainable agriculture and food security depends on efficient land-use management, scientifically sound yield enhancement per unit area, and the spatial assessment of land suitability through robust analytical and optimization approaches under effective management [Seyedmohamadi et al., 2022].
Iran’s climate is gradually shifting toward warmer and drier conditions, accompanied by increasing soil salinity. Considering quinoa’s high tolerance to drought, salinity, and frost, this crop could serve as an optimal alternative for improving cropping patterns and counteracting the adverse effects of climate change.
Quinoa (Chenopodium quinoa Willd.), a member of the Amaranthaceae family, is recognized as a highly nutritious grain crop [Vidueiros et al., 2015]. Its nutritional value lies in its complete amino acid profile and high levels of calcium, phosphorus, and iron. The protein quality and quantity of quinoa surpass those of wheat and barley, containing 16 essential and non-essential amino acids with a more balanced amino acid composition than cereals. One notable characteristic of quinoa seeds is their high lysine content (1.5–6.4%), approximately 2.5 times that of wheat [Kalate Arabi & Kamali, 2021]. Quinoa is adapted to cold and dry climates and can tolerate temperatures ranging from −1°C to 35°C and pre-flowering frost. It is drought-resistant, and excessive irrigation may cause stem lodging. Although the crop’s water requirement varies across regions and climatic conditions, reports indicate that quinoa can produce acceptable yields with annual rainfall of 100–200 mm [Hosseini et al., 2021]. It can grow in soils with a wide pH range (6–8.5) and prefers sandy loam to loam textures. Being salt-tolerant, quinoa can be cultivated in marginal or degraded lands. Moreover, it is gluten-free and has medicinal properties [Jamali & Ansari, 2015]. Quinoa can withstand prolonged drought and severe frost, growing at elevations up to 3922 m above sea level [Jacobsen, 2003].
Kalate Arabi and Kamali [2021] have investigated cultivation conditions and supplemental irrigation requirements for quinoa and reported that although quinoa is drought-tolerant, yield reduction under severe drought can be compensated through supplemental irrigation. While Razzaghi [2011] has observed up to a 50% yield reduction in quinoa at salinity levels of 25 dS/m, contrary to wheat and barley, Salehi et al. [2018] report a 20% yield reduction under the same salinity. Quinoa demonstrates excellent adaptability to high salinity, extremely low, and high temperatures; hence, its cultivation is recommended for saline soils and both hot and cold regions of Iran [Mamedi et al., 2016]. The crop can tolerate temperatures as low as −8°C, drought, and salinity stress [Ruffino et al., 2010]. It regulates leaf water potential by accumulating salt ions in tissues, enabling maintenance of turgor pressure and reduction of transpiration under saline conditions [Gomez-Pando et al., 2010].
The FAO agroecological zoning model identifies potential land suitability and allocates land uses based on the inherent capacity of the territory, establishing a sustainable balance between environmental potential, human needs, and land use [Farajnia et al., 2021]. Numerous factors affect land suitability for specific crops, though their relative importance varies; therefore, determining the weight of each criterion is essential. Multi-Criteria Decision Analysis (MCDA) techniques are employed for this purpose, involving the evaluation and ranking of criteria according to their significance in decision-making [Saaty, 1987]. Among these techniques, the Analytical Hierarchy Process (AHP) is a powerful decision-making tool that performs pairwise comparisons among criteria to derive relative weights. The pairwise comparison method includes three main steps: constructing a hierarchical structure, calculating weights, and checking consistency [Sys et al., 1991].
Dengiz and Usul [2018] have used the FAO agroecological method and AHP model to identify agricultural suitability zones in Bursa Province, Turkey, reporting that 15% of lands were classified as highly or moderately suitable, while 85% were marginally suitable or unsuitable. Girmay et al. [2018] have assessed land suitability in the Gatenoi Basin, Ethiopia, for wheat, barley, and bean cultivation, finding that only 7% of the land was highly suitable for wheat and barley and moderately suitable for beans. In Bijapur, India, sugarcane suitability mapping using GIS and AHP based on ten factors (rainfall, texture, drainage, soil depth, slope, proximity to roads and sugar factories, erosion, flood risk, and acidity) revealed that 61% of the area was highly suitable, 24% moderately suitable, 7% marginally suitable, and 8% unsuitable [Kamali & Owji, 2016].
Abdel Rahman et al. [2016] have applied the FAO method to assess land suitability in Chamarajanagar, India, considering soil texture, depth, erosion, slope, flooding, and stoniness. They used GIS for mapping. Similarly, Asimeh et al. [2019] have evaluated the suitability of Fars Province for quinoa cultivation, reporting that approximately 102,000 km² were highly suitable, 188,000 km² suitable, 1,690 km² moderately suitable, and only 507 km² marginally suitable. Dehani [2016] investigates quinoa cultivation potential in Sistan and Baluchestan Province, assigning weights to criteria using AHP and integrating results via Fuzzy-AHP overlay analysis.
Halabian and Esmaili [2017] have performed agroclimatic zoning for rapeseed cultivation using fuzzy logic and AHP, dividing the study area into four suitability zones: very good, good, moderate, and poor. Farajnia and Moravej [2018] have assessed land suitability in East Azerbaijan Province for saffron cultivation, concluding that 42% of the area was highly or moderately suitable, 14% marginally suitable, and 42% unsuitable. The main limiting factors were elevation, slope, and temperature. Saadatfar et al. [2017] have identified potential habitats for the medicinal plant Ferula assa-foetida in Chatrood, Kerman, using GIS and AHP. Naseri et al. [2016] have analyzed medicinal plant cultivation potential in the Arasbaran region using GIS-based AHP and weighted linear combination (WLC), identifying suitable cultivation zones. Pakzad and Eslami [2017] have located suitable lands for Prosopis cineraria expansion in Kerman Province using GIS and AHP, while Yazdchi et al. [2018] found that Marand County possesses suitable climatic conditions for saffron production.
The objective of this study is to evaluate the potential for quinoa cultivation in the Harzandat Plain of Marand, considering the crop’s agroecological requirements and employing the Analytical Hierarchy Process (AHP) method.
Methodology
This experimental field study was conducted during the 2021–2022 cropping season in the Harzandat Plain of Marand, located in East Azerbaijan Province, Iran. The plain covers more than 18,000 hectares and lies on the southern slopes of the Arduj Mountains, between Jolfa and Marand counties. It is situated approximately 30 kilometers from Marand city and about 100 kilometers from Tabriz.
The soil characteristics of the study area were obtained from the regional soil survey report. Quinoa was planted in mid-April, germinated from early May to mid-June, flowered during late June, reached maturity in mid-September, and was harvested by the end of September.
Spatial distribution maps and spatial pattern analyses were developed by interpolating point-based soil data across the study area. In this process, the values at unsampled locations were estimated based on data from known sampling points. The spatial data were analyzed in ArcGIS software, and separate land suitability layers were generated for each criterion, including slope, soil texture, gravel content, salinity, and pH.
To determine the relative importance of each criterion, the Analytical Hierarchy Process (AHP) method was used. Expert opinions were collected through questionnaires distributed among 15 specialists with relevant research and professional backgrounds. The resulting weights were analyzed using Expert Choice software, which also provided the consistency ratio of expert judgments. Since the calculated consistency ratio was below the acceptable threshold, the results were deemed reliable.
After determining the final weights, they were assigned to the corresponding layers in the GIS environment. A weighted overlay analysis was then performed to combine the thematic layers according to their importance values. The resulting suitability map classified the study area into five categories based on the degree of land suitability for quinoa cultivation: highly suitable, moderately suitable, marginally suitable, currently unsuitable but improvable, and unsuitable
Findings
The soil texture across the Harzandat Plain varied considerably. In the central, southern, and southeastern parts of the plain, the soil texture was predominantly light to medium, while in the western areas it ranged from medium to heavy. The central section of the plain contained very heavy soils with more than 50% clay content.
The soil pH ranged between 7.9 and 8.2 in the northwestern and, to some extent, the eastern parts of the plain. In the central areas, which covered the largest portion of the region, the pH values varied from 8.2 to 8.5, whereas in the southern and southwestern zones, they ranged between 8.5 and 8.7.
Soil salinity was generally low throughout most of the study area and posed no significant limitation for quinoa cultivation, with electrical conductivity values below 5 dS/m. However, in some central parts, salinity levels reached up to 15 dS/m. This increase was attributed to the concave topography of the region, which led to the accumulation of salts in the lower-lying areas.
The proportion of surface gravel was below 15% in the northern, western, and southern parts of the region, while some sections in the west and east contained more than 15%, reaching up to 40%. In the eastern, northern, and central zones, the gravel content increased substantially, up to 55%, which could cause major restrictions for cultivation activities and machinery movement.
Topographically, the central parts of the plain were almost flat or had a very gentle slope. Moving toward the northern, eastern, and western areas, the land slope gradually increased.
Highly suitable lands for quinoa cultivation were primarily located in the western parts of the plain, particularly around the villages of Galin Qayah and Zal, as well as in smaller patches south of Orian Tappeh village in the east. These highly suitable areas covered approximately 3,850 hectares, accounting for about 21% of the total study area. Moderately suitable lands, with minor limitations for quinoa cultivation, were scattered throughout various parts of the plain and covered around 4,600 hectares, representing roughly 25% of the total area.
Land classified as marginally suitable covered about 5,580 hectares (around 30%), while the “currently unsuitable but improvable” category included approximately 1,540 hectares (about 8%). Permanently unsuitable lands, where cultivation was not feasible due to severe limitations, covered about 2,760 hectares, equivalent to roughly 15% of the total area
Discussion
According to the soil survey report of the Harzandat Plain, the most significant limiting factors for cultivating agricultural crops, including quinoa, are land slope, electrical conductivity (EC), pH, soil texture, and the proportion of surface gravel. The final land suitability analysis indicated that approximately 3,850 hectares of the area were completely suitable for quinoa cultivation, showing no major limitations and offering the potential for maximum yield. In other words, based on the growth requirements of quinoa, the selected evaluation criteria in this study were found to be optimal within these lands, and any existing restrictions were considered minimal.
An additional 4,600 hectares were identified as having minor limitations due to soil-related factors and land slope. In some cases, these constraints were mainly associated with slope, EC, and surface gravel, which could be mitigated with reasonable management interventions and moderate investment. However, limitations arising from pH and soil texture are less amenable to direct correction and would require careful agronomic management to minimize their effects. Despite these challenges, quinoa cultivation in these areas remains both profitable and economically justifiable.
Approximately 5,580 hectares were classified as marginally suitable, or “critical suitability” lands, where cultivation is possible but with low profitability. Considering the extent and number of limiting factors in these areas, quinoa cultivation is not recommended due to the limited economic returns. The remaining lands were categorized as unsuitable because of multiple and severe limitations. These findings are consistent with previous studies that have emphasized allocating highly suitable and moderately suitable lands to quinoa production while recommending further evaluation for marginally suitable areas (Seyed Jalali et al., 2020; Farajnia et al., 2021).
Since 2006, repeated drought events have occurred across different parts of the province, leading to reductions in crop yields of up to 35%. The recession of Lake Urmia is one of the most notable consequences of recent droughts, which has had a detrimental effect on both the quantity and quality of groundwater resources (Jahanbakhsh, 2018). To mitigate the impacts of climate change, it is recommended to incorporate quinoa into the regional crop rotation system, given its low water requirement and high tolerance to heat stress. Further systematic research is necessary to identify quinoa varieties suitable for both irrigated and rain-fed conditions and to determine their specific water and nutrient requirements. With proper management and the introduction of suitable genotypes, quinoa cultivation could play an important role in enhancing food security, increasing farmers’ income, and reducing water consumption, particularly in dryland farming systems
Conclusion
Quinoa can be cultivated in more than 40% of the lands across the Harzandat Plain. These suitable areas are scattered throughout different parts of the plain, with the highest concentration found in the western region. In contrast, the central part of the plain contains the largest portion of unsuitable lands, mainly due to high soil salinity and heavy texture. However, given the presence of a seasonal river flowing through the central plain, these limitations could potentially be alleviated or mitigated through appropriate leaching and drainage practices.
Acknowledgments: None reported by the authors.
Ethical Permission: None declared by the authors.
Conflict of Interest: The authors declare no conflicts of interest.
Authors’ Contributions: Farajnia A (First Author), Principal Researcher/Introduction Writer/Methodologist/ Statistical Analyst (50%); Chakherlou S (Second Author), Assistant Researcher/Discussion Writer/Statistical Analyst (50%).
Funding: No financial support was reported by the authors.
Keywords:
References
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