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Article

Production of Quinoa Leafy Greens in High Tunnel for Season Extension in Missouri

Department of Agriculture and Environmental Sciences, Lincoln University of Missouri, Jefferson City, MO 65102, USA
*
Author to whom correspondence should be addressed.
Horticulturae 2023, 9(2), 209; https://doi.org/10.3390/horticulturae9020209
Submission received: 9 January 2023 / Revised: 31 January 2023 / Accepted: 3 February 2023 / Published: 4 February 2023
(This article belongs to the Section Vegetable Production Systems)

Abstract

:
There is limited information regarding the use of quinoa fresh leaves as a vegetable. Thus, the objective of this study was to promote quinoa green leaves as a vegetable, as well as to conduct a season extension feasibility study using high tunnels. The study was conducted during the spring seasons of 2020, 2021, and 2022 at the George Washington Carver farm of Lincoln University in Jefferson City, MO, USA. Three quinoa genotypes were used in a randomized complete block design (RCBD) with three replications over three years. Agronomic data and leaf nutritional analyses for young plants approximately 30 days old were evaluated. Among the three quinoa genotypes, genotype Ames 13724 gave the highest yield of leafy greens and was consistent over the three years. Additionally, the use of high tunnels served as a season extension tool by accelerating the production of quality fruits and vegetables outside typical growing seasons. The results indicated that season extension of quinoa leafy greens production in a high tunnel is possible with a three-week earlier harvest in early spring when fewer fresh vegetables are available in the markets. Farmers can increase farm income by selling this specialty vegetable in the early season for premium prices.

Graphical Abstract

1. Introduction

Quinoa (Chenopodium quinoa Willd.) leafy greens, a non-traditional nutrient-rich leafy vegetable, is a suitable candidate under the situation that could be produced year-round in the field, greenhouse, and high tunnel. However, for small to medium-scale farmers, the use of high tunnels as one of the season extension tools is crucial in improving the competitiveness of specialty crops including vegetable growers in Missouri. A high tunnel or hoop house is a greenhouse-like structure without a heating or cooling system enclosed in polyethylene, polycarbonate, plastic-covered metal structure. It is used to cover and protect crops from the sun, wind, excessive rainfall, or cold, to extend the growing season in an environmentally safe manner. High tunnels are a low-cost technology that can strengthen local and regional food systems by helping the production of high-quality fruits and vegetables during and beyond the growing season [1,2,3]. High tunnel technology has become popular in many countries of Asia and Europe since the 1970s, but the use of high tunnels is relatively new in the USA. Between 2010 and 2015, USDA-NRCS sponsored the ‘Environmental Quality Incentives Program’ (EQIP)- a high tunnel initiative program that has supported the construction of more than 14,000 high tunnels in all 50 States [4]. The NRCS reimburses farmers for a portion of their cost for high tunnel construction. There has been increasing interest from growers in the USA to produce a variety of specialty crops using a high tunnel, particularly among historically underserved, small, and low-income farmers selling their products directly to consumers [5,6,7].
Consumption of fruits and vegetables reduces the risk of heart disease, stroke, and some types of cancers, and managing body weight. According to CDC, only 9% of American adults eat the recommended amount of vegetables [8]. The dietary guidelines for Americans recommend five servings of fruits and vegetables per day (based on an intake of 2000 calories), with green leafy vegetables or leafy greens as one of the five recommended servings [9]. Leafy greens are an essential food due to their high nutritional values, richness in health-promoting phytonutrients, and bioactive components. They contain high amounts of vitamins, minerals, amino acids, and antioxidants [10,11,12]. A single variety cannot provide all the nutrients for adequate bodily functions; therefore, different types and amounts of leafy vegetables are essential for a healthy diet. To meet this increasing demand, farmers/growers are also looking for nutrition-rich new crops to meet the increased demand, even from non-traditional crops.
Major vegetable crops grown using high tunnels in the United States include tomatoes, cucumbers, peppers, lettuce, cabbage, Asian beans, and spinach. Among them, tomatoes alone cover more than 50% of the cultivated areas [13,14,15]. Bruce [6] reported that more than half of the fresh produce grown in high tunnels are sold directly to consumers. Although there are no differences in total yield between production in high tunnels versus open fields [16,17], earlier harvest times and premium prices are the main advantages of high tunnel production. To date, no reports are available on production of quinoa (Chenopodium quinoa Willd.) leafy greens in high tunnel for season extension.
The fresh leaves and tender shoots of quinoa can be eaten as cooked vegetables and as a salad to which quinoa sprouts can be added [18,19,20,21]. Quinoa leaves contain high qualities of protein and all essential amino acids, a high amount of omega-3 fatty acids, essential minerals, and a low amount of carbohydrates [22,23,24]. Quinoa leaves are also rich in chlorophyll, carotenoid, and anthocyanin pigments and rich in health-promoting properties such as antimicrobial, anticancer, antidiabetic, antiobesity, and antioxidant [25,26,27,28]. However, the consumption of quinoa leafy greens as vegetables is less common. Quinoa is a drought-, salinity-, and cold-tolerant crop that requires little water and fertilizer to grow. It can be grown year-round (in the field, greenhouse, or high tunnel/hoop house), with a harvesting time of about 4–6 weeks (planting to harvesting) and can be grown early spring and late fall for season extension. Quinoa leafy greens are emerging as a promising vegetable that can provide a wide variety of benefits including, higher market prices from off-season vegetables, diversifying crop choice as a new specialty crop, and increase farm profit to marginal farmers. Also, it can make access, availability, and consumption of value-added fresh and nutrient-rich leafy greens affordable prices in rural areas. It can contribute significantly to consumer nutritional needs and growers’ economic viability and success. This study was aimed to select suitable quinoa varieties for high tunnel production, to assess the feasibility of quinoa leaf season extension while using high tunnels, and to promote quinoa green leaves as a vegetable crop.

2. Materials and Methods

2.1. Study Location and High Tunnel Structure

The experiment was conducted at the George Washington Carver Farm (lat. 38.32° N, long. 92.80° W, and elevation 170 m) of Lincoln University, Jefferson City, MO, USA. The high tunnel was a single-bay, four-season metal-framed tunnel with a dimension of 30 m long, 6 m wide, and 3.7 m high with a north-south orientation. It was covered with a single-layer clear 0.15 mm polyethylene plastic with roll-up sides for ventilation. During the study, sides were closed automatically when the air temperature was below 20 °C and remained open otherwise with a temperature above 20 °C. A temperature and humidity sensor, Hobo Onset-MX2302A (Onset Computer Corporation, Bourne, MA, USA) was connected to a data logger to monitor air temperature and relative humidity (RH) inside the high tunnel. The high tunnel outdoor temperature and RH data were collected from the USDA-NRCS National Weather and Climate Center (NWCC)-Soil Climate Analysis Network (SCAN) site #2223 located at Carver farm, Jefferson City, MO, USA (https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=2223, (accessed on 15 September 2022).

2.2. Plant Materials, Experimental Design and Methods

Plant Materials: Three quinoa genotypes namely, Ames 13724, PI 614885, and PI 665275 (NM, USA, Chile, and Bolivia, respectively) were used in this study. These lines were selected based on previous test results of early vegetative growth and yield of leafy greens. Seeds of these lines were collected from the USDA-ARS Germplasm Resources Information Network (GRIN-North Central Research Plant Introduction Station, Ames, IA, USA). Subsequently, seeds were increased at the Lincoln University Carver Farm for further studies.
Experimental design: The experiment was set in a randomized complete block design (RCBD) with three replications. The three quinoa genotypes were arranged randomly within the block. Each block consisted of three plots, each 1.0 m long and 1.3 m wide, with a net area of 3.9 m2 for each block.
Methods: The three genotypes were grown from March through May in 2020, 2021, and 2022 at the Lincoln University George Washington Carver Farm in Jefferson City, MO, USA, under high tunnel conditions. The texture of the soil at the site was a well-drained and moderately permeable silt loam with 20% clay content and 0.8% organic matter with a soil pH of 6.5 to 6.8. Before sowing, the soil fertility was improved by incorporating fertilizer at the rate of 12.50 kg/ha each of N, P, and K. In addition, one bag of compost (1 cubic foot, 0.03 cubic meter) was applied in each block of 3.9 m2. Before seed sowing, the soil surface was labeled and soaked well with water for uniform seed germination. Two-hour pre-soaked quinoa seeds were sown manually at a depth of one cm in rows of about 20–25 seeds per one linear meter, about 450 seeds per m2. The line spacing was 7.5 cm. A drip irrigation system was installed and irrigated as needed. The weeds were cleared manually, and no pesticides were applied in the plants.

2.3. Data Collection and Plant Harvest

When plants were about five-week-old, data were collected for plant height (cm), leaf area (cm2), and leaf chlorophyll content (Figure 1). Leaf area was measured using LI-3000C portable leaf area meter (LI-COR Biosciences, Lincoln, NE, USA) from the plant’s fully expanded top third leaf. Three plants were randomly selected to measure leaf area from each replication. Leaf SPAD (Soil-Plant Analysis development) was measured on the top three fully expanded leaves of each replication using a chlorophyll meter, SPAD 502 (Konica Minolta, Inc., Osaka, Japan). The SPAD meter measures the difference between the transmittance of a red light (650 nm) and an infrared (940 nm) light through the leaf, generating a SPAD value [29]. After data collection, plants were harvested about 10–12 cm above the ground from a unit area (900 cm2) from each replication to record fresh leafy greens yield.

2.4. Nutritional Analysis

Nearly a month-old fresh leaf of each variety from each replication were collected in 2020, and 2021 for nutritional analysis. Protein, fat, fiber and ash in dried leaves were determined following the procedure described by the Association of Official Analytical Chemists [30]. The analysis was performed at the Experiment Station Chemical Laboratories (ESCL) of the University of Missouri, Columbia, MO, USA (https://aescl.missouri.edu/contactUS.html, (accessed on 10 August 2021). The total nitrogen content in the dried samples was determined by the Kjeldahl method following AOAC method 984.13 (A–D). Crude fat and fiber were determined following the AOAC method 920.39 (A) and 978.10, respectively. The ash was determined following the AOAC procedure by the combustion of samples at 600 °C for 8 h. The carbohydrate content was calculated using the following equation:
Carbohydrate (%) = 100% − % (crude protein + crude fat + ash + moisture)

2.5. Statistical Analysis

Analyses of variance for quinoa leafy greens yield, and other agronomic traits and nutritional values were calculated by considering replication as a random effect, while the variety and growing seasons (year) were considered as a fixed effect. To validate the normality and homoscedasticity of all measured variables, Shapiro–Wilk’s and Brown–Forsythe’s, and Levine’s tests were used. To capture variability among varieties, data of yield, all agronomic traits data, and nutritional values were analyzed using JMP Pro 13 Software, Statistical Discovery from SAS. For non-normally distributed data, log transformation was applied. Tukey’s HSD test was used to determine differences among genotypes for different traits at the p < 0.05 level of significance. The least-square means were calculated using JMP Genomics 6 [31], where replication was treated as a random effect. Correlation analysis was performed using the restricted maximum likelihood method to evaluate the relationship between different traits of interest.

3. Results and Discussion

The experiment was conducted in 2020, 2021, and 2022. Planting and leafy greens harvesting dates differ by only one week across the years, but the total duration of plant growth was the same. Seeding and harvesting dates, growth duration, and maximum, minimum, and average temperature (°C) inside and outside the high tunnel during quinoa greens growing seasons are presented in Table 1. The harvesting time of quinoa leafy greens as vegetables for yield and nutritional values in different countries and in different seasons ranged from 30 to 62 days after sowing (DAS) [22,23,27,32,33].

3.1. Plant Height, Chlorophyll Content, Leaf Area, Plant Number, and Yield

When the three tested quinoa lines across three-year compared, a significant difference was observed among varieties for leafy greens yield (Yd), leaf area (La), and chlorophyll content (Ch) (Table 2). The year significantly impacted all agronomic traits except leafy greens yield. The significant year-by-variety interaction revealed that year had an impact on the number of plants per unit area (Pn), and this effect was dependent on the variety. No significant year-by-variety interactions were observed for Yd, La, Ch, and Ht, suggesting that varieties showed consistency across the years.
The least-square means indicated significant variability among quinoa varieties for leafy greens yield, leaf area, chlorophyll, and plant height (Table 3). Ames 13724 produced significantly higher leafy greens yield, chlorophyll content, leaf area, and plant height compared to varieties used in this study. The number of plants per unit area showed no significant differences.
Trait’s correlation: Figure 2 depicts the relationship between agronomic and physiological traits of quinoa lines. A significant and positive correlation was observed between plant height and leaf chlorophyll content (r = 0.42), while a negative association was observed between plant height and the number of plants per unit area (r = −0.76). A significant and negative correlation was observed between chlorophyll content and the number of plants per unit area (r = −0.61). The leaf area also positively correlated with yield (r = 0.39) and chlorophyll content (r = 0.30).
Yield performance: Figure 3 illustrates the yield performance of three quinoa varieties under high tunnel conditions. Among the three lines, Ames 13724 produced significantly higher leafy greens yield compared to other two quinoa lines. However, no significant yield differences observed between varieties PI 614885, and PI 665275 under high tunnel conditions. A similar yield trial was conducted in the field, but, there were no significant yield differences between high tunnel and field (field data not presented) grown leafy greens. There was a significant difference in vegetative growth and yield among the tested three varieties. It might be due to differences in cultivar origin. The obtained results are in harmony with other reports stating that cultivar and or genetic variation significantly influence vegetative growth and yield [34,35,36].

3.2. Nutritional Composition-Proximate Analysis

Among the three tested quinoa lines over the two years (2020 and 2021), there was a significant difference in protein, oil, ash, moisture, and carbohydrate contents except for fiber content (Table 4). Variety and year interaction was significant for protein and carbohydrate content. The interaction between variety and year was not significant for moisture, fat, and fiber contents, suggesting that these nutritional qualities are consistent across the years.
Figure 4 portrays the proximate analysis of dry leaves of three varieties of quinoa grown in the high tunnel in 2020 and 2021. The quinoa genotype Ames 13724 contained significantly higher fat and protein in quinoa dry leaf. However, it contained significantly low ash, carb, and moisture. The PI 614885 contained significantly higher carbohydrate and moisture while it contained low ash, fat, and protein. The PI 665275 contained significantly higher ash and protein, while the same variety contained low carb, fat, and moisture content. It appears that Ames 13724 holds better nutritional quality compared to the PI 614885, and PI 665275 lines.
Correlation of nutritional traits: Figure 5 shows the correlation between the different nutritional values of dry leaves of three quinoa genotypes. The correlations between protein and carbohydrate (r = −0.94), moisture and fat (r = −0.96), moisture and carbohydrate (r = −0.58), and ash and fat (r = −0.65) were negative and significant (p ≤ 0.05) suggesting lower the carbohydrate, higher the protein and moisture and vice versa. A significant and positive linear relationship was observed between moisture and ash (r = 0.52) while a negative association was observed between ash and carbohydrate (r = −0.64). A significant linear relationship was observed between fat and carbohydrate (r = 0.65).
In this study, dry leaves of quinoa have a higher amount of protein and a lower amount of carbohydrate, and the results agree with other studies with dry leaves of quinoa [23,24]. Also, a negative correlation was observed between protein and carbohydrates, where higher protein content had a lower amount of carbohydrate, is in accord with the finding of Pathan et al. [24]. Samaha et al. [37] reported that higher plant-based protein and lower carbohydrate intake help in weight control in humans. The lower fat contents in quinoa leaves were within the range found in other leafy green vegetables including quinoa and spinach [23,24,38]. Commonly, leafy vegetables are poor sources of fat.

4. Conclusions

The use of a high tunnel/hoop house production system for season extension has increased significantly in the last few years, particularly by small and low-income farmers. A three-year trial demonstrated the ability of quinoa leafy greens production in a high tunnel far earlier than regular production systems in Missouri. These early-season fresh leafy greens products have premium prices over the regular season crop. The result of the nutritional analysis of the dry leafy greens in this study agrees with previous reports. Among the three quinoa genotypes, Ames 13724 produced the highest yield and nutritional values, which were consistent across the experimental period. This study was the first to establish that quinoa leafy greens could be produced about 3-week earlier in the spring. However, more research is still needed. Vegetable growers can increase farm income by growing this new non-traditional nutrient-rich vegetable, as well as fulfilling consumer nutritional needs.

Author Contributions

Funding acquisition and project supervision, data curation, conceptualization, methodology, writing, S.P.; data analysis, review, and editing, A.G.A.; field work and data collection, S.P., G.N., M.R.I. and S.T.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the senior author (S.P.) through the USDA-NIFA Evans-Allen project for ‘Quinoa leafy vegetable production research’ (award #1019846).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

The senior author (S.P.) would like to thank Lincoln University of Missouri for supporting this research, and USDA-NIFA for providing funding to the senior author. Also, the authors would like to thank the USDA-Germplasm Resources Information Network (GRIN) for providing quinoa seeds.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Carey, E.E.; Jett, L.; Lamont, W.J., Jr.; Nennich, T.T.; Orzolek, M.D.; Williams, K.A. Horticultural Crop Production in High Tunnels in the United States: A Snapshot. HortTechnology 2009, 19, 37–43. [Google Scholar] [CrossRef]
  2. Lamont, W. Overview of the use of high tunnels worldwide. HortTechnology 2009, 19, 25–29. [Google Scholar] [CrossRef]
  3. Orzolek, M.D. Increasing economic return to high tunnel with specialty crops. Acta Hort. 2013, 987, 83–88. [Google Scholar] [CrossRef]
  4. NSAC: National Sustainable Agriculture Coalition. High Tunnels Create Opportunities for New Farmers. NSAC’s Blog. 8 July 2016. Available online: https://sustainableagriculture.net/blog/high-tunnels-create-opportunities/ (accessed on 20 August 2022).
  5. Bruce, A.B.; Farmer, J.R.; Maynard, E.T.; Valliant, J.C.D. Assessing the impact of the EQIP High Tunnel Initiative. J. Agril. Food Syst. Comm. Dev. 2017, 7, 159–180. [Google Scholar] [CrossRef]
  6. Bruce, A.B.; Maynard, E.T.; Farmer, J.R. Farmers’ perspectives on challenges and opportunities associated with using high tunnels for specialty crops. HortTechnology 2019, 29, 290–299. [Google Scholar] [CrossRef]
  7. O’Connell, S.; Rivard, C.; Peet, M.M.; Harlow, C.; Louws, F. High tunnel and field production of organic heirloom tomatoes: Yield, fruit quality, disease, and microclimate. HortScience 2012, 47, 1283–1290. [Google Scholar] [CrossRef]
  8. CDC: Centers for Disease Control and Prevention. Strategies to Prevent Obesity and Other Chronic Diseases: The CDC Guide to Strategies to Increase the Consumption of Fruits and Vegetable; U.S. Department of Health and Human Services: Atlanta, GA, USA, 2011.
  9. U.S. Department of Health and Human Services (HHS); U.S. Department of Agriculture (USDA). 2015–2020 Dietary Guidelines for Americans, 8th ed.; U.S. Department of Health and Human Services (HHS); U.S. Department of Agriculture (USDA): Denver, CO, USA, 2015.
  10. Barkat, N.; Singh, J.; Jayaprakash, G.K.; Patil, B.S. Effect of harvest time on the levels of phytochemicals, free radical-scavenging activity, alpha-amylase inhibition and bile acid binding capacity of spinach (Spinacia oleracea). J. Food Sci. Agron. 2018, 98, 3468–3477. [Google Scholar] [CrossRef]
  11. Sarker, U.; Oba, S. Nutrients, minerals, pigments and phytochemicals, and radical scavenging activity in Amaranthus blitum leafy vegetables. Sci. Rep. 2020, 10, 1–9. [Google Scholar] [CrossRef] [PubMed]
  12. Sivakumar, D.; Chen, L.Y.; Sultanbawa, Y. A comprehensive review of beneficial dietary phytochemicals in common traditional Southern African leafy vegetables. Food Sci. Nutr. 2018, 6, 714–727. [Google Scholar] [CrossRef]
  13. Borrelli, K.; Koenig, R.T.; Jaeckel, B.M.; Miles, C.A. Yield of Leafy Greens in High Tunnel Winter Production in the Northwest United States. Hortscience 2013, 48, 183–188. [Google Scholar] [CrossRef] [Green Version]
  14. NASS-USDA: National Agricultural Statistics Service—US Department of Agriculture. Census of Agriculture; Horticultural Specialties; 2014. Available online: http://www.agcensus.usda.gov/Publications (accessed on 6 July 2022).
  15. Reeder, B.; Foshee, W.; Blythe, E.; Kessler, R.; Kemble, J.; Vinson, E.; Dozier, W.; Wells, L. High Tunnel Production of Tomatoes for Season Extension in Southeast Alabama. Horticulturae 2020, 6, 94. [Google Scholar] [CrossRef]
  16. Rogers, M.A.; Wszelaki, A.L. Influence of High Tunnel Production and Planting Date on Yield, Growth, and Early Blight Development on Organically Grown Heirloom and Hybrid Tomato. Horttechnology 2012, 22, 452–462. [Google Scholar] [CrossRef]
  17. Zhao, Y.; Gu, M.M.; Bi, G.H.; Evans, B.; Harkess, R. Planting Date Effect on Yield of Tomato, Eggplant, Pepper, Zinnia, and Snapdragon in High Tunnel in Mississippi. J. Crop Improvement 2014, 28, 27–37. [Google Scholar] [CrossRef]
  18. Bhargava, A.; Shukla, S.; Deepak, O. Chenopodium quinoa: An Indian perspective. Ind. Crops Prod. 2006, 23, 73–87. [Google Scholar] [CrossRef]
  19. Gawlik-Dziki, U.; Swieca, M.; Sulkowski, M.; Dziki, D.; Baraniak, B.; Czyz, J. Antioxidant and anticancer activities of Chenopodium quinoa leaves extracts- In vitro study. Food Chem. Toxicol. 2013, 57, 154–160. [Google Scholar] [CrossRef] [PubMed]
  20. Jancurová, M.; Minarovičová, L.; Dandár, A. Quinoa-A Review. Czech J. Food Sci. 2009, 27, 71–79. [Google Scholar] [CrossRef]
  21. Vazquez-Luna, A.; Cortes, V.P.; Carmona, F.F.; Diaz-Sobac, R. Quinoa leaf as a nutritional alternative. Ciencia Invest. Agraria. 2019, 46, 137–143. [Google Scholar] [CrossRef]
  22. Adamczewska-Sowińska, K.; Sowiński, J.; Jama-Rodzeńska, A. The effect of sowing date and harvest time on leafy greens of quinoa (Chenopodium quinoa willd.) yield and selected nutritional parameters. Agriculture 2021, 11, 405. [Google Scholar] [CrossRef]
  23. El-Samad, E.; Hussin, S.; El-Naggar, A.; El-Bordeny, N.; Eisa, S. The potential use of quinoa as a new non-traditional leafy vegetable crop. Biosci. Res. 2018, 15, 3387–3403. [Google Scholar]
  24. Pathan, S.; Eivazi, F.; Valliyodan, B.; Paul, K.; Ndunguru, G.; Clark, K. Nutritional composition of the green leaves of quinoa (Chenopodium quinoa Willd.). J. Food Res. 2019, 8, 55–65. [Google Scholar] [CrossRef]
  25. Le, L.; Gong, X.; An, Q.; Xiang, D.; Zou, L.; Peng, L.; Wu, X.; Tan, W.; Nie, Z.; Wu, Q.; et al. Quinoa sprouts as potential vegetable source: Nutrient composition and functional contents of different quinoa sprout varieties. Food Chem. 2021, 357, 129752. [Google Scholar] [CrossRef]
  26. Saini, S.; Saini, K. Chenopodium album Linn: An outlook on weed cum nutritional vegetable along with medicinal properties. Emergent Life Sci. Res. 2020, 6, 28–33. [Google Scholar] [CrossRef]
  27. Wan, Y.; Zhou, M.; Le, L.; Gong, X.; Jiang, L.; Huang, J.; Cao, X.; Shi, Z.; Tan, M.; Cao, Y.; et al. Evaluation of morphology, nutrients, phytochemistry and pigments suggests the optimum harvest date for high-quality quinoa leafy vegetable. Scientia Hort. 2022, 304, 111240. [Google Scholar] [CrossRef]
  28. Yadav, R.K.; Tomar, B.S.; Pachauri, N.; Jain, V. Studies of nutritional properties and antioxidant potential in green leafy vegetables. J. Sci. Food Agril. 2018, 2, 7–13. [Google Scholar]
  29. Uddling, J.; Gelang-Alfredsson, J.; Piikki, K.; Pleijel, H. Evaluating the relationship between leaf chlorophyll concentration and SPAD-502 chlorophyll meter readings. Photosynth. Res. 2007, 91, 37–46. [Google Scholar] [CrossRef] [PubMed]
  30. AOAC: Association of Official Analytical Chemist. Official Methods of Analysis, 18th ed.; AOAC International: Gaithersburg, MD, USA, 2006. [Google Scholar]
  31. JMP. Version 2; The SAS Institute Inc.: Cary, NC, USA, 2013. [Google Scholar]
  32. El-Naggar, A.; Hussin, S.; Abd El-Samad, E.; Eisa, S. Quinoa as a new leafy vegetable crop in Egypt. Arab Univ. J. Agril. Sci. 2018, 26, 745–753. [Google Scholar] [CrossRef]
  33. Pathan, S.; Siddiqui, R. Nutritional composition and bioactive components in quinoa greens—A Review. Nutrients. 2022, 14, 558. [Google Scholar] [CrossRef] [PubMed]
  34. Ahmadi, H.; Akbarpour, V.; Dashti, F.; Shojaeian, A. Effect of different levels of nitrogen fertilizer on yield, nitrate accumulation and several quantitative attributes of five Iranian spinach accessions. Amer. Eurasian J. Agric. Environ. Sci. 2010, 8, 468–473. [Google Scholar]
  35. Mbwambo, O.; Abukutsa-Onyango, M.O.; Dinssa, F.F.; Ojiewo, C. Performances of elite amaranth genotypes in grain and leaf yields in Northern Tanzanian. J. Hort. 2015, 7, 16–23. [Google Scholar] [CrossRef]
  36. Koudela, M.; Petříková, K. Nutrients content and yield in selected cultivars of leaf lettuce (Lactuca sativa L. var. crispa). Hort. Sci. 2008, 35, 99–106. [Google Scholar] [CrossRef]
  37. Samaha, F.F.; Iqbal, N.; Seshadri, P.; Chicano, K.L.; Daily, D.A.; McGrory, J.; Williams, T.; Williams, M.; Gracely, E.J.; Stern, L.; et al. A low-carbohydrate as compared with a low-fat diet in severe obesity. N. Engl. J. Med. 2003, 348, 2074–2081. [Google Scholar] [CrossRef] [PubMed]
  38. Onuminya, T.O.; Shodiya, O.E.; Olubiyi, O.O. Comparative proximate and phytochemical analyses of leafy vegetables of Lagos state. Niger. J. Pure Appl. Sci. 2017, 30, 3097–3103. [Google Scholar] [CrossRef]
Figure 1. Five-week-old leafy greens of three varieties of quinoa at Lincoln University Carver farm, May 2022.
Figure 1. Five-week-old leafy greens of three varieties of quinoa at Lincoln University Carver farm, May 2022.
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Figure 2. Correlation matrix of yield (Yd), plant height (Ht), leaf area (La), leaf chlorophyll content (Ch), number of plants per unit area (Pn), and for three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021 and 2022.
Figure 2. Correlation matrix of yield (Yd), plant height (Ht), leaf area (La), leaf chlorophyll content (Ch), number of plants per unit area (Pn), and for three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021 and 2022.
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Figure 3. Yield comparison of three quinoa varieties grown in the high tunnel (2020, 2021, and 2022) for leafy greens, Lincoln University Carver farm, Jefferson City, MO, USA.
Figure 3. Yield comparison of three quinoa varieties grown in the high tunnel (2020, 2021, and 2022) for leafy greens, Lincoln University Carver farm, Jefferson City, MO, USA.
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Figure 4. Proximate analysis (g per 100 g DW) of dry leaves of three varieties of quinoa grown in the high tunnel in 2020, and 2021, Lincoln University Carver farm, Jefferson City, MO, USA. Different letters suggest significant differences among means within a column indicated by Tukey’s HSD test at p ≤ 0.05.
Figure 4. Proximate analysis (g per 100 g DW) of dry leaves of three varieties of quinoa grown in the high tunnel in 2020, and 2021, Lincoln University Carver farm, Jefferson City, MO, USA. Different letters suggest significant differences among means within a column indicated by Tukey’s HSD test at p ≤ 0.05.
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Figure 5. Correlation matrix for moisture (Mos), protein (Pro), fat, fiber (Fib), ash, and carbohydrate(Carb) for high tunnel-grown quinoa leafy greens in 2020, and 2021.
Figure 5. Correlation matrix for moisture (Mos), protein (Pro), fat, fiber (Fib), ash, and carbohydrate(Carb) for high tunnel-grown quinoa leafy greens in 2020, and 2021.
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Table 1. Seeding and harvesting dates, duration, and maximum, minimum, and average temperature (°C) inside and outside the high tunnel during quinoa greens growing seasons, March–May 2020, 2021, and 2022, Lincoln University Carver farm, Jefferson City, MO, USA.
Table 1. Seeding and harvesting dates, duration, and maximum, minimum, and average temperature (°C) inside and outside the high tunnel during quinoa greens growing seasons, March–May 2020, 2021, and 2022, Lincoln University Carver farm, Jefferson City, MO, USA.
YearSeeding DateHarvesting DateDuration DaysInside Temp °C Outside Temp °C
minmaxavminmaxav
202030 March11 May42na 1nana−4.0029.812.37
202124 March5 May 42−0.1733.7217.82−3.7028.913.1
202230 March11 May420.135.8218.41−3.8032.613.31
1 Data not available.
Table 2. The analysis of variance for leafy greens yield (Yd), leaf area (La), leaf chlorophyll content (Ch), plant height (Ht), and number of plants per unit area (Pn) of three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021, and 2022.
Table 2. The analysis of variance for leafy greens yield (Yd), leaf area (La), leaf chlorophyll content (Ch), plant height (Ht), and number of plants per unit area (Pn) of three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021, and 2022.
ParameterSourceDFSSF RatioProb > F
YdVar218665028.10.0031 **
Year21707610.70.4902
Var × Year410912712.40.091
LaVar2214.50.0259 *
Year226156.5<0.0001 ***
Var × Year4161.80.1817
ChVar21027.80.0037 **
Year228321.5<0.0001 ***
Var × Year4702.70.067
PnVar254341.50.252
Year24294511.80.0005 ***
Var × Year4541997.40.001 ***
HtVar2944.80.2881
Year268835.1<0.0001 ***
Var × Year41554.00.1790
* Significant difference at p < 0.05, ** Significant difference at p < 0.01, *** Significant difference at p < 0.001.
Table 3. Least-square means of yield (Yd), plant height (Ht), leaf area (La), leaf chlorophyll content (Ch), number of plants per unit area (Pn), and for three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021 and 2022.
Table 3. Least-square means of yield (Yd), plant height (Ht), leaf area (La), leaf chlorophyll content (Ch), number of plants per unit area (Pn), and for three varieties of quinoa grown in the high tunnel for leafy greens production in 2020, 2021 and 2022.
Lines 1Yield
(g m2−1)
Leaf Area
(cm2)
Leaf ChlorophyllPlant Number
per Unit Area
Height
(cm)
Ames 137242913.2 a20.1 a50.7 a270.3 a48.0 a
PI 6652752407.9 b18.7 ab48.1 b251.1 a46.2 ab
PI 6148852315.8 b17.9 b45.9 b236.6 a43.4 b
1 Different letters suggest significant differences among means within a column indicated by Tukey’s HSD test at p ≤ 0.05.
Table 4. The analysis of variance for moisture (Mos), protein (Pro), fat, fiber (Fib), ash, and carbohydrate (Carb) for high tunnel-grown quinoa leafy greens in 2020, and 2021.
Table 4. The analysis of variance for moisture (Mos), protein (Pro), fat, fiber (Fib), ash, and carbohydrate (Carb) for high tunnel-grown quinoa leafy greens in 2020, and 2021.
ParameterSourceDFSSF RatioProb > F
MosVariety20.614.00.0007 ***
Year120.1988.2<0.0001 ***
Variety × Year20.13.60.0596
ProVariety28811.60.0019 **
Year17018.50.0012 **
Variety × Year212316.30.0005 ***
FatVariety20.54.30.039 *
Year117.5309.0<0.0001 ***
Variety × Year20.32.60.1182
FibVariety21.80.60.5596
Year10.20.10.7347
Variety × Year24.51.50.2621
AshVariety22310.20.0026 **
Year12723.40.0004 ***
Variety × Year252.30.1383
CarbVariety216017.10.0003 ***
Year124151.6<0.0001 ***
Year × Variety2798.50.005 **
* Significant difference at p < 0.05, ** significant difference at p < 0.01, *** significant difference at p < 0.001.
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MDPI and ACS Style

Pathan, S.; Ndunguru, G.; Islam, M.R.; Jhumur, S.T.; Ayele, A.G. Production of Quinoa Leafy Greens in High Tunnel for Season Extension in Missouri. Horticulturae 2023, 9, 209. https://doi.org/10.3390/horticulturae9020209

AMA Style

Pathan S, Ndunguru G, Islam MR, Jhumur ST, Ayele AG. Production of Quinoa Leafy Greens in High Tunnel for Season Extension in Missouri. Horticulturae. 2023; 9(2):209. https://doi.org/10.3390/horticulturae9020209

Chicago/Turabian Style

Pathan, Safiullah, Grato Ndunguru, Md R. Islam, Sadia T. Jhumur, and Addissu G. Ayele. 2023. "Production of Quinoa Leafy Greens in High Tunnel for Season Extension in Missouri" Horticulturae 9, no. 2: 209. https://doi.org/10.3390/horticulturae9020209

APA Style

Pathan, S., Ndunguru, G., Islam, M. R., Jhumur, S. T., & Ayele, A. G. (2023). Production of Quinoa Leafy Greens in High Tunnel for Season Extension in Missouri. Horticulturae, 9(2), 209. https://doi.org/10.3390/horticulturae9020209

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