Growth and yield of chia (Salvia hispanica L.) in the Mediterranean and desert climates of Chile

Baginsky, Cecilia; Arenas, J. M.; Escobar, Hugo; Garrido, Marco; Valero, Natalia; Tello, Diego Sebastián; Pizarro, Leslie; Valenzuela, Alfonso; Morales, Luis; Silva, Hermán

doi:10.4067/s0718-58392016000300001

Cited by 64 publications

(81 citation statements)

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“…The Las Cruces station (33°30' S; 71°36' W) had low grain yield due to frosts that affected the development of the crop. All three stations produced economically sustainable biomass both in the central and northern zones of the country (Baginsky et al, 2016). In spite of these good results, none of the stations was classified in the highest suitability categories; Canchones was in the "moderately suitable" category, while Azapa and Las Cruces were "marginally suitable".…”

Section: Discussionmentioning

confidence: 92%

“…In spite of these good results, none of the stations was classified in the highest suitability categories; Canchones was in the "moderately suitable" category, while Azapa and Las Cruces were "marginally suitable". In contrast to its classification, Baginsky et al (2016) considered that Azapa was the station with greatest and most stable yields. This incongruence has the same explication as the classification of the oases with Salvia discussed above, the lack of representation of the topoclimates present in the localities of the experimental stations, given the spatial resolution and the quality of the raster layers used in the models.…”

Section: Discussionmentioning

confidence: 99%

“…The coastal zones are exposed to salinity, and although chia may be cultivated with saline irrigation water of 3.0 dS/m, oil production decreased by 20% (Heuer et al, 2002). Baginsky et al (2016) reported the grain and biomass yields of chia in three experimental crops: Azapa (Arica), Canchones (Iquique) and Las Cruces (Fig. 5B).…”

Section: Discussionmentioning

confidence: 99%

“…Considering that among natural factors climate is the one that most affects plant development (Baginsky et al, 2016), we defined a climatic zoning to determine the territorial pattern of aptitude for chia cultivation. Yield data for the species according to environmental variables is required to do this type of zoning, such as that defined by Ecocrop (2007), but this information has not been published for chia.…”

Section: Introductionmentioning

confidence: 99%

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Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model

Cortés

Silva

Baginsky

et al. 2017

Span. j. agric. res.

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Salvia hispanica L., known as chia, is a plant species originally from tropical and subtropical Mesoamerica. It is economically important because its seeds produce omega-3, thus its demand has increased in Chile and internationally. As there is no commercial production in Chile, we investigated the places in the country where this species could be cultivated in order to satisfy at the least the national demand. The aim of the study was to quantify the main climatic requirements of chia and to produce a climatic aptitude map for chia cultivation in Chile. The methodology was based on the Maxent species distribution model. We used 78 georeferenced data points where chia is grown throughout the world, mostly from the GBIF database, along with raster climatic layers from the Worldclim project. We estimated the performance curves of annual precipitation and temperature along with their respective optimal and critical values, in analogy with the Ecocrop method. The maps used two scenarios for crops in different conditions, with and without irrigation. The results indicated that the intermediate depression and coastal edge of mainly the Arica y Parinacota, Tarapacá, Antofagasta and Atacama regions have optimum conditions for irrigated crops, but it would be impossible in rainfed conditions. We conclude that chia's cultivation niche is reduced due to its tropical climate requirements; however, it can be cultivated under irrigation in northern Chile.Additional keywords: functional food; performance curves; suitability, Maxent. Abbreviations used: AUC (area under the curve); C n (critical minimum value); C x (critical maximum value); GBIF (Global Biodiversity Information Facility); O n (optimal minimum value); O x (optimal maximum value); PP (probability of presence); ROC (receiver operating characteristic); SDM (species distribution model) Tnc (minimum temperature of the coldest month); Tnw (minimum temperature of the warmest month); Txc (maximum temperature of the coldest month); Txw (maximum temperature of the warmest month).

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model

Cortés

Silva

Baginsky

et al. 2017

Span. j. agric. res.

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“…There have been numerous reports regarding the effect of altitude on the quality of crops. For instance, the oil content of chia planted at high altitude is significantly higher than that of chia planted at low altitude (Baginsky et al, 2016). Coffees at higher altitudes produced with better sensory quality (Alice et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Correlation between grain quality of foxtail millet ( Setaria italica [L.] P. Beauv.) and environmental factors on multivariate statistical analysis

Yang

Hong

et al. 2017

Chil. j. agric. res.

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Adapting the CROPGRO model to simulate chia growth and yield

et al. 2020

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Chia (Salvia hispanica L.) seeds are becoming increasingly popular as a superfood in Europe. However, broad experience in growing chia in temperate climates is missing. Crop simulation models can be helpful tools for management and decision-making in crop production systems in different regions. The objective of this study was to adapt the CROPGRO model for simulating growth and yield of chia. Data sets from a field experiment conducted over 2 yr in southwestern Germany (48 • 74′ N, 08 • 92′ E, 475 m above sea level) were used for model adaptation. The initial starting point was the CROPGRO-soybean [Glycine max (L.) Merr.] model as a template for parameterizing temperature functions and setting tissue composition. Considerable iterations were made in optimizing growth, development, and photosynthesis parameters. After model calibration, the simulation of leaf area index (LAI) was reasonable for both years, slightly over-predicting LAI with an average d-statistic of 0.95 and root mean square error (RMSE) of 0.53. Simulations of final leaf number were close to the observed data with dstatistic of 0.98 and RMSE of 1.36. Simulations were acceptable for total biomass (d-statistic of 0.93), leaf (d-statistic of 0.94), stem (d-statistic of 0.94), pod mass (d-statistic of 0.89), and seed yield (d-statistic of 0.88). Pod harvest index (HI) showed good model performance (d-statistic of 0.96 and RMSE of 0.08). Overall, the model adaptation resulted in a preliminarily adapted model with realistically simulated crop growth variables. Researchers can use the developed chia model to extend knowledge on the eco-physiology of chia and to improve its production and adaption to other regions. Abbreviations: CSM, cropping system model; CUL, cultivar; DSSAT, Decision Support System for Agrotechnology Transfer; ECO, ecotype; HI, harvest index; LAI, leaf area index; N1, nitrogen fertilizer treatment 0 kg ha −1 ; N2, nitrogen fertilizer treatment 20 kg ha −1 ; N3, nitrogen fertilizer treatment 40 kg ha −1 ; PD, photothermal days; PHI, pod harvest index; RMSE, root mean square error; SLA, specific leaf area; SPE, species; Tb, base temperature; TD, thermal days; Tmax, maximum temperature; Tmin, minimum temperature; Topt, optimum temperature. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Growth and yield of chia (Salvia hispanica L.) in the Mediterranean and desert climates of Chile

Cited by 64 publications

References 14 publications

Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model

Climatic zoning of chia (Salvia hispanica L.) in Chile using a species distribution model

Correlation between grain quality of foxtail millet ( Setaria italica [L.] P. Beauv.) and environmental factors on multivariate statistical analysis

Adapting the CROPGRO model to simulate chia growth and yield

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