Camelina as a Rotation Crop for Weed Control in Organic Farming in a Semiarid Mediterranean Climate
Departament of Hortofruticulture, Botany and Gardening, Agrotecnio, University of Lleida, Alcalde Rovira Roure 191, 25198 Lleida, Spain
*
Author to whom correspondence should be addressed.
Agriculture 2018, 8(10), 156; https://doi.org/10.3390/agriculture8100156
Submission received: 20 August 2018
/
Revised: 23 September 2018
/
Accepted: 2 October 2018
/
Published: 6 October 2018
Abstract
:Crop rotation in winter cereals in semiarid Mediterranean climates is highly desirable to prevent weed infestations, but the climatic conditions make it difficult to implement alternative crops to winter cereals. Camelina (Camelina sativa (L.) Crantz) is an interesting option, as it is able to produce profitable yields thanks to its tolerance to cold and drought. In this work, three autumn–winter sowing dates (SD1, October; SD2, December; SD3, January) and two sowing rates (R1, 8 kg ha−1; R2, 11 kg ha−1) were chosen to evaluate the effectiveness of these cultural methods to control weeds over three seasons, and to determine effects on camelina seed yield. Results showed that a significant reduction of weed coverage was obtained by delaying the sowing date. Sowing rates did not show differences in weed coverage. In contrast, no apparent yield penalty was observed among sowing dates and rates. These results show that the introduction of camelina as a rotational crop in semiarid Mediterranean climates is a feasible option for helping to suppress winter weeds, as well as to provide productive seed yield in these climatic conditions.
1. Introduction
Crop rotation is among the most useful tools in order to control weeds [1] and contribute to Integrated Pest Management (IPM). It allows varying the management of fields, creating an unstable and inhospitable environment that prevents weeds from proliferating [1] as well as disrupting weed population dynamics [2]. This is of special interest in organic farming, where no chemicals can be applied for their control. However, the range of crops used in rotation with cereals in Mediterranean semiarid dryland systems is scarce. Rotation with pea (Pisum sativum L.) and sunflower (Helianthus annuus L.), which intrinsically imply a sowing delay, have proven to be effective for weed control in these climatic conditions [3,4]. Nevertheless, the limited rainfall in semiarid drylands hampers the integration of some of these crops [3].
In the driest part of the Ebro Basin, in northeastern Spain, annual rainfall is about 350 mm [5] and usually presents an erratic distribution [6], which highly affects cereal yields. The future projection of climate change is expected to increase evapotranspiration and decrease rainfall [7]. For this reason, new drought-tolerant crops with the ability to optimize water efficiency and production are being promoted by the Spanish Government [8].
Camelina is one such crop that may well fit with these requirements. Although it is an ancient crop [9,10], it was minimally produced for centuries until the last decade [11]. Its unique oilseed composition has been widely highlighted [12] and is useful for either industrial purposes, such as biodiesel [13,14], or for human consumption [15,16,17]. It can be considered either as a winter [18] or summer crop [19,20]. It has a short life cycle [21], which varies from 58 to 134 days as a summer crop [22,23] and from 209 to 298 days as a winter crop [15,24]. Moreover, the hardiness of the crop [24] makes it suitable for cropping in low input agricultural fields, such as organic systems. The capability of camelina to adapt to different environments [11] makes it suitable for changing sowing dates for its production. In this respect, many studies have been performed in North America [19,25,26,27], but all these sowing dates (SD) are for spring-sown experiments done under temperate continental climates. By contrast, Berti et al. [21] compared different autumn and winter SDs in humid Mediterranean climates and found that significant differences in yield and yield components were dependent on environment and latitude. Whether this also happens in a semiarid Mediterranean climate for autumn- and winter-sown camelina in Spain is unknown.
The objective of this work was to study the effect of different sowing dates of camelina on the control of weeds and its effect on camelina seed yield, so that the inclusion of this crop in rotation with organic winter cereals in the Mediterranean semiarid region of Spain could be evaluated.
2. Material and Methods
2.1. Site Description
The experiment was carried out in a field at the University of Lleida, 41°37′ N–0°35′ E, at 180 m above the sea level. The soil was a clay loam soil, with 31% sand, 38% silt, and 31% clay, pH 8.4, 0.95% of organic matter, and 155 mg kg−1 of N. The climate in Lleida is considered as Mediterranean semiarid and semicontinental [28], although according to the Köppen classification it is considered as a tropical and subtropical steppe climate (BSk). The mean annual temperature over the last four years (2014–2017) was 16.0 °C and total yearly precipitation averaged 291 mm [5].
2.2. Experimental Design
The experiment was carried out over three seasons: 2015–2016, 2016–2017, and 2017–2018. Seeds of Camelina sativa cultivar GP204 from Great Plain Soil & Exploration were provided by Camelina Company Spain. The crop was sown at a rate of 8 kg ha−1 (R1), as recommended by the company, and at 11 kg ha−1 (R2) in the first two seasons, while after observing the results of the first two seasons, it was decided to sow the crop only at R1 in the third season. Three SD were chosen: Late October (SD1), according to the usual cereal SD in the area, early December (SD2), according to late sowing in the area, and January (SD3). These approximate SDs slightly varied depending on the climatic conditions. The exact SDs in each season are shown in Table 1. One to two days before each sowing, the soil was tilled to a depth of 10 cm to prepare it for sowing as well as for killing all emerged weeds.
Sowing was performed with a Plotseeder TC (Wintersteiger AG, Ried im Innkreis, Austria) in a randomized complete block design with three replicates. Plots were 1.5 m wide and 15 m long, with six rows per plot. Plots were neither irrigated nor fertilized, so that the only water and nutrient supply was each season’s precipitation and the previous crop’s residue (barley) (Hordeum vulgare L.).
2.3. Weed Sampling and Removing
On 3 March 2016, 21 March 2017, and 20 March 2018, weed species surveys were performed in five 0.25 m2 quadrats per plot and weed species and weed coverage (percentage of soil covered by weeds within the quadrat) were recorded. After the assessment, the weeds were removed by hand, so that no herbicide was applied in the plots. Those weeds emerging in autumn and winter were classified as winter (WW) and those emerging in spring were considered as summer weeds (SW). There were some species that typically emerged in late winter–early spring, and these were included in the WW group.
At the end of the season, harvest of the entire plots was performed with a Wintersteiger plot combine. The number of days from sowing to harvest was counted, as well as the growing degree days (GDD) using a base temperature (Tb) of −0.7 °C, which was found to be the mean Tb for germination for most camelina varieties [29].
2.4. Statistical Analysis
Results of weed coverage and yield were analyzed with a two-way analysis of variance (ANOVA) followed by a least significant difference (LSD) test, considering the sowing date and growing season as fixed factors, while replicate was considered as a random effect. For yield analysis, a two-way ANOVA was performed for the first and second season separately, with the sowing date and rate as fixed factors. Analysis between seasons was performed for only R1 with a two-way ANOVA, with the season and sowing date as fixed factors, followed by an LSD test. Data were square root transformed if necessary to satisfy the normality assumption. The analyses were performed with SPSS 15.0. (SPSS Inc, Chicago, IL, USA).
3. Results
3.1. Climatic Conditions
Overall temperatures from September to June were similar during the three growing seasons, being 15.9 °C in both 2015–2016 and 2016–2017 and 16 °C in 2017–2018. The only anomaly observed occurred in January 2018, which was warmer than December and February for that particular season (Figure 1). Similarly, total precipitation from September to June did not differ between seasons. The highest rainfall was recorded in 2015–2016 (288 mm), followed by 2017–2018 (278 mm) and 2016–2017 (270 mm). Despite this, the distribution of the precipitation throughout the growing season differed substantially from one season to the next and with the average historical values (Figure 1). Autumn 2015 was very dry, and the precipitation received in November mostly occurred in one day (70 mm), while the end of winter and spring (February through May) were wet. In 2016–2017, a wet autumn was followed by a dry winter and spring, except in March 2017, when over 80 mm of precipitation fell. In 2017–2018, there was severe drought in autumn, but after January, precipitation was evenly distributed throughout late winter and spring.
3.2. Crop Cycle
Camelina emerged soon after sowing, in 2 to 10 days depending on the soil moisture at each SD, and there were no noticeable changes in the crop density due to winter or drought losses. As explained in the Material and Methods, the three sowing dates each season were in October (SD1), December (SD2), and January (SD3) (Table 1). This affected the time required to reach crop maturity, which happened in all three seasons between 11 May and 20 June. Harvest was always two weeks earlier in SD1 than SD2 and SD3, and one to two months earlier than typical cereal harvest in the study area. Conversely, the crop cycle was always shorter for SD3 (123–150 days) than for SD2 (163–202 days) and SD1 (190–219 days). On average, SD3 required 45 and 71 fewer days to complete its life cycle than SD2 and SD1, respectively. In terms of GDD, SD1 needed between 1959 and 2653 GDD from sowing to harvest (Table 1), which was about 63–173 more GDD than that of SD2 each season. Compared to SD1 and 2, SD3 always required considerably less GDD to reach maturity, which ranged from 1720 to 2174 (Table 1).
3.3. Weed Species Number and Coverage
Due to the historical use of the field, several weed species which usually do not appear in winter cereal fields were recorded (Table 2, Table 3 and Table 4). Therefore, the analysis of number and coverage was done for the total of all the species and separately for the winter weed species.
The number and coverage of weeds, considering all species, was greater in SD1 than in SD2 and SD3 in 2015–2016 and 2017–2018, but not in 2016–2017 (Table 5). However, in 2016–2017, when winter/spring weeds were separated from summer ones, their coverage was also significantly greater in SD1 than in SD2 and SD3. No significant differences were detected in the number and coverage of weeds, either for total or winter weeds between R1 and R2 (2015–2016 and 2016–2017). With regard to the differences between seasons for R1, no differences were found for SD1, but the coverage in SD2 and SD3 was greater in 2016–2017 than in the other two seasons (Table 5).
The most abundant winter weed was Diplotaxis erucoides (L.) DC., also a member of the Brassicaceae, followed by Hordeum murinum L. in 2015–2016 (Table 2), then by Sisymbrium irio L. in 2016–2017 (Table 3), and Senecio vulgaris L. in 2017–2018 (Table 4). It should be noted that there was a presence of Kochia scoparia (L.) Schrad. and Polygonum aviculare L., which emerge in late winter and spring, and although they compete less with the crop, they can cause harvesting problems. Among the summer weed species, Chenopodium opulifolium Schrad. was the most abundant, mainly in 2016–2017, followed by Chenopodium. album L. and Convolvulus arvensis L.
3.4. Seed Yield Results
Seed yield of camelina highly depended on the climatic conditions each season (Table 6), but generally not on SD or R. In 2015–2016, significant differences were observed between SDs, but without any clear tendency. For instance, in R1, the highest yield was obtained in SD3, followed by SD1, while in R2, the highest yield was obtained in SD1, followed by SD3. In both cases, SD2 obtained the lowest yield. In 2016–2017, no differences were found among SD or between R, and in 2017–2018, there was no difference among SD. By contrast, significant differences were found between seasons across all SDs, obtaining the highest yield in 2017–2018, followed by 2016–2017 and 2015–2016.
4. Discussion
The hardiness of camelina to abiotic stresses, such as drought and low temperature, makes it a potential crop [11,12] for rotating with cereals, and thus, camelina may be highly beneficial for agricultural systems in semiarid climates, such as the Ebro Basin. Moreover, the high degree of weed suppression obtained in SD2 and SD3 with respect to SD1 in the present study indicates the potential of this crop to be used in organic farming.
In our work, weed coverage was effectively reduced with camelina SD, but no differences were observed with R. In R1, WW coverage was reduced by up to 99.6% in 2015–2016 by delaying the SD from late October (SD1) to December (SD2), while the reduction was 98% in 2017–2018 and 66% in 2016–2017. The delay of SD to January (SD3) did not significantly improve weed coverage reduction, which was of 99.2%, 70.4%, and 99% respectively for 2015–2016, 2016–2017, and 2017–2018. Most WW emerge from October to February, depending on the species and the season; thus, the greatest amount of these weeds was killed with the soil tillage for late SDs. Although the WW species were not the most problematic in the area (Avena sterilis and Bromus diandrus were lacking, while Lolium rigidum and Papaver rhoeas were scarcely represented), the presence of mainly D. erucoides, as well as S. irio and Hordeum murinum could be representative of a WW community, giving validity to the obtained results. Similarly, Garcia et al. [30] also obtained 80–99% weed control with SD from October to December in B. diandrus in the same area. In our conditions, these control levels would have been 0.0–79.4% in SD1, 9.1–37.7% in SD2, and 12.9–81.9% in SD3, depending on the season. Other emergence models already published for A. sterilis [31], L. rigidum [32], and P. rhoeas [33] indicate the usefulness of the SD in the control of the most important weeds in this area: In our climatic conditions, up to 83.9%, 46.9%, and 6.9% of A. sterilis., L. rigidum., and P. rhoeas emergences would have been killed by SD1, while these values would go up to 86.2%, 62.4%, and 17.8% respectively in SD2, and up to 91.9%, 77.7%, and 42.3% in SD3. Moreover, the competitive capacity of camelina, which was not studied in this work, is likely to have contributed to weed suppression. For this reason, camelina can be a good option to alternate with cereals, but this depends on the annual climatic conditions that highly affect the emergence of these weeds.
Not only did delaying SD contribute to the control of weeds, but it also delayed the harvest date. In our experiment, harvest was done between 11 May and 6 June for SD1 and between 25 May and 20 June for SD2 and SD3 (Table 1). These time laps from sowing to harvest (120–220 days) are similar to those obtained by Berti et al. [21] in Chile for autumn–winter sown camelina. Weeds are adapted to the cereal cycle, and most of them release seeds at harvest [34]. This happens in the Ebro Basin from mid-June to July. Therefore, hastening the harvest of camelina by one month to mid-May would prevent weed seeds from maturing, thus avoiding the seed rain that contributes to the management of the seed bank. In this respect, camelina’s short life cycle coincides with that obtained by Gutiérrez and Albalat [24] for SD1, while it was considerably shortened in SD2 and especially in SD3, in the present study.
Contrary to Berti et al. [21], in the present study no significant yield loss was suffered by delaying the sowing date to SD2 or SD3 in any season. The differences with respect to Berti et al. [21] could be partly explained by the climatic differences between the Chilean sites and Lleida Spain. Both winter (Dec–Feb/Jun–Aug) temperatures (6.7 °C < 7.3–8.8 °C) and rainfall (54 mm < 472–747 mm) were lower in Lleida, which could have slowed down the growth of SD1 and SD2, while in Chile the early SD could take advantage of the milder and wetter winter compared with the late SD. There was only some irregular yield in 2015–2016 between SDs. Rainfall in November 2015 was 71 mm, but 70 mm fell in only one day (with a lot of runoff), almost one month before SD2, followed by a December and January that were very dry. This could have contributed to the low yields obtained in SD2 that season. However, this reason does not fully explain yield results in SD2. The lowest yields in 2015–2016 were similar to those obtained by Gutiérrez and Albalat [24] in the nearby county of Aragon, or those by Gesch & Archer [18] and Obour et al. [35] (0.5 Mg ha−1), while others approximated more to French et al. [36] (1Tn ha−1), or even to McVay and Khan [19] and Obour et al. [35] (1.5 Mg ha−1), as yields of 2016–2017. Meanwhile, yields from 2017–2018 were more like those from Gesch [25] (2.3 Mg ha−1) or Zubr [37], who obtained yields of 2.6 to 3.3 Mg ha−1 in Denmark. These differences in yield between seasons are the usual ones for a semiarid region, where climatic conditions can easily vary the productivity of the crop from one season to the next [38], like in barley [39].
In this study, seed oil content was not analyzed. Sowing date 1 plants matured before SD2 and SD3, which means that the climatic conditions for the seed maturation process were different between SDs. This could have affected oilseed quality. Gesch et al. [40] observed higher seed mass, oil content, total carbon, and unsaturated fatty acid content for Thlaspi arvense seeds produced in Spain than in Minnesota, and Pavlista et al. [26] also found differences in oil content and quality in spring camelina, being the highest when sown in April. Whether this also happens in our conditions and how autumn–winter SD affects camelina seed oil content will require further study.
The lack of yield differences between SDs is a great advantage, because, depending on the climatic conditions of each season, mainly precipitation, weeds can significantly vary their emergence period. The flexibility of sowing of camelina without a yield penalty can be used as a strategy to contribute to better weed control. This sowing flexibility also allows for a wider window of opportunity to make decisions. Despite this, some productivity decreases have been reported [35] in winter wheat the following season when it follows camelina in rotation. This aspect should also be studied to better understand this issue.
5. Conclusions
Camelina presents clear favorable characteristics to be implemented in rotation with winter cereals. Its tolerance to abiotic stresses, low fertility requirement, and its short life cycle make it a good option for obtaining effective coverage reduction over winter weeds. Moreover, apparently, no yield penalties occur, thus providing farmers income, in contrast to fallow lands. However, all these results have been obtained in an experimental field and, although there are many studies confirming their validity, new experiments in commercial fields could help to strengthen the results and contribute to the integration of this useful crop in rotation in agricultural systems in Mediterranean semiarid regions.
Author Contributions
For this research both authors contributed in the following aspects: Conceptualization, A.R.-E.; Methodology, A.R.-E.; Formal Analysis, A.R.-E. and F.V.-G.; Investigation, A.R.-E. and F.V.-G.; Resources, A.R.-E.; Data Curation, A.R.-E. and F.V.-G.; Writing-Original Draft Preparation, A.R.-E.; Writing-Review & Editing, A.R.-E., Francisco Valencia-Gredilla and F.V.-G.
Funding
This research received no external funding.
Acknowledgments
We would like to thank the technicians that have participated in the sowing and harvest (Carlos Cortés, Joana Serrano), and in the hand weeding and data collection (Maria Casamitjana, Berta Singla, Neus Mas). We want to especially thank Russell W Gesch for his useful suggestions and manuscript editing. We also thank Camelina Company Spain for providing the seeds of camelina that have been used in this work.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Liebman, M.; Dyck, E. Crop rotation and intercropping strategies for weed management. Ecol. Appl. 1993, 3, 92–122. [Google Scholar] [CrossRef] [PubMed]
- Anderson, R.L. Improving resource-use-efficiency with no-till and crop diversity. Renew. Agric. Food Syst. 2017, 32, 105–108. [Google Scholar] [CrossRef]
- Rey-Caballero, J.; Royo-Esnal, A.; Recasens, J.; González, I.; Torra, J. Management options for multiple herbicide-resistant corn poppy (Papaver rhoeas) in Spain. Weed Sci. 2017, 65, 295–304. [Google Scholar] [CrossRef]
- Torra, J.; Royo-Esnal, A.; Rey-Caballero, J.; Recasens, J.; Salas, M.L. Management of Herbicide-Resistant Corn Poppy (Papaver rhoeas) under Different Tillage Systems Does Not Change the Frequency of Resistant Plants. Weed Sci. 2018. [Google Scholar] [CrossRef]
- Agencia Estatal de Meteorología (AEMET). Ministerio para la Transición Ecológica. Gobierno de España. Available online: www.aemet.es/es/serviciosclimaticos/datosclimatologicos/valoresclimatologicos (accessed on 2 July 2018).
- Abalos, D.; Sanz-Cobena, A.; Andreu, G.; Vallejo, A. Rainfall amount and distribution regulate DMPP effects on nitrous oxide emissions under semiarid Mediterranean conditions. Agric. Ecosyst. Environ. 2017, 238, 36–45. [Google Scholar] [CrossRef]
- García-Garizábal, I.; Causapé, J.; Abrahao, R.; Merchan, D. Impact of climate change on Mediterranean irrigation demand: Historical dynamics of climate and future projections. Water Resour. Manag. 2014, 28, 1449–1462. [Google Scholar]
- Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA). MAGRAMA Stat Database. Available online: http://www.magrama.gob.es/estadistica/temas/publicaciones/anuario-de-estadistica/ (accessed on 27 September 2014).
- Karg, S. Oil-rich seeds from prehistoric contexts in southern Scandinavia—Reflections on archaeobotanical records of flax, hemp, gold of pleasure, and corn spurrey. Acta Palaebot. 2012, 52, 17–24. [Google Scholar]
- Larsson, M. Cultivation and processing of Linum usitatissimum and Camelina sativa in southern Scandinavia during the Roman Iron Age. Veg. Hist. Archaeobot. 2013, 22, 509–520. [Google Scholar] [CrossRef]
- Zanetti, F.; Eynck, C.; Christou, M.; Kryzaniak, M.; Righini, D.; Alexopoulou, E.; Stolarski, M.J.; Van Loo, E.N.; Puttick, D.; Monti, A. Agronomic performance and seed quality attirbutes of Camelina (Camelina sativa L. cranzt) in multi-environment trials across Europe and Canada. Ind. Crops Prod. 2017, 107, 602–608. [Google Scholar] [CrossRef]
- Berti, M.; Gesch, R.W.; Eynck, C.; Anderson, J.; Cermak, S. Camelina uses, genetics, genomics, production, and management. Ind. Crops Prod. 2016, 94, 690–710. [Google Scholar] [CrossRef]
- Drenth, A.; Olsen, D.; Cabot, P.; Johnson, J. Fuel property quantification of triglyceride blends with an emphasis on industrial oilseeds camelina, carinata, and pennycress. Fuel 2015, 153, 19–30. [Google Scholar] [CrossRef]
- Yang, J.; Caldwell, C.; Corscadden, K.; He, Q.S.; Li, J. An evaluation of biodiesel production from Camelina sativa grown in Nova Scotia. Ind. Crops Prod. 2016, 81, 162–168. [Google Scholar] [CrossRef]
- Crowley, J.G. Evaluation of Camelina Sativa as an Alternative Crop; Technical Report for Teagasc; Teagasc: Dublin, Ireland, 1999. [Google Scholar]
- Zubr, J.; Matthäus, B. Effects of growth conditions on fatty acids and tocopherols in Camelina sativa oil. Ind. Crops Prod. 2002, 15, 155–162. [Google Scholar] [CrossRef]
- Zubr, J. Carbohydrates, vitamins and minerals of Camelina sativa seed. Nutr. Food Sci. 2010, 40, 523–531. [Google Scholar] [CrossRef]
- Gesch, R.W.; Archer, D.W. Double cropping with winter Camelina in the northern Corn belt to produce fuel and food. Ind. Crops Prod. 2013, 44, 718–725. [Google Scholar] [CrossRef]
- McVay, K.A.; Khan, Q.A. Camelina yield response to different plant populations under dryland conditions. Agron. J. 2011, 103, 1265–1269. [Google Scholar] [CrossRef]
- Urbaniak, S.D.; Caldwell, C.D.; Zheljazkov, V.D.; Lada, R.; Luan, L. The effect of seeding rate, seeding date and seeder type on the performance of Camelina sativa L. in the Maritime Provinces of Canada. Can. J. Plant Sci. 2008, 88, 501–508. [Google Scholar] [CrossRef]
- Berti, M.; Wilckens, R.; Fischer, S.; Solis, A.; Johnson, B. Seeding date influence on camelina seed yield, yield components, and oil content in Chile. Ind. Crops Prod. 2011, 34, 1358–1365. [Google Scholar] [CrossRef]
- Robinson, R. Camelina: A Useful Research Crop and a Potential Oilseed Crop; Bulletin for Minnesota Agricultural Experiment Station: St Paul, MN, USA, 1987; pp. 1–12. [Google Scholar]
- Angelini, L.G.; Moscheni, E.; Colonna, G.; Belloni, P.; Bonari, E. Variation in agronomic characteristics and seed oil composition of new oilseed crops in Central Italy. Ind. Crops Prod. 1997, 6, 313–323. [Google Scholar] [CrossRef]
- Gutiérrez, M.; Albalat, A. El Cultivo de la Camelina en Aragón; Technical Report for Servicio de Recursos Agrícolas; Gobierno de Aragón: Zaragoza, Spain, 2013. [Google Scholar]
- Gesch, R.W. Influence of genotype and sowing date on camelina growth and yield in the north central US. Ind. Crops Prod. 2014, 54, 209–215. [Google Scholar] [CrossRef]
- Pavlista, A.D.; Isbell, T.A.; Baltensperger, D.D.; Hergert, G.W. Planting date and development of spring-seeded irrigated canola, brown mustard and camelina. Ind. Crops Prod. 2011, 33, 451–456. [Google Scholar] [CrossRef]
- Schillinger, W.F.; Wysocki, D.J.; Chastain, T.G.; Guy, S.O.; Karow, R.S. Camelina: Planting date and method effects on stand establishment and seed yield. Field Crops Res. 2012, 130, 138–144. [Google Scholar] [CrossRef] [Green Version]
- Rivas-Martinez, S.; Rivas-Saenz, S. Worldwide Bioclimatic Classification System, 1996–2018. Phytosociological Research Center, Spain. Available online: http://www.globalbioclimatics.org/ (accessed on 2 July 2018).
- Allen, B.L.; Vigil, M.F.; Jabro, J.D. Camelina growing degree hour and base temperature requirements. Agron. J. 2014, 106, 940–944. [Google Scholar] [CrossRef]
- García, A.L.; Royo-Esnal, A.; Torra, J.; Cantero-Martínez, C.; Recasens, J. Integrated management of Bromus diandrus in dry land cereal fields under no-till. Weed Res. 2014, 54, 408–417. [Google Scholar]
- Leguizamón, E.S.; Fernández-Quintanilla, C.; Barroso, J.; González-Andújar, J.L. Using termal and hydrothermal time to model seedling emergence of Avena sterilis subsp. ludoviciana in Spain. Weed Res. 2005, 45, 149–156. [Google Scholar]
- Izquierdo, J.; Bastida, F.; Lezáun, J.A.; Sánchez del Arco, M.J.; González-Andújar, J.L. Development and evaluation of a model for predicting Lolium rigidum emergence in winter cereal crops in the Mediterranean area. Weed Res. 2013, 53, 269–278. [Google Scholar] [CrossRef]
- Izquierdo, J.; González-Andújar, J.L.; Bastida, F.; Lezáun, J.A.; Sánchez del Arco, M.J. A thermal time model to predict corn poppy (Papaver rhoeas) emergence in cereal fields. Weed Sci. 2009, 57, 660–664. [Google Scholar] [CrossRef]
- Westerman, P.R.; Atanackovic, V.; Royo-Esnal, A.; Torra, J. Differential weed seed removal in dryland cereals. Arthropod-Plant Interact. 2012, 6, 591–599. [Google Scholar] [CrossRef]
- Obour, A.K.; Chen, C.; Sintim, A.Y.; McVay, K.; Lamb, P.; Obeng, E.; Mohammed, Y.A.; Khan, Q.; Afshar, R.K.; Zheljazkov, V.D. Camelina sativa as fallow replacement crop in wheat–based crop production systems in the US Great Plains. Ind. Crops Prod. 2018, 111, 22–29. [Google Scholar] [CrossRef]
- French, A.N.; Hunsaker, D.; Thorp, K.; Clarke, T. Evapotranspiration over a Camelina crop at Maricopa, Arizona. Ind. Crops Prod. 2009, 29, 289–300. [Google Scholar] [CrossRef]
- Zubr, J. Oil-seed crop: Camelina sativa. Ind. Crops Prod. 1997, 6, 113–119. [Google Scholar] [CrossRef]
- Fernández-Getino, A.P.; Santín-Montanyá, M.I.; Zambrana, E.; De Andrés, E.F.; Tenorio, J.L. The response of barley to rainfall and temperature in different tillage and crop rotation systems in semi-arid conditions. Ann. Appl. Biol. 2015, 166, 143–153. [Google Scholar] [CrossRef]
- Morell, F.J.; Lampurlanés, J.; Álvaro-Fuentes, J.; Cantero-Martínez, C. Yield and water use efficiency of barley in a semiarid Mediterranean agroecosystem: Long-term effects of tillage and N fertilization. Soil Tillage Res. 2011, 117, 76–89. [Google Scholar] [CrossRef] [Green Version]
- Gesch, R.W.; Royo-Esnal, A.; Edo-Tena, E.; Recasens, J.; Isbell, T.; Forcella, F. Growth environment but not seed position on the parent plant affect seed germination of two Thlaspi arvense L. populations. Ind. Crops Prod. 2016, 84, 241–247. [Google Scholar] [CrossRef]
Figure 1.
Climatic conditions for each of the three growing seasons (2015–2016, 2016–2017, and 2017–2018), from sowing (September) to harvest (June). The black line indicates the mean monthly temperature (Tm) and the grey bars show total precipitation (P) in each month. The last graph (right) corresponds to monthly average temperatures and precipitations for the period 1983–2010 (AEMET).
Figure 1.
Climatic conditions for each of the three growing seasons (2015–2016, 2016–2017, and 2017–2018), from sowing (September) to harvest (June). The black line indicates the mean monthly temperature (Tm) and the grey bars show total precipitation (P) in each month. The last graph (right) corresponds to monthly average temperatures and precipitations for the period 1983–2010 (AEMET).
Table 1.
Calendar dates and the number of days (N) and growing degree days (GDD) from sowing to harvest for the first, second, and third sowing date in October, December, and January. Tb for GDD estimation was considered at −0.7 °C [29].
Table 1.
Calendar dates and the number of days (N) and growing degree days (GDD) from sowing to harvest for the first, second, and third sowing date in October, December, and January. Tb for GDD estimation was considered at −0.7 °C [29].
| Year | Sowing | Harvest | N | GDD |
|---|---|---|---|---|
| SD1 | ||||
| 2015–2016 | 29 Oct 15 | 06 June 16 | 221 | 2653 |
| 2016–2017 | 02 Nov 16 | 11 May 17 | 190 | 1959 |
| 2017–2018 | 15 Oct 17 | 22 May 18 | 219 | 2319 |
| SD2 | ||||
| 2015–2016 | 01 Dec 15 | 20 June 16 | 202 | 2575 |
| 2016–2017 | 13 Dec 16 | 25 May 17 | 163 | 1897 |
| 2017–2018 | 04 Dec 17 | 08 June 18 | 186 | 2146 |
| SD3 | ||||
| 2015–2016 | 22 Jan 16 | 20 June 16 | 150 | 2174 |
| 2016–2017 | 22 Jan 17 | 25 May 17 | 123 | 1720 |
| 2017–2018 | 16 Jan 18 | 08 June 18 | 143 | 1889 |
Table 2.
Weed coverage (%) by species in 2015–2016 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing dose of 8 kg/ha; R2, sowing dose of 11 kg/ha.
Table 2.
Weed coverage (%) by species in 2015–2016 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing dose of 8 kg/ha; R2, sowing dose of 11 kg/ha.
| Weed Species | 2015–2016 | |||||||
|---|---|---|---|---|---|---|---|---|
| SD1R1 | SD2R1 | SD3R1 | SD1R2 | SD2R2 | SD3R2 | |||
| 1 | Capsella bursa–pastoris (L.) Medicus | WW | 3 | |||||
| 2 | Chenopodium album L. | SW | 0.10 | 0.03 | 0.37 | |||
| 3 | Chenopodium opulifolium Schrad. | SW | 1.20 | 0.02 | 0.10 | 0.05 | ||
| 4 | Convolvulus arvensis L. | SW | 0.30 | |||||
| 5 | Diplotaxis erucoides (L.) DC. | WW | 17.50 | 0.10 | 0.08 | 21.20 | 0.14 | |
| 6 | Euphorbia helioscopia L. | WW | 0.30 | |||||
| 7 | Fumaria officinalis L. | WW | 0.06 | 2 | ||||
| 8 | Geranium molle L. | WW | 0.10 | |||||
| 9 | Hordeum murinum L. | WW | 4.90 | 5.80 | 0.20 | |||
| 10 | Kochia scoparia (L.) Schrad. | WW | 0.10 | 0.02 | 0.02 | 0.08 | ||
| 11 | Lactuca serriola L. | WW | 0.30 | |||||
| 12 | Lolium rigidum Gaudin | WW | 0.30 | |||||
| 13 | Polygonum aviculare L. | WW | 0.08 | |||||
| 14 | Rumex obtusifolius L. | SW | 0.10 | |||||
| 15 | Scorzonera laciniata L. | WW | 0.20 | |||||
| 16 | Senecio vulgaris L. | WW | 0.40 | 0.20 | ||||
| 17 | Sonchus oleraceus L. | WW | 0.50 | 0.37 | ||||
| 18 | Trifolium repens L. | WW | 0.20 | |||||
Table 3.
Weed coverage (%) by species in 2016–2017 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing dose of 8 kg/ha; R2, sowing dose of 11 kg/ha.
Table 3.
Weed coverage (%) by species in 2016–2017 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing dose of 8 kg/ha; R2, sowing dose of 11 kg/ha.
| Weed Species | 2016–2017 | ||||||
|---|---|---|---|---|---|---|---|
| SD1R1 | SD2R1 | SD3R1 | SD1R2 | SD2R2 | SD3R2 | ||
| 1 | Capsella bursa–pastoris (L.) Medicus | 0.83 | 0.15 | 0.11 | 0.77 | 0.57 | 0.05 |
| 2 | Chenopodium album L. | 1.97 | 2.89 | 0.03 | 0.12 | 0.21 | |
| 3 | Chenopodium opulifolium Schrad. | 0.19 | 4.47 | 7.69 | 0.23 | 22.54 | 9.76 |
| 4 | Convolvulus arvensis L. | 0.01 | 0.02 | 0.02 | 0.01 | ||
| 5 | Diplotaxis erucoides (L.) DC. | 8.1 | 1.98 | 2.63 | 5.60 | 1.17 | 0.89 |
| 6 | Euphorbia peplus L. | 0.02 | |||||
| 7 | Fumaria capreolata L. | 0.27 | |||||
| 8 | Fumaria officinalis L. | 0.28 | 0.02 | ||||
| 9 | Kochia scoparia (L.) Schrad. | 0.02 | 0.88 | 0.19 | 0.02 | 0.88 | 0.40 |
| 10 | Lactuca serriola L. | 0.07 | 0.01 | 0.01 | 0.01 | ||
| 11 | Malva sylvestris L. | 0.07 | |||||
| 12 | Papaver rhoeas L. | 0.87 | 0.07 | 0.2 | |||
| 13 | Polygonum aviculare L. | 0.07 | 0.23 | 0.2 | |||
| 14 | Scorzonera laciniata L. | ||||||
| 15 | Senecio vulgaris L. | 0.13 | |||||
| 16 | Rumex obtusifolius L. | 0.07 | 0.01 | ||||
| 17 | Sonchus oleraceus L. | 0.20 | 0.02 | 0.02 | 0.05 | 0.01 | |
| 18 | Sisymbrium crassifolium Cav. | 0.47 | 0.33 | 0.33 | |||
| 19 | Sisymbrium irio L. | 0.67 | 0.07 | 0.43 | 3.80 | 0.51 | 0.58 |
| 20 | Xanthium spinosum L. | 0.01 | |||||
Table 4.
Weed coverage (%) by species in 2016–2017 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January.
Table 4.
Weed coverage (%) by species in 2016–2017 for each sowing date and sowing density. SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January.
| Weed Species | 2017–2018 | |||
|---|---|---|---|---|
| SD1R1 | SD2R1 | SD3R1 | ||
| 1 | Chenopodium album L. | 0.04 | 0.05 | 0.07 |
| 2 | Convolvulus arvensis L. | 0.58 | 0.30 | 0.12 |
| 3 | Diplotaxis erucoides (L.) DC. | 8.97 | 0.06 | 0.01 |
| 4 | Fumaria capreolata L. | 0.05 | ||
| 5 | Fumaria officinalis L. | 0.01 | ||
| 6 | Kochia scoparia (L.) Schrad. | 0.01 | 0.01 | 0.01 |
| 7 | Lactuca serriola L. | 0.01 | 0.01 | |
| 8 | Lolium rigidum Gaudin | 0.01 | ||
| 9 | Papaver rhoeas L. | 0.01 | ||
| 10 | Polygonum aviculare L. | 0.06 | 0.09 | 0.03 |
| 11 | Senecio vulgaris L. | 0.43 | 0.02 | |
| 12 | Sonchus oleraceus L. | 0.68 | ||
| 13 | Veronica hederifolia L. | 0.06 | 0.01 | |
| 14 | Veronica persica Poir. | 0.03 | ||
| 15 | Xanthium spinosum L. | 0.01 | ||
Table 5.
Number and coverage for all weed species and separately for winter weeds (WW) and summer weeds (SW). Results of two-way ANOVA + LSD are provided for total weed coverage and WW coverage: Low case letters, comparisons between sowing dates and sowing densities within seasons (in 2017–2018 only sowing dates); capital letters, comparison between seasons for each sowing date within R1.
Table 5.
Number and coverage for all weed species and separately for winter weeds (WW) and summer weeds (SW). Results of two-way ANOVA + LSD are provided for total weed coverage and WW coverage: Low case letters, comparisons between sowing dates and sowing densities within seasons (in 2017–2018 only sowing dates); capital letters, comparison between seasons for each sowing date within R1.
| Number and Coverage of Weed Species | 2015–2016 | |||||
|---|---|---|---|---|---|---|
| SD1R1 | SD2R1 | SD3R1 | SD1R2 | SD2R2 | SD3R2 | |
| Total weed species | 13 | 3 | 4 | 8 | 3 | 4 |
| Total weed coverage | 26.1 aA | 0.2 cC | 0.5 bB | 33.0 a | 0.3 c | 0.4 b |
| Number WW/SpW | 9 | 1 | 2 | 8 | 2 | 3 |
| WW/SpW coverage | 24.4 aA | 0.1 bB | 0.2 bB | 33.0 a | 0.2 b | 0.3 b |
| Number SW | 4 | 2 | 2 | 0 | 1 | 1 |
| SW coverage | 1.7 | 0.1 | 0.4 | 0.0 | 0.1 | 0.1 |
| 2016–2017 | ||||||
| Total weed species | 12 | 13 | 9 | 10 | 12 | 10 |
| Total weed coverage | 11.6 aA | 10.3 aA | 14.1 aA | 11.0 a | 26.4 a | 12.1 a |
| Number WW/SpW | 10 | 10 | 6 | 7 | 7 | 8 |
| WW/ SpW coverage | 11.5 aA | 3.9 bA | 3.4 bA | 10.7 a | 3.5 b | 2.0 b |
| Number SW | 2 | 3 | 3 | 3 | 5 | 2 |
| SW coverage | 0.2 | 6.5 | 10.6 | 0.3 | 22.7 | 10.1 |
| 2017–2018 | ||||||
| Total weed species | 8 | 9 | 11 | |||
| Total weed coverage | 10.8 aA | 0.6 bB | 0.3 bB | |||
| Number WW/SpW | 6 | 7 | 8 | |||
| WW/ SpW coverage | 10.1 aA | 0.2 bB | 0.1 bC | |||
| Number SW | 2 | 2 | 3 | |||
| SW coverage | 0.6 | 0.4 | 0.2 | |||
Different letters show significances at p < 0.05.
Table 6.
Seed yield (kg ha−1) results (+SE) for each sowing date (SD) and rate (R) in each season (Y). SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing rate of 8 kg ha−1; R2, sowing rate of 11 kg ha−1. The comparisons between SDs and R are shown for 2015–2016 and 2016–2017 (lower rows), as well as the comparison between Y and SD for R1 (last columns).
Table 6.
Seed yield (kg ha−1) results (+SE) for each sowing date (SD) and rate (R) in each season (Y). SD1, first sowing date in late October; SD2, second sowing date in December; SD3, third sowing date in January. R1, sowing rate of 8 kg ha−1; R2, sowing rate of 11 kg ha−1. The comparisons between SDs and R are shown for 2015–2016 and 2016–2017 (lower rows), as well as the comparison between Y and SD for R1 (last columns).
| Seed Yield Results | 2015–2016 | 2016–2017 | 2017–2018 | ||||
|---|---|---|---|---|---|---|---|
| R1 | R2 | R1 | R2 | R1 | |||
| SD1 | 766 ± 210 | 1026 ± 262 | 1768 ± 250 | 1476 ± 186 | 2369 ± 136 | Y | p ≤ 0.001 |
| SD2 | 598 ± 133 | 557 ± 131 | 1374 ± 95 | 1941 ± 320 | 2426 ± 163 | SD | p = 0.451 |
| SD3 | 1382 ± 135 | 950 ± 163 | 1473 ± 183 | 1482 ± 153 | 2135 ± 242 | Y × SD | p = 0.082 |
| SD | p = 0.032 | p = 0.939 | |||||
| R | p = 0.662 | p = 0.378 | |||||
| SD × R | p = 0.240 | p = 0.827 | |||||
© 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Royo-Esnal, A.; Valencia-Gredilla, F. Camelina as a Rotation Crop for Weed Control in Organic Farming in a Semiarid Mediterranean Climate. Agriculture 2018, 8, 156. https://doi.org/10.3390/agriculture8100156
AMA Style
Royo-Esnal A, Valencia-Gredilla F. Camelina as a Rotation Crop for Weed Control in Organic Farming in a Semiarid Mediterranean Climate. Agriculture. 2018; 8(10):156. https://doi.org/10.3390/agriculture8100156
Chicago/Turabian StyleRoyo-Esnal, Aritz, and Francisco Valencia-Gredilla. 2018. "Camelina as a Rotation Crop for Weed Control in Organic Farming in a Semiarid Mediterranean Climate" Agriculture 8, no. 10: 156. https://doi.org/10.3390/agriculture8100156
APA StyleRoyo-Esnal, A., & Valencia-Gredilla, F. (2018). Camelina as a Rotation Crop for Weed Control in Organic Farming in a Semiarid Mediterranean Climate. Agriculture, 8(10), 156. https://doi.org/10.3390/agriculture8100156
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
