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Article

Growing Triticum aestivum Landraces in Rotation with Lupinus albus and Fallow Reduces Soil Depletion and Minimises the Use of Chemical Fertilisers

by
Fernando Almeida-García
1,*,
Sara Lago-Olveira
2,
Ricardo Rebolledo-Leiva
2,
Sara González-García
2,
María Teresa Moreira
2,
Benigno Ruíz-Nogueiras
1 and
Santiago Pereira-Lorenzo
1
1
Department of Crop Production and Engineering Projects, High Polytechnich School of Engineering, Universidade de Santiago de Compostela, 27002 Lugo, Spain
2
CRETUS Institute, Department of Chemical Engineering, School of Engineering, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(7), 905; https://doi.org/10.3390/agriculture12070905
Submission received: 1 June 2022 / Revised: 15 June 2022 / Accepted: 20 June 2022 / Published: 22 June 2022
(This article belongs to the Section Agricultural Systems and Management)
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Abstract

:
In north-western Spain, the cultivation of wheat landraces represents the pillar of quality Galician bread; today, a minimum of 25% Galician flour is required to produce bread under the auspices of the Protected Geographical Indication “Pan Galego”. The main objective of this study was to evaluate the effect of the rotation of two wheat landraces—‘Carral’ and ‘Caaveiro’—with lupin (sweet Lupinus albus), together with a fallow period, on crop yield and quality, as well as the environmental benefits of rotations over conventional monoculture systems. After the different agricultural activities, twelve agronomic parameters were analysed at the end of the third year. For the environmental analysis, the Life Cycle Assessment methodology was applied. The results showed a positive influence of rotation systems on wheat yield and quality parameters, reporting higher specific weight and lower impurities compared to monoculture. No significant differences were observed between wheat rotation and monoculture in other parameters related to baking quality, such as protein, wet gluten, baking strength (W), elasticity (L), tenacity (P), and swelling (G). However, soil quality influenced wheat quality independently of rotation, and higher organic matter and lower phosphorus produced higher W and P, respectively. Moreover, rotation had a positive effect on yield, up to 62% when fallow preceded wheat, and in reducing diseases, pests, and weeds. Finally, in terms of environmental performance, the best results were identified when lupin preceded wheat due to lower fertiliser application. In this regard, the worst profiles corresponded to the scenarios based on monoculture for both wheat landraces.

1. Introduction

Wheat (Triticum aestivum L.), along with maize and rice, is at the base of the food pyramid. With a total production of 762 million tonnes, it is the second most cultivated cereal in the world after maize (International Cereal Council 2020). In Galicia, the cultivation of native varieties has been characterised by their better adaptation to the physical environment and lower input conditions [1]. The recent Protected Geographical Indication “Pan Gallego” is consolidated as a value-added quality brand and establishes as a requirement a minimum percentage of 25% for indigenous varieties of wheat to produce Galician bread, with ‘Caaveiro’ as one of the two registered crops [2]. The main characteristics of ‘Caaveiro’ are its long stalks and great rusticity, which implies that the variety is not very demanding in terms of growing conditions (nutrients, soil type, and water demand). It is also very competitive with weeds and has good organoleptic qualities for producing Galician bread, although it is less productive than commercial cultivars.
The practice of crop rotation dates back to the very origins of agriculture. However, with the agricultural intensification of recent decades [3], the monoculture system has spread. The rotation of cereal crops with other crops, such as rapeseed or legumes, helps the cereal to grow in an environment with lower levels of weeds and diseases [4], which implies the interruption of pathogen cycles [5]. In addition, fungal diseases directly affect cereal quality parameters such as specific gravity and 1000-grain weight. Therefore, with rotation, these quality parameters are also improved in contrast to monoculture. Wheat monoculture increases the percentage of impurities due to the presence of seeds from adventitious plants in the harvested product. Crop rotations of barley, maize, and sugar beet reduced the total number of weed seeds by 96.4% after 6 years of crop management (two rotation cycles) [6]. Legumes, such as sweet lupin (Lupinus albus), can fix nitrogen from the air through symbiosis with Rhizobium [7]. In cereal rotations with legumes, cereal yields tend to increase when preceded by legumes, reaching increases of around 50% compared to monoculture [8]. In particular, wheat rotations with lupins increased yields on culture by more than 40% [9].
Fallowing is an agricultural practice that originated in the Middle Ages. It consists of a short annual fallow to control weeds, pests, and diseases and to promote the mineralisation of organic matter [10]. On the other hand, grain quality and yield are often negatively correlated. In this regard, the “protein dilution” effect is known. This often occurs under conditions of high productivity and limited nitrogen availability that do not allow the wheat plant to store an adequate amount of protein in the grain [11].
On the other hand, how the cereal cropping strategy influences greenhouse gas (GHG) emissions and water pollution has to be taken into account [12]. According to the new Common Agricultural Policy (CAP), improvements in agriculture are needed to achieve more sustainable practices [13]. In this respect, the introduction of legumes and fallow periods in cereal-dominated crop rotations brings important environmental benefits [14,15,16]. These rotations contribute to enriching food sources for pollinators [17] and reducing nitrate leaching [18], as well as improving phosphorus availability [19] and water retention [20].
To analyse the environmental consequences of agricultural practices, special attention is given to the Life Cycle Assessment (LCA) methodology. Many studies have adopted the LCA methodology to evaluate agricultural systems from an environmental point of view [21,22,23,24]. This tool makes it possible to quantify and compare the environmental impacts of agricultural systems throughout their life cycle, as well as to identify the hotspots within them. This study had a two-fold objective: (1) to analyse the effects of introducing lupine and fallow in triennial rotation with wheat in terms of yield and quality, and (2) to demonstrate the environmental benefits of agricultural systems that include legumes and fallow compared to wheat monoculture from an LCA approach. The introduction of sweet lupine and fallow in triennial rotation with wheat landraces improved the yield and quality of cereals while reducing the environmental impact of monoculture wheat.

2. Materials and Methods

2.1. Materials

A randomised complete block design with four replications was used for three types of crop rotations with local wheat (‘Caaveiro’ and an ecotype from the Carral region, A Coruña), which were (Figure 1) as follows: A, fallow (F) (Year 1), lupine (L) (Year 2), and Carral ecotype of wheat (WEcot) (Year 3); B, lupine (Year 1), fallow (Year 2), and Carral ecotype of wheat (WCaav) (Year 3); C, Carral ecotype of wheat monoculture; D, fallow (Year 1), lupine (Year 2), and ‘Caaveiro’ wheat (Year 3); E, lupine (Year 1), fallow (Year 2), and ‘Caaveiro’ wheat (Year 3); and F, ‘Caaveiro’ wheat monoculture.
The trial was in northwestern Spain (43°15′20″ N, 8°21′18″ W) and had a total of 24 subplots (6 per repetition). Each subplot was 6 × 14 m2 with repetitions separated by corridors to allow manoeuvring. The following management was implemented during the 3 years:
Year 1: A mould-board plough incorporated 500 kg ha−1 of mineral complex (9-18-27) as background fertiliser—sowing (not in the fallow plots) was performed with a combined rototiller and seeder implement. The herbicidal pre-emergence treatment for all subplots was diflufenican 50% (250 mL) + pendimethalin 33% (4 l ha−1). For harvesting, a self-propelled harvesting machine was used. The sowing date for lupine and wheat was 2 October 2017.
Year 2: The same as Year 1 but without fertiliser. The sowing date for lupine and wheat was 15 October 2018.
Year 3: All plots were planted with wheat. A mould-board plough incorporated 300 kg ha−1 of mineral complex 8-15-15 as background fertiliser, sowing with a combined rototiller and seeder implement. Post-emergence herbicidal treatment was on 21 November 2019: 0.6% sodium iodosulfuron methyl + 3% methyl mesosulfuron (400 g ha−1). For harvesting, a self-propelled harvesting machine was used. The sowing date was 24 October 2019.
The following characteristics of the wheat were evaluated at harvest in the third year: grain yield (GY, kg ha−1); humidity of the seeds (H, %) and hectolitre weight (HW, kg 100 L−1), using a certified high frequency meter; weight of one thousand seeds (WTS, g), with a seed counter and precision scale; protein (%), with near-infrared (NIR) analyser; wet gluten (%), GlutenMatik system; and impurities in the form of seeds of other species (%), with a sample cleaner with sieves and suction, baking strength (W), elasticity (L), tenacity (P), P/L ratio, and swelling (G). The last six variables were evaluated with Chopin Alveograph, only for the ’Caaveiro’ crop, due to the similarity of the Carral ecotype with this crop but with less genetic homogeneity of the seed (unpublished data).
Soil samples were collected the first year before sowing and before the beginning of the last growing season (third year, all wheat). Twelve subsamples were collected for each experimental subplot at a depth of 20 cm to complete a homogeneous sample for each experimental unit. The following parameters were analysed: pH in water at 25 °C (potentiometer with glass electrode); organic matter (%), determination of organic C (Walkley Black method); Olsen phosphorus (mg kg−1); assimilable potassium (mg kg−1); Ca (mg kg−1); Mg (mg kg−1); Na (mg kg−1), extraction with ammonium acetate (atomic absorption spectrophotometer); CEC (sum of cations extracted with ammonium acetate) (meq 100 g−1); Ca/Mg, K/Mg; and Ca:Mg:K ratio.
Pearson’s correlations (r) were estimated with IBM SPSS Statistics 25 between the agronomical traits, and the soil characteristics for each subplot were evaluated during the third year previous to sowing. Estimated correlations were considered significant (p < 0.05). An analysis of variance (ANOVA) was carried out with IBM SPSS Statistics 25 to estimate the effects of the agronomical traits. The AS-N-K multiple range test was used to assess significant differences between means at the 5% level. In addition, we performed principal component analysis (PCA) with IBM SPSS Statistics 25 over the standardised agronomical traits to detect the main origins of variability in relation to rotations and the quality of the soil.

2.2. Environmental Assessment Methodology

The environmental profile associated with each scenario proposed for assessment was analysed using the LCA methodology [25], with the aim of identifying the best crop rotation from an environmental point of view. To this end, the analysis was conducted from a cradle-to-farm gate perspective. Figures S1–S3 in the Supplementary Material show the schemes of the 6 rotation scenarios analysed. As depicted in the diagrams, the effect of biomass left in the field after harvest (i.e., straw and/or grass) was allocated to the next crop. As for the life cycle inventory, each rotation system included the production of the required inputs—background processes: seeds, machinery, diesel, and agrochemicals (fertilisers, pesticides, and herbicides)—as well as their use and consumption. Therefore, the emissions derived in the field and at the tailpipe were also calculated in the inventories. A more detailed description of the primary inventory data can be found in Tables S1–S3 in the Supplementary Material.
Field emissions related to the application of agrochemicals were estimated according to González-García et al. [23]. Accordingly, N2O, NH3, and NO2 emissions into air and NO3− and PO4−3 emissions to groundwater from the application of mineral fertilisers were estimated. In addition, emissions to air, water, and soil from other agrochemical applications were also computed, taking into account the amount of active ingredient applied.
The crop biomass left on the field (grass in fallow and straw in lupin and wheat crops) has a relevant impact on the land and ultimately modifies GHG emissions [23]. Due to their relevance, these effects were assessed, following the guidelines given by Schmidt et al. [26], in terms of direct and indirect land use changes (dLUC and iLUC, respectively). iLUC refers to changes in carbon content occurring on land other than the land being used. In this study, a single emission factor was estimated as iLUC for all rotation systems: 144 kg CO2eq ha−1 of agricultural land used per cropping system over a period of 3 years. For its calculation, the location (Galicia), type of land (arable land), and the soil carbon content (6.11 tC ha−1 y−1) were considered.
In years when wheat and lupin were grown, only the grain and seeds (respectively) were harvested, while the remaining biomass was left in the field (representing 57% for wheat and 55.5% for lupin). Where fallow was implemented, the total biomass, the grass, was left in the field (Figures S1–S3 in the Supplementary Material). The permanence of the biomass in the field causes an increase in its soil carbon content, which corresponds to dLUC. In order to quantify these increases, a proportion of 16% of the biomass left in the field was assumed to be captured in the soil in the long term [27], considering that 49% (for wheat) and 47% (for lupin and grass) of the dry matter biomass corresponds to the carbon content [28,29].
Concerning the life cycle impact assessment, ReCiPe 2016 hierarchist Midpoint method V1.06 World (2010) [30] was considered and SimaPro software v9.3 [31] was used to implement the primary inventory data. Ecoinvent database v3.8 was considered for the collection of inventory data corresponding to background processes. The chosen impact categories to assess the environmental profiles were global warming (GW), terrestrial acidification (TA), freshwater eutrophication (FE), terrestrial ecotoxicity (TET), and freshwater ecotoxicity (FET). In accordance with the main objective of the study, one kilogram of wheat harvested in the third year was used as the functional unit.

3. Results

Harvesting dates for the three years were 21 August 2018, 16 August 2019, and 12 August 2020. There was adequate weed control thanks to the chemical treatment, although it was more complete in the rotation plots. In monoculture plots, with a lower general growth, fungi, Gaeumannomyces graminis and Fusarium roseum, and insects, Mayetiola sp., Frankliniella fusca, and Chlorops sp. were identified. The monoculture subplots had lower plant density with less vegetative development, smaller spikes, and poorer root development (Figure 2).
Rotations showed significant differences (p < 0.05) (Table 1) for grain yield, hectolitre weight, weight of one thousand seeds, and impurities in the form of seeds of other species.

3.1. Grain Yield

ANOVA showed significant differences (p < 0.01) in the grain yield. Rotations (Table 1, Figure 3) B (lupine-fallow-Carral ecotype of wheat) and E (lupine-fallow-Caaveiro wheat) presented higher significant differences (1996.75 kg ha−1 and 2356.75 kg ha−1, respectively) with respect to C (Carral ecotype of wheat monoculture) and F (Caaveiro wheat monoculture) (863.25 kg ha−1 and 887 kg ha−1, respectively). When lupin preceded both the Carral ecotype and ‘Caaveiro’ wheat, grain yield (1833.3 and 1601 kg ha−1, respectively) was higher than monoculture and lower than rotations with fallow before wheat.

3.2. Hectolitre Weight (kg 100 L−1)

ANOVA showed significant differences (p < 0.01) for hectolitre weight. Rotations beginning with lupine and fallow, A (F-L-WEcot), B (L-F-WEcot), D (F-L-WCaav), and E (L-F-WCaav), had significantly higher values (74.5, 75.6, 75, and 76.7 kg 100 L−1, respectively) than monoculture C (WEcot-WEcot-WEcot) and F (WCaav-WCaav-WCaav) (70.4 and 69.6 kg 100 L−1, respectively).

3.3. Weight of One Thousand Seeds

ANOVA showed significant differences (p < 0.001) for weight of one thousand seeds. Rotations beginning with lupine and fallow, A (F-L-WEcot), B (L-F-WEcot), D (F-L-WCaav), and E (L-F-WCaav), had significantly higher values (49.2, 48.8, 48.9, and 50.8 g, respectively) than monoculture, C (WEcot-WEcot-WEcot), and F (WCaav-WCaav-WCaav) (42.5 and 43.1 g, respectively).
The main traits evaluated with higher significant differences (yield, one thousand seeds, weeds, and impurities) indicated that the monoculture was the least favourable with respect to both rotations, the one beginning with fallow and the one beginning with lupine (Figure 3).

3.4. Impurities from Other Seeds

Monoculture F (WCaav-WCaav-WCaav) had significantly (p < 0.05) more impurities (0.49%) than rotations D (0.22%) (F-L-WCaav) and E (0.18%) (L-F-WCaav) when the same herbicide treatment was applied to the trial. A lower presence of seeds of other species was observed in the harvested grain, most of them coming from grasses (Lolium sp. and Avena sp.).

3.5. Grain Moisture, Grain Protein, and Wet Gluten

For these traits (Table 1), the rotation factor did not cause significant differences. Values for grain moisture (H) varied from 12.8% for B (L-F-WEcot) to 13.5% for monocultures C (WEcot-WEcot-WEcot) and F (WCaav-WCaav-WCaav); and wet gluten from 28% for A (F-L-WEcot) to 29% for C (WEcot-WEcot-WEcot).

3.6. Alveograph Parameters

Alveograph parameters W (baking force), P (Tenacity), L (Extensibility), P/L (Ratio between Tenacity and Extensibility), and G (Swelling) did not show significant differences between rotations (Table 1).Values varied for baking strength (W) from 170.8 for D (F-L-WCaav) to 179.3 for F (WCaav-WCaav-WCaav); elasticity (L) from 125.3 for F (WCaav-WCaav-WCaav) to 142.5 for D (F-L-WCaav); tenacity (P) from 57 for D (F-L-WCaav) to 62 for F (WCaav-WCaav-WCaav); finally, P/L ratio and swelling (G) from 24.8 for F (WCaav-WCaav-WCaav) to 26.4 for D (F-L-WCaav).

3.7. Lupine Yield

Yield for lupine varied from 2130.8 kg ha−1 for R1B to 3350.8 kg ha−1 for R3E in the first year and from 1944.3 kg ha−1 for R1A to 4027.8 kg ha−1 for R3D in the second year. Yield was not significantly different between the two years, with an average of 2663.3 kg ha−1 and 2664.93 kg ha−1 for the first and second years, respectively.

3.8. Correlations with Quality of the Soil

Significant correlations were observed between soil fertility parameters previous to sowing in the third year and alveograph parameters of flour quality. The pH in water at 25 °C had a positive correlation with elasticity (L) and swelling (G), with values of 0.619 and 0.622, respectively, and a negative correlation with tenacity (P) and P/L ratio, −0.666 and −0.657, respectively. Castable organic matter (%) presented a positive correlation with P (toughness) and W (baking force), 0.738 and 0.743, respectively, and the opposite with Olsen phosphorus (mg kg−1), −0.730 and −0.777, respectively. Assimilable potassium, CEC, and Ca/Mg, K/Mg, and Ca:Mg:K ratios showed a negative correlation with W (baking force), −0.588, −0.683, and −0.811, respectively. Finally, Ca had a negative correlation with tenacity (P), P/L ratio, and baking strength (W), −0.788, −0.586, and −0.684, respectively.
The influence of Olsen phosphorus, Ca (mg kg−1), Ca:Mg:K ratio, and castable organic matter (%) status on the soil affected W (baking force) (Table 2) and tenacity (P) (Table 2), with the highest values in the subplots having the highest levels of organic matter. On the contrary, the lowest W was found in subplots with Olsen phosphorus over 60 mg kg−1.

3.9. Environmental Assessment Results

The environmental assessment showed a notable difference between rotation and monoculture-based regimes. Concerning the scenarios where the Carral ecotype was grown, rotation A (F-L-WEcot) was the most environmentally friendly scenario regardless of the impact category analysed (Figure 4a). Concerning the ’Caaveiro’ landrace, rotation D (F-L-WCaav) reported the best environmental profile, except for categories FE and MET, in which the introduction of the legume before fallowing, i.e., rotation E (L-F-WCaav), was the preferred system (Figure 4b). Nevertheless, irrespective of the wheat variety, the monoculture-based systems; that is, rotations C (WEcot-WEcot-WEcot) and F (WCaav-WCaav-WCaav), were the ones with the worst environmental profiles for all the impact categories.
The environmental hotspots, that is, the flows or activities responsible for the highest contributions to the global profile were also identified. As expected, the on-field emissions related to the application of mineral fertilisers were mainly responsible for the environmental burdens for all scenarios in terms of GW, TA, and FE. In addition, the production of the required dose of these mineral fertilisers also played a key role, especially in GW and TET. Regarding FET impact category, burdens derived mainly from the application of herbicides. Moreover, returning the biomass to the field reduced CO2eq emissions in all agricultural systems. These improvements in terms of GHG emissions were considered as environmental credits. Rotations A and D presented the most outstanding results since their environmental credits outweighed their derived impacts (Table S4 in the Supplementary Material).

4. Discussion

Rotation B (lupine-fallow-Carral ecotype of wheat) and E (lupine-fallow-Caaveiro wheat) showed 56% and 62% higher yield than monoculture C (Carral ecotype of wheat monoculture) and F (Caaveiro wheat monoculture), respectively. Yield increases were lower with wheat immediately after lupine in the sequence, with 44.6% for ‘Caaveiro’ wheat and 52.9% for ecotype wheat, lower than the 60% described by Angus et al. [10] in the rotation of lupine–wheat.
Rotation also contributed to better control of the adventitia, reflected in a lower presence of seeds of other species in the harvested grain, most of them coming from grasses (Lolium sp. and Avena sp.). The cereal monoculture increases the pressure of adventitious weeds with a similar cycle [32].
Rotation B (lupine-fallow-Carral ecotype of wheat) and E (lupine-fallow-Caaveiro wheat) showed increases in hectolitre weight (HW), close to 7% and 9%, compared to monoculture C (Carral ecotype of wheat monoculture) and F (Caaveiro wheat monoculture), respectively. Finally, rotations A and B showed increases of around 13% with respect to the monoculture. On the other hand, the D and E (lupine-fallow-’Caaveiro’ wheat) rotations increased the weight of one thousand seeds by 12% and 15%, respectively, the same level as the 10% obtained in a 29-year study of winter wheat rotation versus monoculture [33] and higher than those observed by other authors in similar trials (2.43%) [34]. As it happened with yield, these results could not only be related to a higher soil nitrogen level but also to the benefits of a disease break and better weed control [10]. Intercropping a legume in the rotation with winter wheat reduces the inoculum of Gaeumannomyces graminis (an incidence of foot disease of between 20 and 60% in the third year in this study). Other studies also confirmed the positive effect of rotating wheat with legumes as a pre-crop, observing a reduction in the incidence and severity of the disease in the following year [35]. The higher incidence of foot and root diseases could have been a key factor in this decline in monoculture plots, as other authors also noted [10].
Wheat monoculture negatively affects grain yield and quality [36,37], which is in agreement with the present work indicating a clearly negative effect of the cereal monoculture on yield parameters, impurities, specific weight, and weight of one thousand seeds. Rotation with lupine positively influenced these parameters on the cereal. These effects became much more visible in the second year after interspersing one year of fallow. In line with other trials, a positive effect of rotation on the specific weight and the weight of one thousand seeds was observed, in which the monoculture negatively affected these parameters [36].

4.1. Alveograph Parameters

Despite the existence of numerous studies that highlight the positive effect of the legume predecessor crop on the percent protein of the cereal [38], no significant differences were observed in this study. A previous study indicated a positive effect of rotation with legumes on alveograph parameters [39]. Meanwhile, other work indicated that this effect requires an extra nitrogen supply to make this improvement evident [40].
Organic matter constitutes a transcendental factor in the fertility of any soil, acting on its physical, chemical (providing nutrients), and biological properties. The quality of wheat depends largely on the availability of N in the soil during the grain filling phase. Nitrogen has effects on the rheological parameters of the dough, such as baking force (W), toughness (P), and extensibility (L) [41]. In our case, a significant positive correlation was observed between organic matter and W (baking strength). The subplots with higher W results had much higher organic matter contents.

4.2. Rotation, Fallow

The inclusion of fallow breaks the cycle of diseases and allows for mechanical weed control. Said tillage also promotes the mineralisation of the organic matter provided in the previous crop, making it available to the next crop. There are many studies that reinforce the positive effect on the yield of wheat in rotation compared to monoculture [10]. The incorporation of fallow increased yields and profitability in farms in southeastern Australia, maintaining the benefits by reducing the cost of inputs [42]. Other studies cite the positive effect of fallow in relation to water storage in the soil profile, registering notable increases in wheat yield [43].

4.3. Rotation, Lupine

Lupine productivity was similar for both rotations, with average results similar to other studies for the same variety in its country of origin [44]. Intercropping a legume in the rotation with winter wheat reduces the inoculum of Gaeumannomyces graminis (foot disease) to safe thresholds for the cereal according to trials in the USA [45]. In our monoculture plots, we found an incidence between 20% and 60% in the third year. The higher incidence of foot and root diseases could have been a key factor in the decline in monoculture plots, as this happened in other studies [35].
Lupine residues can be over 4.5 t ha−1 of dried matter with a richness in nutrients of N, 1.81%; P2O5, 0.4%; and K2O, 0.72% for a sowing dose of 100 plants per m2 [46]. These residues had a higher effect with fallow before wheat, with an increase in yield of approximately 10% with respect to lupine before wheat, which could be related to the beneficial function of weedy fallow in the retention and recycle of the nutrients as described in previous studies [47]. In our trial, the fallow was not cultivated, allowing the development of adventitia until its clearing prior to the consolidation of the seeds.

4.4. Environmental Profile

Rotations A and D were the scenarios with the best environmental performances. This was mainly due to the remarkable difference in the dose of mineral fertilisers applied, where rotations B and E used two times more mineral fertilisers than A and D. Within ‘Caaveiro’ landrace systems, E showed the best environmental performance for categories FE and FET; meanwhile, within ‘Carral’ ecotype rotations, A presented the best profile regardless the category analysed. This is justified by the noticeably higher yield of E (47%) with respect to D, whereas A and B obtained similar yields (Table 1). In this regard, and as was to be expected, the consideration of productivity as the functional unit benefits the scenarios with higher yields. Monocultures C and F had both high mineral fertilisation and low yield; therefore, both scenarios presented the worst environmental profiles. Concerning the environmental hotspots previously identified, the majority of the environmental burdens derived from the fertilisation process. Since legumes have the ability to fix nitrogen [18], rotations with lupine (A, B, D, and E) could experience an improvement of their environmental profiles if a lower dose of mineral fertilisers was applied.

5. Conclusions

The wheat landraces monoculture negatively affected yield and milling quality. It also presented the worst environmental profiles.
The lupine-fallow-wheat rotation sequence increased yield by over 60%. The fallow-lupine-wheat sequence also improved production notably (57%), while implying less environmental impact. With the cultivation of Lupinus albus, the contribution of chemical fertilisers can be reduced or eliminated, reducing environmental burdens.
Soil quality influenced wheat bakery quality, independent of rotation. Higher organic matter contents and lower phosphorus levels meant increases in the parameters W (baking force) and P (Tenacity).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture12070905/s1, Figure S1: Flowchart for scenarios A (Fallow-Lupine-Wheat ecotype Carral) and D (Fallow-Lupine-Wheat Caaveiro); Figure S2: Flowchart for scenarios B (Lupine-Fallow -Wheat ecotype Carral) and E (Lupine-Fallow -Wheat Caaveiro); Figure S3: Flowchart for scenarios C (Wheat ecotype Carral-Wheat ecotype Carral-Wheat ecotype Carral) and F (Wheat Caaveiro-Wheat Caaveiro-Wheat Caaveiro); Table S1: Field operations and inventory data (per hectare) for the rotations A and D in year 1; B and E in year 2; and for the rotations B, C, E and F in year 1; Table S2: Field operations and inventory data (per hectare) for the rotations B, C, E and F in year 2; Table S3: Field operations and inventory data (per hectare) for the rotations A, B, C, D, E and F in year 3; Table S4: Characterization results per kg of wheat harvest in the third year.

Author Contributions

Methodology, F.A.-G., S.P.-L., B.R.-N., S.L.-O., R.R.-L. and S.G.-G.; software, F.A.-G., S.P.-L., B.R.-N., S.L.-O., R.R.-L. and S.G.-G.; resources, F.A.-G.; data curation, F.A.-G., S.P.-L. and B.R.-N.; writing—original draft preparation, F.A.-G., S.P.-L., S.L.-O., R.R.-L. and S.G.-G.; writing—review & editing, F.A.-G., S.P.-L., S.L.-O., R.R.-L. and S.G.-G.; supervision, S.G.-G., M.T.M., S.P.-L. and B.R.-N.; project administration, F.A.-G.; funding acquisition, F.A.-G. and S.G.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

To Manuel Da Cunha Pereira for providing the material and human resources for the execution of the project, the cultivation plots, the fertilisers, the phytosanitaries, and machinery. To Félix Veiga González for successfully executing all the cultivation tasks for the three consecutive years: tillage, sowing, treatments, and harvesting. To Ana María Ramos-Cabrer for her work in reviewing this document. To the project Enhancing diversity in Mediterranean cereal farming systems (CerealMed) funded by PRIMA Programme and FEDER/Ministry of Science and Innovation—Spanish National Research Agency (PCI2020-111978) for its financial support.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Agriculture 12 00905 g001 550
Figure 1. Trial design: R1, repetition one; R2, repetition two; R3, repetition three; R4 repetition four; A, fallow (Year 1), lupine (Year 2), and Carral ecotype of wheat (Year 3); B, lupine (Year 1), fallow (Year 2), and Carral ecotype of wheat (Year 3); C, Carral ecotype of wheat monoculture; D, fallow (Year 1), lupine (Year 2), and ‘Caaveiro’ wheat (Year 3); E, lupine (Year 1), fallow (Year 2), and ‘Caaveiro’ wheat (Year 3); and F, ‘Caaveiro’ wheat monoculture. In dark grey, wheat monoculture.
Figure 1. Trial design: R1, repetition one; R2, repetition two; R3, repetition three; R4 repetition four; A, fallow (Year 1), lupine (Year 2), and Carral ecotype of wheat (Year 3); B, lupine (Year 1), fallow (Year 2), and Carral ecotype of wheat (Year 3); C, Carral ecotype of wheat monoculture; D, fallow (Year 1), lupine (Year 2), and ‘Caaveiro’ wheat (Year 3); E, lupine (Year 1), fallow (Year 2), and ‘Caaveiro’ wheat (Year 3); and F, ‘Caaveiro’ wheat monoculture. In dark grey, wheat monoculture.
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Agriculture 12 00905 g002 550
Figure 2. Above left picture: differences in vegetative development (those with less development correspond to the monoculture of wheat, treatments C and F). Above right picture: spike morphology, treatment E (rotation) versus F (monoculture). Below left image: general view of the state of the plants, treatments E and F. Below right image: plant root of plot F (monoculture) with symptoms of Gaeumannomyces graminis.
Figure 2. Above left picture: differences in vegetative development (those with less development correspond to the monoculture of wheat, treatments C and F). Above right picture: spike morphology, treatment E (rotation) versus F (monoculture). Below left image: general view of the state of the plants, treatments E and F. Below right image: plant root of plot F (monoculture) with symptoms of Gaeumannomyces graminis.
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Figure 3. Parameters with significant differences (p < 0.05): grain yield (GY, kg∙ha−1), humidity of the seeds (H, %), hectolitre weight (HW, kg∙100 L−1), and weight of one thousand seeds (WTS, g).
Figure 3. Parameters with significant differences (p < 0.05): grain yield (GY, kg∙ha−1), humidity of the seeds (H, %), hectolitre weight (HW, kg∙100 L−1), and weight of one thousand seeds (WTS, g).
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Figure 4. Comparative profiles between the different scenarios in terms of global warming (GW), terrestrial acidification (TA), freshwater eutrophication (FE), terrestrial ecotoxicity (TET), and freshwater ecotoxicity (FET); (a) scenarios with Carral ecotype. (b) Scenarios with ‘Caaveiro’ landrace.
Figure 4. Comparative profiles between the different scenarios in terms of global warming (GW), terrestrial acidification (TA), freshwater eutrophication (FE), terrestrial ecotoxicity (TET), and freshwater ecotoxicity (FET); (a) scenarios with Carral ecotype. (b) Scenarios with ‘Caaveiro’ landrace.
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Table
Table 1. Agronomical traits for Galician wheat (‘Carral’ ecotype and ‘Caaveiro’ wheat, WEcot and WCaav, respectively) for six rotations with lupine (L) and fallow (F) evaluated by ANOVA: grain yield (GY, kg ha−1), humidity of the seeds (H, %), hectolitre weight (HW, kg 100 L−1), and weight of one thousand seeds (WTS, g), protein (%), wet gluten (%), impurities in the form of seeds of other species (%), baking strength (W), elasticity (L), tenacity (P) and P/L ratio, and swelling (G).
Table 1. Agronomical traits for Galician wheat (‘Carral’ ecotype and ‘Caaveiro’ wheat, WEcot and WCaav, respectively) for six rotations with lupine (L) and fallow (F) evaluated by ANOVA: grain yield (GY, kg ha−1), humidity of the seeds (H, %), hectolitre weight (HW, kg 100 L−1), and weight of one thousand seeds (WTS, g), protein (%), wet gluten (%), impurities in the form of seeds of other species (%), baking strength (W), elasticity (L), tenacity (P) and P/L ratio, and swelling (G).
RotationGY (kg ha−1) **H(%) nsHW (kg 100 L−1)
**		WTS (g) ***Protein (%)
ns		Wet Gluten (%) nsSeed Impurities (%)
*		W
ns		L
ns		p nsG ns
AF-L-WEcot1833.3 ab a13.374.5 b49.2 b14.328-----
BL-F-WEcot1996.8 c12.875.6 b48.8 b14.628.3-----
CWEcot-WEcot-WEcot863.3 a13.570.4 a42.5 a14.929.5-----
DF-L-WCaav1601 ab13.375 b48.9 b14.828.80.22 a170.8142.55726.4
EL-F-WCaav2356.8 c13.476.7 b50.8 b13.926.60.18 a173.5132.859.825.3
FWCaav-WCaav-WCaav887 a13.569.6 a43.1 a14.4290.49 b179.3125.36224.8
* p < 0.05, ** p < 0.01, *** p < 0.001, ns—not significant. a (a, b, c) Means with different letters in the same column differ statistically using an SNK test at p < 0.05.
Table
Table 2. Pearson’s correlations between quality characteristics of the wheat and soil analyses.
Table 2. Pearson’s correlations between quality characteristics of the wheat and soil analyses.
Alveograph Parameters of Flour QualitypH in Water at 25 °COrganic Matter (%)Phosphorus Olsen (mg kg−1)Assimilable Potassium (mg kg−1)Ca (mg kg−1)Mg(mg kg−1)CEC (Sum of Cations Extracted with Ammonium Acetate) (meq/100 g)Ca/Mg, K/Mg, and Ca:Mg:K Ratio
Elasticity (L)0.619 *−0.2800.2280.0930.3830.5000.3310.156
0.0320.3780.4760.7730.2180.0970.2930.629
Tenacity (P)−0.666 *0.738 **−0.730 **−0.465−0.788 **−0.416−0.758 **−0.714 **
0.0180.0060.0070.1280.0020.1790.0040.009
Swelling (G)0.622 *−0.2830.2350.0740.3990.5190.3510.170
0.0310.3730.4610.8190.1990.0840.2630.598
P/L ratio−0.657 *0.476−0.449−0.169−0.586 *−0.540−0.563−0.406
0.0200.1180.1430.6000.0450.0700.0570.190
Baking strength (W)−0.2880.743 **−0.777 **−0.588 *−0.684 *−0.024−0.683 *−0.811 **
0.3640.0060.0030.0440.0140.9410.0140.001
* p < 0.05; ** p < 0.01.
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Almeida-García, F.; Lago-Olveira, S.; Rebolledo-Leiva, R.; González-García, S.; Teresa Moreira, M.; Ruíz-Nogueiras, B.; Pereira-Lorenzo, S. Growing Triticum aestivum Landraces in Rotation with Lupinus albus and Fallow Reduces Soil Depletion and Minimises the Use of Chemical Fertilisers. Agriculture 2022, 12, 905. https://doi.org/10.3390/agriculture12070905

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Almeida-García F, Lago-Olveira S, Rebolledo-Leiva R, González-García S, Teresa Moreira M, Ruíz-Nogueiras B, Pereira-Lorenzo S. Growing Triticum aestivum Landraces in Rotation with Lupinus albus and Fallow Reduces Soil Depletion and Minimises the Use of Chemical Fertilisers. Agriculture. 2022; 12(7):905. https://doi.org/10.3390/agriculture12070905

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Almeida-García, Fernando, Sara Lago-Olveira, Ricardo Rebolledo-Leiva, Sara González-García, María Teresa Moreira, Benigno Ruíz-Nogueiras, and Santiago Pereira-Lorenzo. 2022. "Growing Triticum aestivum Landraces in Rotation with Lupinus albus and Fallow Reduces Soil Depletion and Minimises the Use of Chemical Fertilisers" Agriculture 12, no. 7: 905. https://doi.org/10.3390/agriculture12070905

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