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Article

Comparison of Productivity and Agro-Biological Traits of Alfalfa Populations Resistant to Mobile Al Grown on Acidic and Neutral Soils

by
Regina Skuodienė
1,*,
Aurelija Liatukienė
2 and
Giedrius Petrauskas
2
1
Vėžaičiai Branch of Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry, Gargždų St. 29, Vėžaičiai, LT-96216 Klaipėda District Municipality, Lithuania
2
Institute of Agriculture, Lithuanian Research Centre for Agriculture and Forestry, Instituto al. 1, Akademija, LT-58344 Kėdainiai District Municipality, Lithuania
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(1), 156; https://doi.org/10.3390/agronomy13010156
Submission received: 18 November 2022 / Revised: 15 December 2022 / Accepted: 28 December 2022 / Published: 3 January 2023
(This article belongs to the Section Grassland and Pasture Science)
Browse Figures
Versions Notes

Abstract

:
To evaluate the agro-biological traits and select the promising populations of alfalfa under pedoclimatic conditions, field experiments were carried out in two locations of the Lithuanian Research Centre for Agriculture and Forestry (western Lithuania 55°70′ N, 21°49′ E and central Lithuania 55°23′ N, 23°51′ E). Eleven populations were established in acidic soil with a pH of 4.0 (experimental site I) and neutral soil with a pH of 7.0 (experimental site II). The productivity and agro-biological traits: fresh matter yield, dry matter yield, seed yield, stem thickness, and stem, leaf, and inflorescence weight of alfalfa populations were evaluated from 2019 to 2021. In the acidic soil, the populations 3056, 3132, 3130, and 3058 yielded more fresh and dry matter compared to the standard cultivar Birutė in the period from 2019 to 2021. In the acidic soil, populations 3131 and 3057 had a higher seed yield compared to the cultivar Birutė in 2019 and 2020, respectively. The 3086 population significantly differed in leaf weight compared to the cultivar Birutė. The cultivar Birutė and population 3132 were similar in stem thickness and fresh matter yield. In the neutral soil, population 3056 yielded more fresh matter compared to the cultivar Birutė.

1. Introduction

Alfalfa (Medicago sativa L.) is an important and the main leguminous crop worldwide, spreading in southern Europe where it is usually grown under irrigation in low-rainfall areas [1]. Alfalfa increases the nitrogen content and generally improves soil fertility due to their deep-reaching systems, accumulation into the soil, and rapid breakdown of root biomass [2,3]. Increasing the variability of selection material could be achieved by introducing distinct alfalfa varieties or populations as new sources of diversity. Given the importance of alfalfa as a forage crop, scientific efforts are being made to improve the yield and quality of alfalfa through breeding techniques. The agro-morphological characterisation is the first step towards the evaluation of genotypes and is often used in breeding programs for developing cultivars with high forage production and quality [4,5].
As the climate changes so do the environmental factors which have the greatest impact on crops [6]. Therefore, there is an increasing need for fertile and high-quality alfalfa cultivars that adapt to regional conditions. Research should be expanded by selecting genotypes of alfalfa with high adaptive capacity and good productivity [7]. Creating new, fertile, and better-fed alfalfa cultivars or populations that adapt to environmental conditions is a very time-consuming process of selecting plants with improved qualities over several cycles to produce cultivars significantly better than others (resistant to cold or drought, higher yield, better nutritive value, etc.) [8,9]. There are numerous cultivars in the world, created with one or several positive characteristics, but they often have different adaptability to environmental conditions [9].
Alfalfa is usually grown on neutral soil, with a pH ranging from 6.2 to 7.8 [3]. Less productive Retisols in Lithuania account for about 8% of the country’s total soil area. Retisols have a low buffering capacity and sorption, resulting in fast acidification, and loss of nutrients and water reserves [10]. On low-yielding soils, alfalfa growth is very slow, and the productivity of genotypes is very low due to the direct effects of pH on the root environment and plant growth [11,12]. When alfalfa plants are grown in soil with an acidic pH, root growth is reduced or halted, and forthright toxicity occurs as H, Fe, Al, and Mn ion concentrations build up and corresponding deficiencies of the available P, Mo, Ca, Mg and K show up [12,13].
As a result, new genotypes of alfalfa are being developed that are resistant to low-pH soils. However, alfalfa cultivars and populations respond differently to the low pH of soil and concentrations of mobile Al [14]. In fact, several scientists from different regions of the world have emphasized the problem of the susceptibility of alfalfa to soil acidity [15,16]. The resistance of alfalfa to mobile Al can be assessed based on laboratory methods, such as hydroponic, filter paper-based screening, and root staining methods [17,18,19]. In addition, the resistant genotypes of alfalfa are selected in field conditions when genotypes of alfalfa are grown in low-pH soil and with high concentrations of mobile Al [20].
According to these observations, we hypothesised that by choosing different soil types (Retisol and Cambisol), it is possible to affect not only the biomass and seed yields but also the agro-biological traits of alfalfa in both positive and negative ways. Given that soil properties (pH and mobile aluminium) can have a major impact on alfalfa development, we utilised data from a field experiment to test the effects of soil acidity factors on the productivity and agro-biological traits of alfalfa.
Therefore, the aim of this study was to investigate the seed, fresh, and dry matter yields, stem thickness, leaf weight, stem weight, and inflorescence weight of local populations of alfalfa under different soil pH and climatic conditions and select the promising populations of alfalfa which grow in acidic soil with concentrations of mobile Al.

2. Materials and Methods

2.1. Development of Alfalfa Populations Resistant to Mobile Al under Laboratory Conditions

In the period from 2008 to 2009, populations of alfalfa were developed by crossing Lithuanian and foreign accessions with different resistance indices to acidic soil (Table 1). In 2010, the tolerance to mobile Al toxicity in populations of alfalfa was determined by filter paper-based screening methods under laboratory conditions [21]. The most tolerant alfalfa populations were characterized by the best seed germination and longer hypocotyls and roots at 8 and 16 mM AlCl3 concentrations. The seeds of the most promising 11 populations of alfalfa were germinated in a 16 mM AlCl3 concentration for 4 days in the dark at 25 °C. Later, the seeds were maintained for 3 days with 12 h illumination at 25/20 °C. After 3 days, seedlings of each population were placed into hydroponic conditions and maintained for 5 days. After 5 days, the seedlings were planted in pots and maintained in greenhouse conditions. Plants of populations were pollinated by hand and the seeds of each population were harvested by hand. The seeds of each population in selection cycle C1 were harvested in 2011. According to Scott et al. (2008) [22], the recurrent selection was carried out in vegetation pots in greenhouse conditions from 2011 to 2014. Then, from 2015 to 2017, the evaluation of alfalfa populations occurred based on morphological traits, seed yield, and resistance to diseases in field conditions.

2.2. Plant Material, Research Location, Experimental Design, and Soil Description

The experimental material consisted of 11 populations that were developed under laboratory and greenhouse conditions in previous research from 2008 to 2014 and tested under field conditions over the period from 2015 to 2017. The populations of alfalfa were established in 2018 on two experimental sites of the Lithuanian Research Centre for Agriculture and Forestry. Experimental site I was in the Vėžaičiai Branch in the western part of Lithuania (55°70′ N lat., 21°49′ E long.), and experimental site II was in the Institute of Agriculture in the central part of Lithuania (55°23′ N lat., 23°51′ E long.). The soil texture and climate of experimental sites I and II are shown in Table 2.
The populations of alfalfa were sown on 24–25 April 2018 using a randomised block design with four replications. The seeds of each population were sown at a rate of 0.2 g scarified seed per 1 m in two 3-metre-long rows with a special hand-sowing machine Plomatic 1R (Wintersteiger, Austria). The distance between the rows of the line was 0.5 m, and between different cultivars was 1.0 m. The field area of one population was 1.5 m2.
The populations of alfalfa were assessed from 2019 to 2021; the fresh matter (FM), dry matter (DM), and seed yield (SY) were evaluated. In the acidic soil (experimental site I), the plants of populations were cut two times in each experimental year at an early flowering growth stage (10.0% flowers). In the neutral soil (experimental site II), the populations were cut three times each year at an early flowering growth stage. The seed yield (kg ha–1) and the fresh and dry matter yields were then measured (t ha–1). To determine the dry grass content, fresh samples (500 g) of randomly chosen plants were taken from each plot, dried at 105 °C, and weighed. To determine the components of alfalfa grass, the stems, leaves, and inflorescences parts of plants were used. The fresh samples (1000 g) were taken from each plot of populations, dried at 105 °C, and weighed. In addition, the weight (g) of stems, leaves, inflorescences, and stem thickness (mm) were determined.
The experimental plots of alfalfa in both experimental sites (I and II) were sprayed with the herbicide Basagran 480 (a.i. bentazon 480 g L–1) at 2 L ha–1 to protect them from weeds in 2018, when, after germination, the alfalfa had reached the height of 10 cm. In addition, the seed crops of alfalfa before flowering time were sprayed with Mavrik 2 F (a.i. tau-fluvalinate240 g L–1) 0.20 L ha–1 from 2019 to 2021.
The agrochemical characteristics of the soil were determined from soil samples taken from a depth of 0–20 cm with a drill from each plot before establishing the experiment: soil acidity was measured by the potentiometric method in the extraction of 1 M KCl(pHKCl) according to the standard ISO 10390:2005 (Soil quality—Determination of pH). Mobile P2O5 and K2O in the soil were determined using the Egner–Riehm–Domingo (A-L) method (LVP D-07:2016) and mobile Al was determined according to the standard ISO 14254:2018 (Soil quality—Determination of exchangeable acidity using barium chloride solution as extractant).

2.3. Meteorological Conditions during the Vegetation Period of Alfalfa Populations

The climate of the Western part of Lithuania is transitional between a maritime climate and a continental climate. The growing season of alfalfa plant populations started on the 20th and 25th of April, respectively, in 2019 and 2020, and on the 5th of May in 2021. During the vegetation period in 2019, the average temperature and precipitation were 10.2 °C and 39.7 mm in the spring months and 17.7 °C and 55.7 mm in the summer and autumn months.
In 2020, the average temperature and precipitation of experimental site I were 8.2 °C and 16.9 mm in the spring season, 17.5 °C and 82.0 mm in the summer season, and 10.4 °C and 74.7 mm in the autumn season. In 2021, the average temperature and precipitation were 8.3 °C and 53.1 mm in the spring season, 18.6 °C and 77.9 mm in the summer season, 8.5 °C and 113.2 mm in the autumn season. (Figure 1A).
The weather conditions of experimental site II are shown in Figure 1B where cold and wet climate conditions prevail in the central region of Lithuania. In experimental site II, the growing season of plants of alfalfa populations started on the 9th, 11th, and 19th of April, respectively, in 2019, 2020, and 2021. In 2019, the average temperature and precipitation were 10.9 °C and 27.7 mm in the spring season, 18.7 °C and 63.0 mm in the summer season, and 9.0 °C and 37.6 mm in the autumn season. In 2020, the average temperature and precipitation were 8.7 °C and 29.8 mm in the spring season, 18.3 °C and 93.1 mm in the summer season, and 10.2 °C and 32.5 mm in the autumn season. In 2021, the average temperature and precipitation were 8.9 °C and 63.7 mm in the spring season, 19.6 °C and 67.4 mm in the summer season, and 7.9 °C and 50.4 mm in the autumn season (Figure 1B).

2.4. Statistical Analysis

An analysis of variance (ANOVA) was used followed by Tukey’s test for the least significant difference at p < 0.05 significance levels. The significance of the difference between the experimental treatments was evaluated by the one-factor analysis of variance ANOVA. The interactions between the population and year for seed yield, fresh and dry matter yields, and each component of structural analysis were evaluated by the two-factor analysis ANOVA. The correlations between experimental data were investigated using a linear regression analysis between the variables at 95% and 99% probability levels (p < 0.05 and p < 0.01). The statistical analyses were performed using the statistical program SAS Enterprise Guide, version 7.13 (SAS Institute Inc., Cary, NC, USA).

3. Results and Discussion

3.1. The Fresh and Dry Matter Yields and Components of the Structural Analysis of Alfalfa Populations

During all experimental years, the climatic conditions including the mean temperature and precipitation were quite variable, resulting in significantly different fresh and dry matter yields [23]. The significant (p < 0.05) influence of the year was also determined for fresh and dry matter yields in the acidic and alkaline soils (Table 3).
Kavut and Avcioglu (2015) [24] argued that soil factors, such as nutritional, biological, or physiological variables including soil temperature, influence root growth and development and the penetration of roots into the soil, thereby affecting the yield of crops. Khu et al. (2012) [19] and Dugalić et al. (2011) [25] argued that alfalfa is sensitive to mobile Al toxicity, reducing the penetration of roots and symbiotic nitrogen fixation. In addition, the fresh matter yield is usually low due to the inhibited root growth in acidic soils [19]. Environmental factors influence the growth of alfalfa crops at various development stages, however, the genotypes have a wide response to environmental conditions [26]. In this study, the results showed that the fresh matter yield of alfalfa populations is dependent on the low concentrations of mobile Al in acidic soil and the contrasting weather conditions during the vegetation period. In 2019, the fresh matter yield was the lowest in the acidic soil (pH 4.4) due to very dry, warm weather conditions during the vegetation period of the alfalfa. In neutral soil (pH 7.0) in 2019, the fresh matter yield was 40.0 t ha–1 higher compared with the fresh matter yield in acidic soil (pH 4.4). In 2020, the fresh matter yield was 19.1 t ha–1 lower in the acidic soil, compared with neutral soil, due to rainy and warm weather conditions. In 2021, the fresh matter yield was 7.5 t ha–1 higher in the acidic soil compared to the neutral soil because the weather conditions were very hot and dry. A significant (p < 0.05) influence on the alfalfa population in acidic soil (pH 4.4) was determined for fresh matter yields. In this study, the results showed that differences in the fresh matter yield among populations of alfalfa was dependent on the environmental conditions and genotype effect in both regions. Kebede et al. (2017) [27] suggested that the selection of better-yielding genotypes in one environment may not enable the identification of genotypes that can repeat similar performances in other environments. Furthermore, our study showed that the populations of alfalfa differed more by the fresh matter yield in the acidic soil (pH 4.4). In 2019, the total fresh matter yield of population 3056 was significantly highest in the acidic soil. However, the population 3056 yielded more fresh matter compared to the standard cultivar Birutė (by 2.7 t ha–1) (Table 4).
In 2020, the populations 3132 and 3130 and cultivar Birutė had a similar fresh matter yield in the acidic soil. The fresh matter yield of populations 3132 and 3130 was higher compared to populations 3056, 3057, 3059, 3060, and 3131 (on average by 12.6 t ha–1), 3058 (by 16.6 t ha–1), 3061 (by 31.6 t ha–1), 3086 (by 20.0 t ha–1) and 3129 (by 6.6 t ha–1) (Table 4). In 2021, population 3130 had the highest fresh matter yield in the acidic soil compared to other populations and yielded more compared to the cultivar Birutė (by 23.0 t ha–1). Population 3056 had a higher total fresh matter yield in the neutral soil compared to populations 3057, 3058, 3059, 3060, 3061, 3132, 3129, and 3086 (on average by 18.6 t ha–1), 3131, and 3130 (on average by 33.0 t ha–1) (Table 4). However, population 3056 yielded more fresh matter compared to cultivar Birutė (by 4.0 t ha–1). Additionally, the study showed that the fresh matter yield of populations varied more (CV%) in the acidic soil in 2019 and 2021, while the fresh matter yield of the population varied more in the neutral soil in 2021 (Table 4).
The significant (p < 0.05) influence of the population in acidic soil (pH 4.4) was determined for the dry matter yields. The dry matter yields differed significantly between populations and between experimental sites (I and II), due to not only the weather conditions but the environmental conditions of the soil as well. It also showed that the interaction between the population and year was highly (p < 0.05) significant for the dry matter yield in the acidic soil (Table 2). The average dry matter yield was significantly higher in the acidic soil (pH 4.4) compared with the average dry matter yield in the neutral soil (pH 7.0), by 3.9 t ha–1 in 2020 and by 3.4 t ha–1 in 2021, respectively (Table 5). The dry matter yield has been shown to be dependent on regional climate, soil conditions, plant genetics, sowing time, and cultural practices [28]. The significant population differences observed for the dry matter yield in the present study concur with other reports [29,30,31].
In 2019, alfalfa population 3056 had the highest total dry matter yield in the acidic soil compared to other populations (Table 5). The dry matter yield of population 3056 was very similar compared to the standard cultivar Birutė, however, the average dry matter yield was 5.6 t ha–1 higher in the neutral soil compared with the acidic soil and the dry matter yield of the populations was similar in the neutral soil. In 2020, alfalfa population 3132 had the highest dry matter yield in acidic soil by 4.7 t ha–1 compared to the cultivar Birutė. The total dry matter yield of alfalfa population 3057 was significantly similar compared to the cultivar Birutė in the neutral soil (Table 5). In 2021, the dry matter yield of population 3058 was the highest in the acidic soil and was higher than the cultivar Birutė (by 4.0 t ha–1). However, the dry matter yield of all populations was very similar in the neutral soil (Table 5). Some research pointed out that the dry matter yield characteristics are closely related to the overall growth performance of alfalfa crops (such as fresh herbage yield and dry matter content) and there are great variations among various cultivars [32]. In this study, the dry matter yield variations were the highest among alfalfa populations in acidic soil. The alfalfa plants within the populations, which determined the dry matter yields, had a high degree of plant diversity. The dry matter yields showed the highest coefficient of variation in 2019. In 2020, the dry matter yield variations were medium and very low; in 2021, the variations were also very low. In addition, the variations of dry matter yield were determined in the neutral soil where the coefficient of variation was medium in 2020 and 2021 (Table 5).
The selection of promising genotypes in a breeding program is based on various criteria, especially on the final crop yield and its quality. The leaf–stem ratio is an important trait in the selection of appropriate forage cultivars as it is strongly related to forage quality. Katić et al., (2009) [33] and Gashaw et al. (2015) [34] reported that the proportion of leaf and stem in alfalfa hay can vary greatly, depending on maturity at harvest, cultivars, handing and climate conditions. In this study, the stem weight was higher than the leaf weight in 2019, 2020, and 2021 by 27%, 32.0%, and 23.7%, respectively, in the acidic soil, and by 22.4%, 21.2%, 17.6% in the neutral soil (Figure 2). Furthermore, this study showed that the stem weight composition of alfalfa was dependent on different soil types and the root growth, development, and penetration of roots in the soil, especially in acidic soil. The roots of alfalfa penetrated the soil better and the alfalfa plants became lusher in 2020 and 2021 (Figure 2). Additionally, the leaf weight was lower in the acidic soil because the leaves of alfalfa populations were smaller and their weight was lower compared with the neutral soil in 2019, 2020, and 2021 by 2.8%, 5.1%, and 3.0%, respectively. The inflorescence weight of the populations was higher in the acidic soil in 2019. The leaves and inflorescences weights of alfalfa populations depended on the weather conditions, the severity of diseases, and the soil types of the experimental sites (Figure 2).
Heidarian and Mostafavi (2012) [35] detected significant differences between the cultivars of alfalfa with regard to the leaf and stem ratio. Julier et al. (2000) [36] suggested that the leaf–stem ratio is an important trait in the selection of appropriate forage cultivars as it is strongly related to forage quality. In our study, population 3086 significantly differed by leaf weight and was 1.4-fold higher compared to the standard cultivar Birutė in the acidic soil. The weight of the leaves of all populations was lower compared with the weight of stems in the acidic and neutral soils, by 1.8-fold and 1.6-fold, respectively (Table 6). Other researchers have suggested that the cultivars of alfalfa had superior leaf–stem ratios and sometimes, the leaf–stem ratio of cultivars differed non-significantly [37,38]. The alfalfa plants varied by the weight of inflorescences within populations in the acidic and neutral soils and showed high variation coefficients (CV%) (Table 6). The stem diameters of the alfalfa cultivars also may vary in different locations [39]. The average thickness of the stems of all populations was similar in the acidic and neutral soils, 2.9 and 3.0 (mm), respectively. Tucak et al. (2014) [8] found that the average stem thickness of all populations was 2.08 mm. In our study, population 3132 was similar in stem thickness compared to the standard cultivar Birutė in the acidic soil. However, the stem diameter of population 3056 was 1.7-fold lower compared to the cultivar Birutė in the acidic soil (Table 6).
Lakić et al. (2019) [3] argued that the stem diameter of the alfalfa genotypes has a significant impact on the yield of the biomass. However, an increased stem thickness may have an adverse effect on the quality of the biomass and forage yield. Geleti et al. (2014) [37] argued that the leaf–stem ratio of alfalfa plants was associated with the height of plants. In our study, the fresh and dry matter yields varied between experimental sites due to the contrasting environmental conditions during the vegetation period of the alfalfa populations. In the acidic and neutral soil, due to the weather conditions, the alfalfa crop populations had a high overground mass. Additionally, the populations differed by stem thickness, which varied between populations, and was influenced by the fresh and dry matter yields. Significant correlation coefficients were found between the fresh matter yields and stem thickness in different years (FMY19 × ST19—r = −0.461, p < 0.05; FMY19 × ST20—r = −0.469, p < 0.05; FMY20 × ST19—r = −0.572, p < 0.01; FMY20 × ST21—r = 0.69, p < 0.01). The fresh matter yield of the alfalfa populations influenced the dry matter yield. Strong positive correlation coefficients were also found between the fresh matter yield and the dry matter yield in each year (FMY19 × DMY19—r = 0.96, p < 0.01, FMY20 × DMY20—r = 0.866, p < 0.01; FMY21 × DMY21—r = 0.549, p < 0.01) (Table 7). In addition, in the neutral soil, the fresh matter yield was dependent on the stem thickness. A correlation coefficient was found between the fresh matter yield and stem thickness in 2020 (FMY20 × ST20—r = −0.755, p < 0.05). Strong positive correlation coefficients were also found between the fresh and dry matter yields (FMY21 × DMY20—r = 0.669, p < 0.01; FMY19 × DMY19—r = −0.959, p < 0.01; FMY20 × DMY20—r = −0969, p < 0.01; FMY21 × DMY21—r = −0.976, p < 0.01). In acidic soil, the dry matter yield depended on the stem thickness in the different experimental years. The positive and negative correlation coefficients were detected between the dry matter yield and stem thickness in different years (DMY19 × ST20—r = −0.53, p < 0.05; DMY19 × ST21—r = −0.423, p < 0.05; DMY20 × ST21—r = 0.729, p < 0.01; DMY21 × ST19—r = 0.437, p < 0.05) (Table 7). In neutral soil, a strong negative correlation coefficient was found between the dry matter yield and stem thickness in 2020 (DMY20 × ST20—r = −0.741, p < 0.01). Finally, strong positive correlation coefficients were found between the dry matter yield in different years (DMY19 × DMY 20—r = 0.605, p < 0.05; DMY20 × DMY21—r = 0.697, p < 0.05) (Table 7).
The direct and indirect effects of phenotypic correlation were determined between the leaf–stem ratio and fresh forage yields [40]. In our study, we found that the dry matter yield was lower depending on the leaf weight in the acidic soil. Significant negative correlation coefficients were found between the leaf weight and dry matter yield (DMY19 × LW20—r = −0.423, p < 0.05; DMY20 × LW20—r = −0.463, p < 0.05). In the acidic soil, the correlation coefficients were more significantly different between agro-biological traits, such as stem thickness, stem weight, leaf weight, and inflorescence weight. Low positive and negative correlation coefficients were found between the stem thickness and other traits: ST21 × ST19—r = 0.491, p < 0.05; ST20 × IW19—r = 0.474, p < 0.01; ST20 × SW20—r = 0.452, p < 0.05. Significant positive and negative correlation coefficients were found between the leaf weight and other traits: LW19 × IW19—r = −0.54, p < 0.01; LW19 × SW21—r = 0.818, p < 0.01; LW19 × ST19—r = 0.445, p < 0.05; LW20 × IW20—r = 0.595, p < 0.01; LW21 × IW20—r = 0.469, p < 0.05; LW21 × SW20—r = 0.776, p < 0.01. Positive and negative correlation coefficients were found between the stem weight and other traits: SW19 × IW21—r = −0.643, p < 0.01; SW19 × ST21—r = −0.567, p < 0.01; SW21 × IW19—r = −0.523, p < 0.05; SW21 × IW21—r = 0.569, p < 0.01 (Table 7). In the neutral soil, the alfalfa plant crops with coarser and larger leaves dominated, and their stems varied from thin to thick. Positive and negative strong correlation coefficients were found between the stem thickness and the inflorescence weight (ST19 × IW19—r = −0.742, p < 0.01, ST21 × IW19—r = 0.787, p < 0.01). Positive and negative correlation coefficients were found between the leaf weight and other traits: LW19 × IW19—r = −0.566, p < 0.05; LW19 × SW21—r = 0.825, p < 0.01; LW19 × ST21—r = −0.706, p < 0.05; LW20 × IW20—r = 0.584, p < 0.05; LW21 × SW20—r = 0.777, p < 0.01. Finally, a strong negative correlation coefficient was found between the stem weight and the inflorescence weight (SW19 × IW21—r = −0.787, p < 0.01) (Table 7).

3.2. The Seed Yield of Alfalfa Populations

Khasanov et al. [41,42] suggested that one of the most acute problems in alfalfa growing is the generation of stable seed yields. Alfalfa is a cross-pollinated crop, and the optimum production of seed depends upon the activity of pollinators [43]. Moreover, the seed yield depends on the weather conditions during seasons, especially during the flowering and ripening stages [44,45]. Naydovich and Popova (2015) [46] argued that the seed yield depends on the temperature, amount of precipitation, and air humidity. Additionally, in our study, the significant (p < 0.05) influence of the year was determined for seed yield in acidic and neutral soils (Table 2). Sengul (2006) [47] evaluated the effect of genotype × environment interaction on the seed yield production of alfalfa. In our study, the population interaction with the year was highly (p < 0.05) significant for seed yield in acidic soil. During three growing years, due to changes in temperature and rainfall, environmental conditions were quite variable, especially during flowering and pod formation (June and July) (Figure 1). The growing season in 2019 was very warm and dry, and the seed yield was the highest in the acidic and neutral soils, 329.2 kg ha–1 and 658.0 kg ha–1, respectively, in comparison to the two other experimental years 2020 and 2021 (Table 8). However, the populations of alfalfa reacted strongly to the weather conditions and low pH of the soil. The seed yield was 328.8 kg ha−1 lower in the acidic soil (pH 4.4) compared to the neutral soil (pH 7.0). In 2020, due to the rainy and warm weather conditions and different environmental conditions of soils, the seed yield was lower by 186.6 kg ha–1 and 219.3 kg ha–1, respectively, in the acidic and neutral soils compared with 2019 (Table 8).
In 2021, the weather conditions were favourable for seed yields because very warm and hot weather conditions prevailed during the vegetation period of alfalfa populations, especially during the period of formatting and ripening pods. However, the seed yield was low due to the fact that rainy and windy weather occurred during seed harvesting time. The seed yields were very low in the acidic soil. In addition, the seed yield was lower in the neutral soil, compared with 2019 and 2020, by 307.1 kg ha–1 and by 87.8 kg ha–1, respectively (Table 8). Bakheit et al. (2017) [48] estimated the stability parameters of alfalfa seed yield and the components of the seed. These authors also selected populations that differed by these traits under different environmental conditions. Mamalyga et al. [49] investigated the parent material resistant to high soil acidity and selected the most promising cultivars of alfalfa, those with the highest adaptive potential, and utilized them as donors for creating highly productive hybrid populations resistant to soil acidity. In our study, the developed populations varied widely by the seed yield, with high coefficients of variation established in the acidic soil in 2019 and 2020 and in the neutral soil in 2019, 2020, and 2021 (Table 8). In 2019, the seed yield of populations 3131 and 3057 was the highest (498.8 kg ha–1 and 1115.2 kg ha–1) in the acidic and neutral soils compared with other populations. The seed yield of populations 3057, 3058, 3060, 3132, 3130, and 3129 was lower on average by 167.1 kg ha–1, and the seed yield of populations 3056, 3061, and 3086 was lower by 66.8 kg ha–1, 316.9 kg ha–1, and 279.6 kg ha–1, respectively, compared to population 3131 in the acidic soil. However, population 3131 had 115.3 kg ha–1 more seed yield compared to the standard cultivar Birutė. In 2020, population 3057 had the highest seed yield in the acidic and neutral soils, 309.2 kg ha–1 and 743.5 kg ha–1, respectively. However, the seed yield of population 3057 was 171.4 kg ha–1 higher in the acidic soil compared with the seed yield of cultivar Birutė. In 2021, the populations’ yields were similar to the seed yield in the acidic soil. Moreover, the seed yield of populations from 2019 through 2021 was similar in the neutral soil. In 2021, population 3086 had the highest seed yield (504.2 kg ha–1) which was 153.3 kg ha–1 higher compared to the average seed yield (Table 8).
Wang et al. (2016) [50] argued that the seed yield of alfalfa genotypes is dependent on the weather conditions, and the seed crops of populations were lush and easily lodged by the rainfall. In addition, correlation coefficients between pods per raceme and flower per raceme had a highly significant and positive direct effect on seed yield. In our study, we found that the seed yield depended on contrasting weather conditions which influenced seed yields each year. In acidic soil, the alfalfa population plants had thicker stems and many inflorescences (Table 6). The seed crops of the populations were less during the warm and dry vegetation period of 2019 and 2021, and seed harvesting was easier compared with the rainy and warm period of 2020. A significant negative correlation coefficient was shown between the seed yield and stem thickness r = −0.74, p < 0.01 (Table 7).

4. Conclusions

The populations that were developed for tolerance to mobile Al toxicity under laboratory conditions showed significant differences in the seed, fresh and dry matter yields, stem thickness, stem weight, leaf weight, and inflorescence weight under field conditions in acidic soil with a pH of 4.4. The populations were more stable in terms of stem weight and had a high diversity of leaves and inflorescences as shown by the correlation coefficients between agro-biological traits and productivity traits. These results occurred due to the fact that the populations grew on acidic soils with low toxicity concentrations of mobile aluminium. In the acidic soil, the populations 3056, 3132, 3130, and 3058 yielded more fresh and dry matter compared to the standard cultivar Birutė in the period from 2019 to 2021. In the acidic soil, populations 3131 and 3057 had a higher seed yield compared to cultivar Birutė in 2019 and 2020, respectively. Population 3086 significantly differed by leaf weight compared to the cultivar Birutė, and population 3132 and cultivar Birutė had a similar stem thickness and fresh matter yield. In the neutral soil with a pH of 7.0, the populations were similar in fresh matter, dry matter, and seed yields. Furthermore, alfalfa crops were characterised by a diversity of stems, ranging from smaller to larger stems, which resulted in lower stem weights compared to the stems from acidic soils. However, the alfalfa populations had large leaves and a wide variety of inflorescences. In the neutral soil, population 3056 yielded more fresh matter compared to cultivar Birutė.

Author Contributions

R.S. and A.L. conceived and designed the experiment, performed the experiments, analysed the data, prepared figures and tables, and wrote and reviewed drafts of the paper; G.P. performed the statistical analysis and prepared figures and tables; R.S., A.L. and G.P. reviewed drafts of the paper and approved the final draft. 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.

Data Availability Statement

Not applicable.

Acknowledgments

The paper presents research findings obtained through the long-term research programme ‘Genetics, biotechnology and breeding for plant biodiversity and innovative technologies’ implemented by the Lithuanian Research Centre for Agriculture and Forestry.

Conflicts of Interest

The authors declare no conflict of interest.

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Agronomy 13 00156 g001 550
Figure 1. The meteorological conditions of the experimental sites from 2019 to 2021 (data from the Vėžaičiai and Dotnuva, Automatical Meteorological Station). (A) The western region of Lithuania and (B) the central region of Lithuania.
Figure 1. The meteorological conditions of the experimental sites from 2019 to 2021 (data from the Vėžaičiai and Dotnuva, Automatical Meteorological Station). (A) The western region of Lithuania and (B) the central region of Lithuania.
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Agronomy 13 00156 g002 550
Figure 2. Comparison of stem weight (SW), leaf weight (LW), and inflorescence weight (IW) mean values of alfalfa populations grown on acidic and alkaline soil. Vertical dashes indicate the mean of standard error.
Figure 2. Comparison of stem weight (SW), leaf weight (LW), and inflorescence weight (IW) mean values of alfalfa populations grown on acidic and alkaline soil. Vertical dashes indicate the mean of standard error.
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Table
Table 1. The development of alfalfa populations by crossing combinations with the accessions of different tolerance indices to acidic soil.
Table 1. The development of alfalfa populations by crossing combinations with the accessions of different tolerance indices to acidic soil.
No.Number of PopulationYearCrossing Combination
1.30562008cv. Augūnė (M. sativa) × PGR12410 (M. sativa)
2.30572008cv. Augūnė (M. sativa) × No.12835 (M. sativa)
3.30582008cv. Augūnė (M. sativa) × No.12991 (M. sativa)
4.30592008cv. Augūnė (M. sativa) × PGR12425 (M. sativa)
5.30602008cv. Žydrūnė (M. varia) × PGR12410 (M. sativa)
6.30612008cv. Žydrūnė (M. varia) × No.12835 (M. sativa)
7.31312009cv. Antanė (M. sativa) × PGR12410 (M. sativa)
8.31322009cv. Antanė (M. sativa) × No.12835 (M. sativa)
9.31302009cv. Antanė (M. sativa) × No.12991 (M. sativa)
10.31292009cv. Malvina (M. sativa) × No.12835 (M. sativa)
11.30862009cv. Malvina (M. sativa) × PGR12410 (M. sativa)
Name of accessionsGRIN codeTolerance index Country of origin
CN39465PI 4679011.37USA, North Dakota
No.12835PI 2121041.39Afghanistan
No.12991PI 2116091.51Afghanistan
CN39479PI 4679161.55USA, Nebraska
Table
Table 2. Sites’ characteristics.
Table 2. Sites’ characteristics.
IndicesExperimental Site
Experiment Site IExperiment Site II
Pedological indices
Soil typeRetisolCambisol
Soil textureLoamLoam
Sand, %46.949.0
Silt, %45.137.5
Clay, %8.013.5
pHKCl4.47.0
Mobile Al mg kg−11.78–23.410.00
Mobile P2O5 mg kg−1177–335201–70
Mobile K2O mg kg−1195–234101–175
Ntotal, %0.12–0.140.14–0.16
Climatic indices (SRC 1990–2020)
Total annual precipitation, mm914.8566.0
Annual mean temperature, °C7.47.5
Growing season’s total precipitation, mm436.2327.0
Growing season’s mean air temperature, °C13.614.3
Note. SRC—The standard rate of climate; growing seasons from 4 to 9 months.
Table
Table 3. The ANOVA results by year under different experimental sites and their effect on seed yield and fresh matter and dry matter yields.
Table 3. The ANOVA results by year under different experimental sites and their effect on seed yield and fresh matter and dry matter yields.
Source of
Variation		Degree of FreedomMean
Squares		p-ValueDegree of FreedomMean Squaresp-Value
Acid Soil (pH 4.4)Neutral Soil (pH 7.0)
Seed yield, kg ha−1
Population (A)1115,821.60.001311124,654.00.0130
Year (B)21,066,1400.000021,181,7300.0000
A × B2223,129.50.00002237,469.00.7917
Fresh matter yield, t ha−1
Population (A)11609.40.000011748.20.0263
Year (B)26655.50.0000215,939.00.0000
A × B22436.40.000022199.50.9202
Dry matter yield, t ha−1
Population (A)1123.90.00001149.60.0007
Year (B)2739.40.00002252.20.0000
A × B2243.40.00002211.00.7635
Table
Table 4. The fresh matter yield (t ha–1) of alfalfa populations under different experimental sites (I and II).
Table 4. The fresh matter yield (t ha–1) of alfalfa populations under different experimental sites (I and II).
PopulationAcidic Soil (4.4 pH)Neutral Soil (7.0 pH)
201920202021201920202021
Birutė92.3 h106.6 f80.3 b114.4 a113.7 a95.8 ab
305695.0 h94.7 d80.3 b118.2 a128.9 a99.8 b
305770.3 d93.0 d85.7 c107.8 a106.3 a73.3 ab
305843.3 a89.7 c95.0 e110.2 a117.4 a74.9 ab
305956.7 b93.0 d79.7 b117.6 a124.9 a88.4 ab
306075.7 e93.0 d73.7 a110.2 a117.6 a92.2 ab
306159.3 c74.7 a93.7 d122.5 a114.4 a86.7 ab
313170.7 d94.7 d99.7 f118.0 a111.9 a66.7 a
313278.3 f106.3 f101.0 g118.2 a100.2 a71.8 ab
313071.3 d106.3 f106.3 h99.1 a101.5 a66.9 a
312980.0 g99.7 e86.3 c106.9 a129.8 a84.7 ab
308677.7 f86.3 b86.3 c108.4 a100.2 a77.3 ab
Mean72.694.889.0112.6113.981.5
SEM4.22.72.91.93.03.3
CV%20.09.811.35.99.213.8
Note. Averages followed by the same letter in a column do not differ from each other according to Tukey’s test, significance at p < 0.05; SEM—standard error of the mean; CV%—variation coefficient.
Table
Table 5. The dry matter yield (t ha–1) of alfalfa populations at different experimental sites (I and II).
Table 5. The dry matter yield (t ha–1) of alfalfa populations at different experimental sites (I and II).
PopulationAcidic Soil (pH 4.4)Neutral Soil (pH 7.0)
201920202021201920202021
Birutė25.6 h27.5 f24.3 e24.0 a22.3 a22.6 a
305623.3 h23.2 b20.7 a25.6 a26.1 a24.0 a
305718.7 e27.6 f24.7 e23.3 a20.8 a18.3 a
305811.4 a26.0 d28.3 g24.4 a23.8 a19.3 a
305915.5 b28.4 g22.6 d26.5 a25.8 a22.0 a
306017.2 c25.9 d20.7 a24.5 a23.3 a23.5 a
306115.4 b20.8 a26.1 f27.0 a23.2 a21.0 a
313118.6 e26.4 de21.3 b25.8 a23.6 a16.1 a
313220.6 f32.2 i24.5 e25.6 a20.2 a17.7 a
313017.8 d29.7 h24.7 e21.8 a18.6 a15.7 a
312920.8 f26.9 ef22.4 d24.0 a26.1 a22.0 a
308622.8 g24.2 c22.1 c23.0 a19.1 a19.3 a
Mean19.026.623.524.622.720.1
SEM1.10.90.70.40.80.8
CV%20.711.29.86.211.514.0
Note. Averages followed by the same letter in a column do not differ from each other as determined by Tukey’s test, significance at p < 0.05; SEM—standard error of the mean; CV%—variation coefficient.
Table
Table 6. The mean values of stem thickness, stem weight, leaf weight, and inflorescence weight under different experimental sites (I and II).
Table 6. The mean values of stem thickness, stem weight, leaf weight, and inflorescence weight under different experimental sites (I and II).
PopulationST (mm)SW (g)LW (g)IW (g)
Acidic Soil
(pH 4.4)		Neutral Soil (pH 7.0)Acidic Soil
(pH 4.4)		Neutral Soil (pH 7.0)Acidic Soil
(pH 4.4)		Neutral Soil (pH 7.0)Acidic Soil
(pH 4.4)		Neutral Soil (pH 7.0)
Birutė3.8 c2.7 a185.3 a191.3 a90.6 a94.0 a9.4 a9.4 a
30562.3 a2.7 a184.3 a159.2 a104.7 ab107.2 a10.5 a6.8 a
30572.7 abc2.8 a189.7 a149.1 a103.0 ab92.6 a6.9 a4.6 a
30583.1 abc3.0 a196.0 a169.9 a112.3 ab96.2 a7.0 a5.5 a
30592.8 abc3.0 a208.0 a148.2 a112.3 ab97.1 a7.0 a4.8 a
30602.6 abc2.9 a193.6 a151.0 a103.1 ab91.4 a5.1 a3.7 a
30612.9 abc3.0 a191.8 a155.2 a103.3 ab107.5 a7.0 a8.3 a
31312.8 abc2.9 a204.2 a138.8 a103.1 ab100.5 a10.0 a9.1 a
31323.4 c3.0 a200.0 a160.5 a98.8 ab103.1 a7.8 a5.2 a
31303.3 bc3.2 a180.5 a141.2 a100.5 ab92.0 a9.5 a6.2 a
31292.5 ab2.9 a182.3 a160.2 a108.2 ab115.3 a5.6 a6.9 a
30862.9 abc3.3 a184.6 a156.8 a132.3 b108.0 a5.5 a9.0 a
Mean2.93.0191.7156.8106.0100.47.66.6
SEM0.10.12.64.02.92.30.50.6
CV%14.36.14.78.99.67.824.229.4
Note. Averages followed by the same letter in a column do not differ from each other according to Tukey’s test, significance at (p < 0.05); SEM—standard error of the mean; CV%—variation coefficient; ST—stem thickness; SW—stem weight; LW—leaf weight; IW—inflorescence weight.
Table
Table 7. The correlation coefficients between productivity traits and stem thickness, stem weight, leaf weight, and inflorescence weight of alfalfa populations from 2019 to 2021.
Table 7. The correlation coefficients between productivity traits and stem thickness, stem weight, leaf weight, and inflorescence weight of alfalfa populations from 2019 to 2021.
Acidic Soil (pH 4.4)
Trait PairrTrait PairrTrait Pairr
SY21 × ST20−0.74 **DMY20 × LW20−0.463 *LW21 × IW200.469 *
FMY19 × ST19−0.461 *DMY21 × ST190.437 *LW21x SW200.776 **
FMY19 × ST20−0.469 *ST21 × ST190.491 *SW19 × IW21−0.643 **
FMY20 × ST19−0.572 **ST20 × IW19−0.474 **SW19 × ST21−0.567 **
FMY20 × ST210.69 **ST20 × SW20−0.452 *SW21 × IW19−0.523 *
DMY19 × ST20−0.53 *LW19 × IW19−0.544 **SW21 × IW210.569 **
DMY19 × ST21−0.423 *LW19 × SW210.818 **FMY19 × DMY 190.96 **
DMY19 × LW200.423 *LW19 × ST190.445 *FMY20 × DMY200.866 **
DMY20 × ST210.729 **LW20 × IW 200.595 **FMY21 × DMY210.549 **
Neutral soil (pH 7.0)
Trait pairrTrait pairrTrait pairr
FMY20 × ST20−0.755 **LW20 × IW200.584 *FMY21 × DMY200.669 *
DMY20 × ST20−0.741 **LW21x SW200.777 **DMY19 × DMY200.605 *
ST19 × IW19−0.742 **SW19 × IW21−0.667 *DMY20 × DMY210.697 *
LW19 × IW19−0.566 *ST21 × IW190.787 **FMY19 × DMY 190.959 **
LW19 × SW210.825 **FMY20 × FMY210.74 **FMY20 × DMY200.969 **
LW19 × ST21−0.706 *FMY20 × DMY210.767 **FMY21 × DMY210.976 **
Note. SY—seed yield (kg ha–1); FMY—fresh matter yield (t ha–1); DMY–dry matter yield (t ha–1); ST—stem thickness; SW—stem weight; LW—leaf weight; IW—inflorescence weight; * significance at (p < 0.05); ** significance at (p < 0.01).
Table
Table 8. The seed yield (kg ha−1) under different experimental sites (I and II).
Table 8. The seed yield (kg ha−1) under different experimental sites (I and II).
PopulationAcidic Soil (pH 4.4)Neutral Soil (pH 7.0)
201920202021201920202021
Birutė383.5 abc137.8 abc15.0 a520.2 a346.8 a348.0 a
3056432.3 bc58.1 a15.3 a746.0 a497.3 a406.9 a
3057271.5 abc309.2 c15.0 a1115.2 a743.5 a311.1 a
3058324.1 abc68.4 a15.0 a653.6 a435.7 a304.2 a
3059243.8 ab269.5 bc14.3 a534.0 a356.0 a244.9 a
3060375.4 abc167.5 abc14.0 a625.0 a416.6 a384.7 a
3061181.9 a102.4 ab13.7 a543.6 a362.4 a296.7 a
3131498.8 c164.7 abc14.3 a608.3 a405.5 a469.3 a
3132314.0 abc139.0 abc14.7 a727.3 a484.9 a281.8 a
3130318.2 abc79.6 a13.2 a465.4 a310.3 a348.2 a
3129387.2 abc93.4 ab14.0 a608.8a405.9 a311.1 a
3086219.2 ab129.3 ab13.7 a749.1 a499.4 a504.2 a
Mean329.2143.414.4658.0438.7350.9
SEM26.522.30.249.332.922.4
CV%27.954.04.625.925.922.1
Note. Averages followed by the same letter in a column do not differ from each other as determined by Tukey’s test, significance at (p < 0.05); SEM—standard error of the mean; CV%—variation coefficient.
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Skuodienė, R.; Liatukienė, A.; Petrauskas, G. Comparison of Productivity and Agro-Biological Traits of Alfalfa Populations Resistant to Mobile Al Grown on Acidic and Neutral Soils. Agronomy 2023, 13, 156. https://doi.org/10.3390/agronomy13010156

AMA Style

Skuodienė R, Liatukienė A, Petrauskas G. Comparison of Productivity and Agro-Biological Traits of Alfalfa Populations Resistant to Mobile Al Grown on Acidic and Neutral Soils. Agronomy. 2023; 13(1):156. https://doi.org/10.3390/agronomy13010156

Chicago/Turabian Style

Skuodienė, Regina, Aurelija Liatukienė, and Giedrius Petrauskas. 2023. "Comparison of Productivity and Agro-Biological Traits of Alfalfa Populations Resistant to Mobile Al Grown on Acidic and Neutral Soils" Agronomy 13, no. 1: 156. https://doi.org/10.3390/agronomy13010156

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