A field experiment was conducted in an area with saline sandy loam soil in the Hohhot district (111°45′E, 40°36′N) on the Tumochuan plain, China, during two consecutive alfalfa growing seasons: 2019 and 2020. The site has a typical continental climate with mean annual air temperature of 7.6°C and mean annual maximum and minimum air temperatures of 23.3°C (July) and −11.0°C (January), respectively. The mean annual precipitation is 392.6 mm (average values for 1981–2010), and around 74.8% of the precipitation occurs between July and September. The potential annual evaporation is about 1757.1 mm. Mean annual sunshine exceeds 2829.8 h, and the frost-free period is about 137 d (range, 99 d to 183 d). The distribution of precipitation in 2019 and 2020 is shown in Fig. 1.
The properties of the background surface soil (0–15 cm) were as follows: 15.9 g kg-1 soil organic matter (SOM), 930 mg kg-1 total N, 14 mg kg-1 available phosphorus (P), and 225 mg kg-1 available potassium (K), with an ECe (electrical conductivity of a saturated soil extract) of 15.8 dSm-1 in spring and with an ECp (electrical conductivity of pore water) of 1.1dSm-1 in early fall. Alfalfa seeds were sown in early August (fall) in 2019.
Experimental Design and Field Management
The cold-tolerant alfalfa cultivar Medicago sativa L. cv. “Zhongcao NO.3”, bred by Linqing Yu, Chinese Academy of Agricultural Sciences, was selected for this study, as it is widely cultivated on the Inner Mongolia plateau in China. The experiment comprised two cultivation systems: furrow-bed seeding (FU) (cultivation with ridges and furrows) and flat-bed seeding (FL) (conventional flat cultivation without ridges). The experiment had a completely randomized block design with four replicates. Each plot was 20.0-m long and 3.2-m wide. Alfalfa seeds were planted on 8 August 2019 using the drill planting method with a hand-pushed vegetable planter. For the FU treatment, the width of the ridges and the furrows was 35 cm and 5 cm, respectively, and the ridge height was 15 cm. The furrows were leveled as planting belts (Fig. 2). The ridge and furrow were made using a tiny furrow machine and the ridges were compacted using a roller. Alfalfa seeds were drill-sown in the furrows in the FU system and then covered with 1 cm soil. All the planting rows in both FU and FL systems had a north-south orientation with 40-cm spacing between adjacent rows. Weeds were controlled manually, with care taken not to destroy the ridge soil crust. Alfalfa plants were harvested manually in 2020.
The alfalfa plants in the plots were not irrigated in 2019 because rainfall was sufficient that year, but were irrigated three times at key stages of growth in 2020. Other field management was conducted according to local agronomic practices.
Data were collected for rainfall, soil temperature, soil salinity, soil moisture content, seedling emergence number, soil bacterial diversity, soil properties, plant height, plant yield, shoot sodium (Na+)concentration, shoot K+ concentration, shoot calcium (Ca2+) concentration, and plant nutritional components.
Rainfall at the experimental site was measured using an automatic weather station (WSSTD1, Campbell Scientific, Loughborough, UK). The number of emerged seedlings (number of alfalfa seedlings at the cotyledon stage) was counted in five 100-cm-long seed-row sections and the average number per 100-cm-long seed-row in each plot at four, six, and nine days after seeding (DAS) was calculated. The soil moisture content, salinity, and temperature during the seedling stage at four, six, and nine DAS were determined by analyzing 10 surface (0–10 cm) soil samples with a HH2 Moisture Meter and a WET-2 sensor (Delta-T Devices Ltd. Cambridge, United Kingdom) (Kargas et al. 2011). For analyses of the soil bacterial community, five surface (0–15 cm) soil samples were collected from random positions along the crop row from each plot in both systems on 9 DAS. The soil samples from each plot were homogenized to form a composite sample and sieved through a 2 mm sieve to remove rocks and roots. A subsample was immediately stored at −80°C until use in molecular analyses.
For determination of the properties of the soil before the experiments started, ten soil cores were collected from random positions in the experimental field. For determination of soil salinity and the contents of SOM, total N, available P, and available K during the experiment, five soil cores were collected from random positions along the crop row to a depth of 15 cm from both the FU and FL treatment in the spring of 2020 when the alfalfa plants had just turned green. The soil samples from each plot were homogenized to form a composite sample. Subsamples were air-dried, ground, and passed through a 2-mm sieve, then used for analyses of soil salinity, SOM, available K, available P, and total N. Soil was mixed with water (1:5 soil to water ratio) to determine soil salinity. Soil chemical characteristics were tested following the method described by Bao(2018).
Plant height was measured five times from Oct 17, 2019 to Jul 3, 2020. At each measurement time, 20 plants were selected from each plot and the height was measured and the average height of alfalfa were used. In 2020, the yield of the first cut of alfalfa was measured. Alfalfa plants were cut in a 1-m long part of the row, with three replicates per plot. The average yield from plants in 1 m was calculated, and used to estimate the yield per hectare. The harvested material was dried at 65°C for 48 h and then weighed to determine dry matter content. Then, the dried samples were ground to pass through 1-mm screen using a laboratory knife mill (FW100, Taisite Instruments, Tianjin, China) for later analysis. Neutral detergent fiber (NDF) (Van Soest et al. 1991) and acid detergent fiber (ADF) (Robertson and Van Soest 1981) were measured using an ANKOM fiber analyzer (ANKOM2000; Macedon, NY, USA). Crude ash (ash) content was determined by burning samples in a muffle furnace at 500°C for 5 h and then weighing the residue . Total nitrogen (total N) content was determined by the Kjeldahl procedure (Krishnamoorthy et al., 1982); crude protein (CP) was determined by multiplying the total N by 6.25. Ions were extracted by shaking ground leaf samples in 0.5 M HNO3 in vials for 48 h. Then, the diluted extracts were analyzed to determine their Na+, K+ and Ca2+ contents using an M410 flame photometer (Sherwood, Cambridge, UK).
DNA was extracted from 0.25 g soil using an E.Z.N.A.®Soil DNA Kit (Omega Biotek, Norcross, GA, USA) according to the manufacturer’s instructions. The reagents in this kit were designed to isolate DNA from trace amounts of sample, and are effective for isolating DNA from most bacteria. Nucleic acid-free water was used as the blank. The total DNA was eluted in 50 µL elution buffer and stored at −80°C until PCR analyses by the LC-Bio Technology Co., Ltd (Hang Zhou, Zhejiang Province, China).
PCR Amplification and 16S rDNA Sequencing
The V3–V4 region of the prokaryotic (bacterial and archaeal) small-subunit 16S rDNA gene was amplified with slightly modified versions of the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). The 5' ends of the primers were tagged with specific barcodes for each sample and universal sequencing primers.
Each PCR amplification reaction mixture contained 25 ng template DNA, 12.5 µL PCR premix, 2.5 µL each primer, and PCR-grade water to complete the volume to 25 µL. The thermal cycling conditions to amplify the prokaryotic 16S fragments were as follows: initial denaturation at 98°C for 30 s; 35 cycles of denaturation at 98°C for 10 s, annealing at 54°C/52°C for 30 s, and extension at 72°C for 45 s; and then final extension at 72°C for 10 min. The PCR products were confirmed by 2% agarose gel electrophoresis. Throughout the DNA extraction process, ultrapure water, instead of a sample solution, was used to exclude the possibility of false-positive PCR results as a negative control. The PCR products were purified using AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA) and quantified by Qubit (Invitrogen, Carlsbad, CA, USA). The amplicons were prepared for sequencing using a Library Quantification Kit for Illumina (Kapa Biosciences, Woburn, MA, USA), and the size and quantity of the amplicon library were assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA, USA). The PhiX Control library (v3) (Illumina) was combined with the amplicon library (expected at 30%). The libraries were sequenced with 300PE MiSeq runs. One library was sequenced with both protocols using standard Illumina sequencing primers, eliminating the need for a third (or fourth) index read.
Samples were sequenced on the Illumina MiSeq platform according to the manufacturer’s recommendations (LC-Bio). Paired-end reads were assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequences. Paired-end reads were merged using FLASH. Quality filtering of the raw tags was performed under specific filtering conditions to obtain high-quality clean tags according to FastQC (V 0.10.1). Chimeric sequences were filtered using Verseach software (v 2.2.4). Sequences with ≥97% similarity were assigned to each representative sequence using the RDP (Ribosomal Database Project) classifier. Differences in dominant species among different groups were detected and multiple sequence alignments were conducted using PyNAST software, which revealed the phylogenetic relationships among different operational taxonomic units (OTUs). Abundance information for OTUs was normalized using a standard sequence number corresponding to the sample with the least sequences. Alpha diversity was determined by calculating four indices (Chao 1, Shannon’s, Simpson’s and Observed species) using QIIME (V 1.8.0). Differences in beta diversity (species complexity) among samples were detected by a principle co-ordinates analysis (PCoA) conducted using QIIME (V 1.8.0).
One-way analysis of variance (ANOVA) was used to evaluate statistical significance of the effects of the two seeding patterns on soil properties, plant properties, relative abundance of dominant bacterial phyla, classes, and genera; bacterial community richness, diversity indices, and OTUs using SAS version 8.02 (SAS Institute, Cary, NC, USA). Unless otherwise stated, the significance level was P≤0.05. SigmaPlot was used to generate bar graphs. Pearson’s correlation analysis was performed to detect relationships among soil and plant properties and soil fungal abundance, diversity, and relative abundance of dominant bacteria phyla and classes using Systat version 12.0 (Systat Software Inc., Chicago, IL, USA)., and the results were plotted using SigmaPlot.