Optimizing Row Spacing and Seeding Rate for Yield and Quality of Alfalfa in Saline–Alkali Soils

Abstract

To elucidate the photosynthetic physiological mechanisms influencing alfalfa (Medicago sativa L.) yield and quality under varying planting densities, the cultivar ‘Zhongmu No.1’ was used as experimental material. The effects of different row spacing (R1, R2, R3) and seeding rate (S1, S2, S3, S4, S5) combinations on chlorophyll content (ChlM), nitrogen flavonol index (NFI), chlorophyll fluorescence parameters, forage quality, and hay yield were systematically analyzed. Results showed that alfalfa under R1S3 treatment achieved peak values for ChIM, NFI, EE, and hay yield, whereas R1S4 treatment yielded the highest Fv/Fm and CP content. Redundancy analysis further indicated that yield was most strongly associated with ChlM, NFI, Y (II), and qP. Y (II), and qP significantly influenced alfalfa forage quality, exerting negative effects on ADF and NDF, while demonstrating positive effects on CP and EE. In conclusion, narrow row spacing (15 cm) with moderate seeding rates (22.5–30 kg·hm⁻²) optimizes photosynthetic performance while concurrently enhancing both productivity and forage quality in alfalfa cultivated, establishing a theoretical foundation for photosynthetic regulation in high-quality and high-yield alfalfa cultivation.

1. Introduction

Soil salinization is a global ecological challenge that imposes severe constraints on crop growth and productivity [1,2]. Among forage crops, alfalfa (Medicago sativa L.) is an important perennial leguminous species worldwide, renowned for its high digestibility, abundant amino acids, and elevated protein content, surpassing many other legumes in nutritional value [3,4]. Due to these attributes, alfalfa is often known as the “Queen of Forages” [5]. Meanwhile, alfalfa also exhibits strong adaptability to saline–alkali soils [6], sustaining high yields when the electrical conductivity (EC) of the soil plow layer is maintained at 6 mS cm⁻¹ [7], and can even withstanding short-term exposure to salinity levels up to 10 mS cm⁻¹ [8]. In regions such as the coastal saline–alkali lands of Hebei Province, where soil salinity is high, structure in poor, and freshwater resources are scarce, the efficiency of traditional crop production is significantly limited [9]. In this context, developing the alfalfa industry in these areas is an important method to solve the grass–grain land competition conflict and to promote sustainable utilization of saline–alkali soils.

In alfalfa production, both yield and quality are of paramount importance, as they jointly determine forage dry matter accumulation and nutrient value [10]. Optimizing planting density—particularly through appropriate row spacing and seeding rate—is a key agronomic practice for achieving high yield and superior forage quality. Such configurations affect canopy structure and light interception efficiency, ultimately affecting crop productivity [11]. Studies have shown that at lower seeding rates, individual plants grow more robustly, yet total biomass may decline due to sparse canopy structure and reduced leaf area [12]. In contrast, overly dense planting may lead to light deficiency in lower canopy layers, where photosynthetic rates fall below respiration, turning these leaves into net carbon consumer [13]. Additionally, excessive density impairs ventilation, lowers inter-canopy CO₂ concentration, and diminishes CO₂ absorption, further weakening photosynthesis and accelerating leaf senescence, ultimately reducing yield [14,15]. Nevertheless, how row spacing and seeding rates photosynthetically regulate alfalfa yield remains poorly characterized.

Alfalfa is a high-protein forage crop. Through photosynthesis, its leaves convert water and CO₂ into sugars and other organic compounds, which are then used to synthesize proteins and other essential nutrients that support plant growth [16]. Insufficient daily light exposure can reduce photo-assimilate production and sucrose synthesis, resulting in a lower soluble sugars [17]. Previous studies have investigated the effects of seeding rate and row spacing configurations on alfalfa yield [18], yet lack in-depth exploration of nutritional quality. Therefore, elucidating the physiological mechanisms by which photosynthesis drives both yield and quality under varying planting densities holds significant practical implications.

Photosynthesis involves a series of intricate photophysical and photochemical reactions, during which part of the absorbed light energy is dissipated as fluorescence [19,20]. Chlorophyll fluorescence has emerged as a sensitive and non-destructive tool for studying plant photosynthetic performance, allowing rapid and precise assessment of chloroplast function, photosynthetic efficiency, and photosystem activity under varying cultivation conditions [21,22]. Despite previous studies investigating planting density in various crops [23,24], few have integrated chlorophyll fluorescence and photosynthetic parameters to evaluate their physiological contribution to yield and quality in alfalfa, especially under saline–alkali dryland conditions. This study aims to fill that gap.

The objective of this study is to elucidate how planting density, through different row spacing and seeding rate combinations, influences the chlorophyll fluorescence parameters, forage quality, and hay yield of alfalfa in coastal saline–alkali dry lands. Specifically, we hypothesize that moderate seeding rates combined with narrow row spacing will optimize photosynthetic efficiency and enhance both yield and forage quality in alfalfa grown in saline–alkali soils.

2. Materials and Methods

2.1. Experiment Site Description

The experiment was conducted at the Cangzhou Comprehensive Experimental Station of National Forage Industry Technology System (E117°58′, N38°31′), located in Yangerzhuang Town, Huanghua City, Hebei Province. This region is part of the water-scarce, saline–alkali zone in the Bohai Rim, characterized by semi-humid, warm temperate continental monsoon climate. The area is characterized by hot, wet summers and cold, dry winters, with an average annual rainfall of 530 mm, most of which occurs between June and August. The average annual temperature is 15.7 °C, with a frost-free period of approximately 210 days. Prior to the trial, a soil salinity uniformity assessment was conducted across the designated plot area. Surface soil samples were collected using a grid sampling pattern and transported to the laboratory for analysis. Laboratory analysis indicated that the experimental soil was salinized soil with homogeneous salinity distribution. The soil exhibited a soluble salt content of 2.07 g·kg⁻¹ and a pH of 7.62. The topsoil contains 12.31 g·kg⁻¹ of organic matter, 19.71 mg·kg⁻¹ of available nitrogen, 146.04 mg·kg⁻¹ of available potassium, and 8.94 mg·kg⁻¹ of available phosphorus (

Table 1. Physicochemical properties of the experimental soil.

Point	SOM (g·kg−1)	AN (mg·kg−1)	AP (mg·kg−1)	AK (mg·kg−1)	pH	SSC (g kg−1)
1	11.79	16.10	8.60	149.60	7.64	1.88
2	14.60	12.60	6.70	166.80	7.66	1.97
3	11.18	21.50	7.80	130.20	7.60	2.40
4	13.78	10.30	9.90	141.00	7.82	2.47
5	12.47	18.80	10.10	146.00	7.52	2.22
6	13.06	23.10	9.50	148.40	7.42	1.94
7	11.13	25.70	9.60	139.80	7.56	1.82
8	11.61	16.90	8.10	146.00	7.65	2.10
9	11.35	29.70	9.60	140.20	7.58	2.02
10	12.10	22.40	9.50	152.40	7.74	1.84
Average	12.31 ± 1.11	19.71 ± 5.64	8.94 ± 1.04	146.04 ± 9.16	7.62 ± 0.11	2.07 ± 0.22

).

2.2. Experimental Design

The experiment was conducted using the ‘Zhongmu No.1’ alfalfa variety, which was sown in May 2020. Measurements and sampling were carried out during the initial flowering stage of the third-cut regrowth in July 2022. The experiment employed a split-plot design with row spacing as the main-plot factor and seeding rate as the subplot factor. Three levels of row spacing were tested: 15 cm (R1), 20 cm (R2), and 25 cm (R3), and five seeding rates were evaluated: 7.5 kg·hm⁻² (S1), 15 kg·hm⁻² (S2), 22.5 kg·hm⁻² (S3), 30 kg·hm⁻² (S4), and 37.5 kg·hm⁻² (S5). This factorial combination produced 15 treatment combinations, each replicated three times, yielding 45 experimental plots arranged in a randomized block design. Each plot measured 5 m in length and 4 m in width, with a 1 m buffer zone between plots. Seeding was performed manually using furrow-opening drilling, with a controlled seeding depth of 1.5–2.0 cm. The experiment was conducted under rain-fed dry land farming conditions, with supplemental irrigation or fertilization applied during the growing season.

Measurements of chlorophyll content, nitrogen-flavonol index (NFI), and chlorophyll fluorescence parameters were recorded at the initial flowering stage of the third regrowth cycle in July 2022. Following these assessments, alfalfa was harvested to measure yield. A representative subsample of 500 g of plant material was collected, cut into 2–5 cm segments, placed in kraft paper bags, and oven-dried for subsequent nutritional quality analysis.

2.3. Measurement Indicators and Methods

2.3.1. Photosynthetic Pigments

The central leaflet of the fourth fully expanded trifoliate leaf from the shoot apex was sampled for pigment analysis between 8:00 and 9:00 AM. Chlorophyll content (ChlM) and nitrogen-flavonol index (NFI) were determined using an in situ multi-pigment meter (MPM-100, Opti-Sciences Inc., Hudson, NY, USA). For each treatment, nine replicates were measured, and six stable readings were selected for statistical analysis.

2.3.2. Chlorophyll Fluorescence Parameters

Chlorophyll fluorescence parameters were measured using a portable pulse-amplitude-modulated fluorometer (PAM-2500, Walz, Effeltrich, Germany). Measurements were conducted during 08:30–11:30 and 15:00–17:30 on clear-sky days, with ambient air temperature maintained at 29 ± 2.5 °C throughout. One representative plant exhibiting uniform vigor was selected per experimental plot. Measurements were performed at a consistent leaf position (the fourth cluster from the apex). Before measurements commenced, calibration of the instrument was verified, and the optical fiber’s light-transmitting area was checked to ensure it exceeded 2/3. Leaves were dark-adapted for 30 min using leaf clips or controlled dark conditions. The actinic light intensity was set to 6 to stabilize the Y (II) at approximately 0.2, with readings recorded under a PAR intensity of 196 µmol m⁻²s⁻¹. The Slow Kinetics measurement program was initiated to record chlorophyll fluorescence parameters, which included the following: maximum photosynthetic efficiency (Fv/Fm), actual photosynthetic efficiency [Y (II)], quantum yield of regulated energy dissipation [Y (NPQ)], quantum yield of non-regulated energy dissipation [Y (NO)], non-photochemical quenching coefficient (qN), photochemical quenching coefficient (qP), and the apparent photosynthetic electron transfer rate (ETR) [25]. Following measurements, the data were inspected, and any questionable data points were re-measured.

2.3.3. Yield

To assess yield, border rows were removed, and the first 50 cm of row ends were discarded to eliminate edge effects. The remaining plants were harvested, and fresh weight (Fw) was recorded. A representative subsample (~500 g) was selected from the harvested material, oven-dried to constant weight, and ground for nutritional analysis.

The dry matter content was calculated, and the alfalfa hay yield D (t·hm⁻²) was estimated using the following formula [18]:

$${D (\mathrm{t}·\mathrm{hm}}^{-2}{) = Fw (\mathrm{kg}) ÷ \mathrm{plot} \mathrm{area} (\mathrm{m}}^2) \times \mathrm{10,000} ÷ 1000 \times \mathrm{Dry} \mathrm{matter} \mathrm{content} (\%)$$

(1)

2.3.4. Nutritional Quality

Oven-dried alfalfa samples were ground using a plant tissue mill pass through a 40-mesh sieve (particle size ≤425 μm) and stored in resealable plastic bags for subsequent analysis. Nutritional quality parameters were determined as follows:

Neutral detergent fiber (NDF) and acid detergent fiber (ADF) were measured using filter bag technology; crude fat (ether extract, EE) content was determined by the Soxhlet fat extraction method; coarse ash (Ash) content was determined using the combustion oxidation method; the anthrone-sulfuric acid method was used to determine the content of soluble sugar (SS) content; crude protein (CP) content was determined using the Kjeldahl nitrogen determination method [26].

2.4. Statistical Analyses

Data were analyzed using Microsoft Excel 2022 and SPSS 20.0 software. Prior to ANOVA, the assumptions of normality (assessed using the Shapiro–Wilk test) and homogeneity of variances (assessed using Levene’s test) were verified. The data satisfied both requirements. Subsequently, one-way analysis of variance (ANOVA) was conducted using the LSD method to compare the effects of row spacing and seeding rate treatments on various indicators. Two-way ANOVA was employed to examine the interaction between row spacing and seeding rate treatments. Additionally, redundancy analysis (RDA) was performed to evaluate the relationship between fluorescence parameters and quality indicators. Graphical representations were generated using Origin 2021.

3. Results

3.1. ChIM and NFI

Row spacing had a significant influence on both ChIM and NFI of alfalfa leaves, while seeding rate exhibited no significant effect on either parameter. However, a significant interaction effect between row spacing and seeding rate was observed for NFI, though this interaction did not significantly impact ChIM (

Table 2. Variance analysis of pigment content, quality parameters, and yield of alfalfa under different row spacing and sowing rate combinations.

Treatment	ChlM	NFI	ADF	NDF	EE	Ash	SS	CP	Hay Yield
Row spacing	**	**	NS	NS	**	**	**	NS	**
Seeding rate	NS	NS	NS	*	NS	**	**	**	NS
R × S	NS	**	NS	NS	*	**	NS	NS	**

Notes: * and ** indicate significance at the 0.05 and 0.01 probability levels, respectively. NS denotes no significant difference (p > 0.05). This notation is consistent across all tables.

). At the same seeding rate, ChIM generally declined with increasing row spacing. Specifically, under the widest row spacing treatment (R3), ChIM values in treatments S2 to S5 were significantly reduced by 16.1–28.0% compared to the narrowest spacing (R1). Notably, the R1S3 combination yielded the highest ChIM and NFI values among all treatment groups (Figure 1).

3.2. Chlorophyll Fluorescence Parameters

Seeding rate had a significant influence on the Fv/Fm of alfalfa leaves, whereas row spacing had no significant influence. With the increase in seeding rate, the Fv/Fm initially rose before subsequently declining, and the highest value was observed in the R1S4 treatment. Additionally, the interaction between row spacing and seeding rate had a highly significant effect on Y (II), ETR, qP, qN, Y (NPQ), and Y (NO) (

Table 3. Effects of different row spacing and seeding rate combinations on chlorophyll fluorescence parameters of alfalfa leaves.

Row Spacing	Seeding Rate	Fv/Fm	Y(II)	ETR	qP	qN	Y(NPQ)	Y(NO)
R1	S1	0.745 ± 0.008 Aab	0.536 ± 0.009 Aa	44.367 ± 0.758 Bb	0.792 ± 0.019 Ba	0.330 ± 0.038 Ab	0.125 ± 0.016 Ab	0.339 ± 0.015 Aa
	S2	0.754 ± 0.026 Aab	0.561 ± 0.014 Aa	51.578 ± 1.604 Aa	0.838 ± 0.041 Aa	0.479 ± 0.053 Aa	0.171 ± 0.015 Aa	0.268 ± 0.024 Bb
	S3	0.724 ± 0.029 Ab	0.548 ± 0.023 ABa	45.333 ± 1.895 Bb	0.864 ± 0.047 Aa	0.410 ± 0.026 ABab	0.154 ± 0.018 Bab	0.298 ± 0.006 ABab
	S4	0.792 ± 0.004 Aa	0.562 ± 0.007 Aa	46.522 ± 0.560 ABb	0.780 ± 0.009 Ba	0.342 ± 0.017 Bb	0.126 ± 0.008 Bb	0.312 ± 0.002 Aa
	S5	0.736 ± 0.006 Aab	0.556 ± 0.001 Aa	46.033 ± 0.083 Ab	0.835 ± 0.001 Aa	0.338 ± 0.010 Bb	0.121 ± 0.004 Cb	0.323 ± 0.005 Aa
R2	S1	0.688 ± 0.043 Ab	0.555 ± 0.017 Aab	52.089 ± 4.246 Aa	0.934 ± 0.031 Aa	0.425 ± 0.022 Ab	0.150 ± 0.010 Abc	0.295 ± 0.010 Bbc
	S2	0.730 ± 0.006 Aab	0.529 ± 0.010 Ab	43.756 ± 0.843 Ba	0.749 ± 0.027 Ac	0.268 ± 0.020 Bd	0.103 ± 0.007 Bd	0.368 ± 0.011 Aa
	S3	0.785 ± 0.005 Aa	0.567 ± 0.004 Aa	52.622 ± 2.783 Aa	0.787 ± 0.007 Ac	0.354 ± 0.008 Bc	0.128 ± 0.004 Bcd	0.305 ± 0.000 Ab
	S4	0.751 ± 0.004 Bab	0.556 ± 0.014 Aab	52.033 ± 3.861 Aa	0.865 ± 0.029 Ab	0.475 ± 0.034 Aab	0.175 ± 0.015 ABb	0.269 ± 0.013 Bc
	S5	0.762 ± 0.016 Aa	0.473 ± 0.031 Cc	48.589 ± 1.798 Aa	0.723 ± 0.002 Cc	0.494 ± 0.014 Aa	0.216 ± 0.018 Aa	0.311 ± 0.030 Ab
R3	S1	0.727 ± 0.044 Aa	0.539 ± 0.006 Aa	44.578 ± 0.534 Bab	0.828 ± 0.030 Ba	0.359 ± 0.036 Ab	0.136 ± 0.017 Ab	0.325 ± 0.013 ABa
	S2	0.748 ± 0.014 Aa	0.550 ± 0.032 Aa	45.533 ± 2.620 Bab	0.818 ± 0.042 Aa	0.374 ± 0.039 ABb	0.146 ± 0.027 ABab	0.303 ± 0.005 Bab
	S3	0.755 ± 0.028 Aa	0.490 ± 0.03 Ba	49.011 ± 2.023 ABa	0.78 ± 0.040 Aa	0.513 ± 0.062 Aa	0.230 ± 0.040 Aa	0.280 ± 0.010 Bb
	S4	0.786 ± 0.000 Aa	0.500 ± 0.020 Ba	41.656 ± 2.069 Bb	0.730 ± 0.020 Ba	0.459 ± 0.053 Aab	0.200 ± 0.030 Aab	0.300 ± 0.010 Ab
	S5	0.754 ± 0.012 Aa	0.532 ± 0.015 Ba	47.356 ± 1.963 Aab	0.782 ± 0.021 Ba	0.372 ± 0.029 Bb	0.146 ± 0.016 Bab	0.323 ± 0.006 Aa
Row spacing	P	NS	*	NS	NS	NS	*	NS
Seeding rate	P	*	**	NS	**	NS	*	**
R × S	P	NS	**	**	**	**	**	**

Notes: Different uppercase letters indicate significant differences among row spacing within the same seeding rate (p < 0.05), while different lowercase letters indicate significant differences among seeding rates within the same row spacing (p < 0.05). * and ** indicate significance at the 0.05 and 0.01 probability levels, respectively. NS denotes no significant difference (p > 0.05).

).

3.3. Nutritional Quality

3.3.1. ADF and NDF

Seeding rate had a significant effect on the NDF content of alfalfa, but not on ADF. Row spacing did not significantly influence either NDF or ADF (Table 2). The NDF content showed fluctuating trend across different seeding rates. Specifically, under R1 and R3, the lowest NDF was observed at the S5 seeding rate, while under R2, the lowest NDF occurred at S3 (Figure 2).

3.3.2. EE and Ash

Row spacing had a significant influence on the EE content of alfalfa, whereas seeding rate had no significant effect (Table 2). Compared with R1, EE content significantly decreased by 9.6–14.0% at S1–S3 under R2, and by 13.8% and 32.4% at S1 and S3 under R3, respectively. The highest EE value was observed under R1S3, which was significantly higher by 15.2–27.6% compared to other seeding rate treatments within the same row spacing, and by 11.0–32.4% compared to other row spacing treatments at the same seeding rate (Figure 3).

Ash content was significantly affected by row spacing, seeding rate, and their interaction (Table 2). Compared with R1, ash content decreased significantly by 12.3–30.7% under R2 and by 21.1–43.3% under R3, except at S1. Under R1, ash content increased significantly with higher seeding rates, rising by 16.8–65.5%; however, no significant trend was observed under R2 and R3. Additionally, the ash content of all treatments remained below 12%, except for R1S2 and R1S5 (Figure 3).

3.3.3. SS and CP

Both row spacing and seeding rate had significant effects on SS content, but their interaction did not (Table 2). Compared with S1, SS content decreased significantly by 10.3% and 11.2% at S2 and S5 under R1, and by 16.7%, 11.4%, and 13.1% at S3, S4, and S5 under R3, respectively (Figure 4). Seeding rate also had a significant effect on CP content, whereas row spacing showed no significant effect (Table 2). As seeding rate increased, CP content initially rose and then declined. The highest CP value was recorded at R1S4, reaching approximately 20.93% (Figure 4).

3.4. Hay Yield

Row spacing and seeding rate interacted significantly to effect hay yield of alfalfa (Table 2). Overall, hay yield under R1 was higher than that under R2 and R3. Compared with R1, hay yield at S2 and S3 decreased significantly by 44.4% and 32.8%, respectively, under R2. Under R3, hay yield at S1 to S4 showed a decreasing trend compared to R1, with reductions ranging from 28.6% to 57.8%. Hay yield also fluctuated with different seeding rates. The highest yield was recorded at R1S3, reaching approximately 7.36 t·hm⁻² (Figure 5).

3.5. Relationships Between Chlorophyll Fluorescence Parameters, Yield, and Quality

The relationships between chlorophyll fluorescence parameters, hay yield, and forage quality in alfalfa were analyzed using redundancy analysis (RDA) (Figure 6;

Table 4. RDA correlation coefficient between yield, quality indicators, and chlorophyll fluorescence parameters of alfalfa.

Index	The 1st Sort Axis RDA	The 2nd Sort Axis RDA	R2	p
ChlM	0.391	0.920	0.294	0.001 **
NFI	0.756	0.654	0.226	0.005 **
Y(II)	0.980	−0.200	0.169	0.013 *
qP	0.988	−0.152	0.129	0.047 *
Y(NPQ)	−0.923	0.385	0.111	0.083
qN	−0.717	0.697	0.050	0.323
Y(NO)	−0.730	−0.684	0.032	0.498
Fv/Fm	0.741	−0.672	0.000	0.999
ETR	−0.874	−0.485	0.002	0.954
Cumulative explanation (%)	44.03%	30.14%	-	-

Notes: * indicates extremely significant correlation at p < 0.05 level, and ** indicates extremely significant correlation at p < 0.01 level.

). The first two RDA axes explained 74.17% of the total variation, with RDA1 and RDA2 accounting for 44.03% and 30.14%, respectively.

ChlM had a highly significant positive influence on both yield and quality. NFI, Y (II), and qP also showed significant effects. ADF and NDF were positively correlated with Y (NPQ), while negatively affected by Y (II) and qP. ChlM and NFI were positively associated with ash content. Crude protein (CP) was positively influenced by Y (II) and qP. Hay yield was positively associated with ChlM, NFI, Y (II), and qP (Figure 6).

4. Discussion

4.1. Yield Effects

Planting density is widely recognized as one of the most basic and effective agronomic practices that affecting crop productivity [27,28]. Among its key components, row spacing and seeding rate play pivotal roles in determining planting density, thereby affecting crop dry matter accumulation and organic matter synthesis through the modulation of light interception [29]. Results from this study indicate that the interaction between row spacing and seeding rate has a significant impact on alfalfa hay yield, with row spacing as the more dominant factor. Specifically, yield declines markedly with increasing row spacing (Figure 5, Table 2). Seeding rate determines the size and vigor of individual plants, whereas row spacing affects the spatial uniformity of crop stand [30]. At a constant seeding rate, narrower row spacing enhances population uniformity, facilitating more coordinated interactions between the crop canopy and light environment. This results in greater leaf area for light interception and improved light use efficiency, ultimately increasing biomass production [31]. Moreover, as the trial was conducted in a saline–alkaline area with water deficits across the Bohai Rim under rainfed dryland conditions, optimizing planting density elevated canopy coverage, which suppressed topsoil evaporation and reduced foliar transpiration losses, consequently boosting forage productivity [32].

4.2. Forage Quality Traits

While yield is determined by the accumulation of assimilates, forage quality depends on the transformation of these assimilates into various nutritional compounds [33]. Photosynthesis is central to this process, synthesizing essential organic matter such as carbohydrates, proteins, and fats [34]. Soluble sugars, direct products of photosynthesis, serve as substrates for the formation of polysaccharides and act as indicators of forage nutritional value. This study found that row spacing and seeding rate have a significant impact on the SS content of alfalfa (Table 2). Optimized planting density reduces inter-plant shading and improves the light microenvironment, thereby increasing SS content due to enhanced photosynthetic activity [18].

CP, another key quality trait, initially increased and then declined with increasing seeding rate. This aligns with previous research demonstrating close correlations between planting density and protein content in both leguminous and cereal crops [35,36]. As a high protein-forage crop, alfalfa accumulates most of its protein in the leaves [37], which are also the primary photosynthetic organs. An appropriate seeding rate enhances canopy photosynthetic efficiency and increases the leaf-to-stem ratio, ultimately improving protein content [38,39]. EE constitutes a fundamental indicator for forage energy valuation, and exhibited 2.4-fold higher content than the combined carbohydrates and proteins [29]. The R1S3 treatment maximized EE, whereas R1S4 optimized CP (Figure 3A and Figure 4B). Aligned with this finding, our research demonstrates that a 15 cm row spacing combined with the medium seeding density treatment (S3/S4) enables alfalfa to achieve peak protein content [40]. Beyond nutritional minerals, ash also reflects environmental contaminants (e.g., soil dust), with levels > 12% indicating disqualifying forage quality [29]. Notably, alfalfa under R1S3 and R1S4 treatments consistently maintained ash content below 12%, qualifying as premium forage. In this study, row spacing exerted a highly significant effect on ash, EE, and SS content. This contrasts with findings by Bouchard et al. [41] demonstrating no impact of row spacing on any nutritional parameters. These divergent results may be attributed to differences in forage species and regional cultivation conditions.

4.3. Mechanisms of Photosynthetic Regulation

Crop yield formation is a complex biological process, primarily driven by light availability [42,43]. Redundancy analysis further indicated that yield was most strongly associated with ChlM, NFI, Y (II), and qP (Figure 6). Across all treatments, the R1S3 produced the highest values for ChIM, NFI, and hay yield (Figure 1 and Figure 5). Chlorophyll, a key photosynthetic pigment, plays a crucial role in capturing light energy and driving CO₂ assimilation. Its content reflects the photosynthetic activity of leaves [22]. Flavonol, another group of bioactive compounds, accumulate under abiotic stress and enhance electron transport while scavenging reactive oxygen species, due to their redox potential and hydroxylation patterns [44,45]. Therefore, we tentatively infer that the R1S3 treatment (narrow row spacing with a medium seeding rate) enhances canopy photosynthetic efficiency and stress resilience by optimizing ChlM and NFI, ultimately increasing yield. However, future studies are needed to investigate ROS activity and flavonol biosynthesis to validate the proposed stress mitigation mechanisms.

Our findings also indicate that Y (II) and qP significantly influence alfalfa forage quality, exerting negative effects on ADF and NDF, while positively affecting CP and EE (Figure 6). Both NDF and ADF primarily originated from plant cell walls and are critical indicators of forage fiber content. Specifically, NDF exhibits a negative correlation with dry matter intake, whereas ADF directly affects feed digestibility [46]. According to Huang et al. [47], reducing cell wall thickness is an effective strategy to improve photosynthetic capacity. Thinner cell walls may enhance mesophyll conductivity, boost photosynthesis, and reduce fiber content in alfalfa. This indicates that higher measured photosynthetic efficiency correlates with reduced fiber content, elevated protein content, and consequently improved forage quality.

4.4. Implications and Limitations

In practical production, a configuration of narrow row spacing (15 cm) combined with a moderate seeding rate (22.5~30 kg·hm⁻²) not only maintained higher forage quality but also exhibited better adaptation to local climatic and soil conditions. This optimized planting density enhanced canopy coverage, reduced water loss through topsoil evaporation and plant transpiration, and suppressed upward salt migration. Simultaneously, it improved the utilization efficiency of light, water, and nutrients, thereby achieving higher yields [48]. Furthermore, this specific row spacing and seeding rate configuration was well-suited for mechanized production systems, further enhancing operational efficiency.

However, there are two major limitations in this study that should be addressed in future research. First, the lack of measurements for certain physiological indicators, such as ROS, antioxidant enzymes, and related stress markers, required us to rely on assumptions when interpreting the results. Second, although we assessed soil salinity uniformity before the trial, we did not re-monitor it during subsequent measurements of fluorescence parameters, yield, and quality after two years of cultivation. In future studies, we plan to expand the indicator system to elucidate the specific physiological pathways by which photosynthetic processes regulate alfalfa yield and quality under coastal saline–alkaline conditions.

5. Conclusions

R1S3 demonstrated superior performance in yield and nutritional parameters—achieving peak values for ChIM, NFI, EE, and hay yield—whereas R1S4 exhibited maximal photosynthetic efficiency (Fv/Fm) coupled with the highest CP. These outcomes validate our initial hypothesis that narrow row spacing (15 cm) with moderate seeding rates (22.5–30 kg·hm⁻²) optimize photosynthetic performance while concurrently enhancing both productivity and forage quality in alfalfa cultivated under saline–alkaline conditions.