Moderate Deficit Irrigation and Reduced Nitrogen Application Maintain Tuber Quality and Improve Nitrogen Use Efficiency of Potato (Solanum tuberosum L.)

Abstract

Efficient water and nitrogen (N) management are essential for sustaining potato (Solanum tuberosum L.) production under limited resource conditions. This study investigated the effects of deficit irrigation and reduced N application on tuber quality parameters including specific gravity (SG), starch content (SC), and tuber dry matter (TDM) as well as agronomic water use efficiency (WUE) and nitrogen use efficiency (NUE) in four commercial potato cultivars (Canela Russet, Mesa Russet, Russet Norkotah 3, and Yukon Gold) over two seasons (2016 and 2017) at Colorado State University’s San Luis Valley Research Center. Three irrigation levels (100%, ~80%, and ~70% evapotranspiration replacement) and two N application rates (165 and 131 kg N ha⁻¹) were evaluated using four replications. Moderate deficit irrigation (up to ~18% ET reduction) improved or maintained SG, SC, and TDM in all four cultivars, while severe deficit irrigation (~30–40% reduction) reduced tuber quality. Reduced N application improved NUE in all cultivars without compromising tuber quality or yield. While WUE responded variably to deficit irrigation, NUE was highest under moderate to full irrigation and low N rate. Although effects on WUE were variable, integrating moderate deficit irrigation (18%) with reduced N application (20%) enhanced NUE while maintaining tuber quality.

1. Introduction

Potato (Solanum tuberosum L.) is one of the world’s most important food crops, with an estimated annual production of approximately 376 million tons in 2020, covering 19.3 million hectares in 159 countries [1]. However, its shallow root system and sensitivity to soil moisture make water availability a primary limiting factor in potato cultivation. Appropriately timed and well-calibrated irrigation scheduling throughout the growing season can substantially enhance both tuber formation and overall yield [2]. Similarly, nutrient management, particularly nitrogen (N), is critical for supporting vigorous vegetative growth, optimizing photosynthetic efficiency, and promoting high-quality tuber development [3,4]. Moreover, the effectiveness of N fertilization is highly dependent on its synchronization with soil moisture conditions. Without integrated water and nutrient management, nitrate–nitrogen is prone to leaching, which not only reduces nutrient use efficiency but also increases the risk of environmental contamination [5].

The Rio Grande River starts in the mountains of southern Colorado, flowing south through New Mexico (USA) and forming the 2000 km long border between Texas (USA) and the country of Mexico. The Rio Grande watershed is experiencing prolonged drought and increased water demand, resulting in groundwater depletion and water shortages. During the last 20 years, the Rio Grande River’s annual water flows have decreased steadily in southern Colorado’s San Luis Valley [6]. The San Luis Valley is an important agricultural region in the Rio Grande watershed where potato production plays a key role in the local economy, and the current water crisis is causing potato farmers to seek ways to reduce water use while maintaining profitability [6]. One promising water conservation measure is deficit irrigation. Previous research in the San Luis Valley has shown that reducing irrigation rates by up to 18% did not reduce yield of most potato cultivars [7]. However, in addition to yield optimization, it is also critically important to maximize potato tuber quality and resource use efficiency while conserving water.

Improper irrigation or N regimes can result in suboptimal tuber development and a higher incidence of defects that negatively affect both marketability and seed quality. The presence of physical or physiological defects, particularly on the tuber surface, is a critical concern for commercial grading systems and consumer acceptance [8,9]. Early identification and mitigation of such defects are essential to ensure consistent yield and to maintain quality standards in both fresh market and processing sectors. Potato tuber quality can be significantly compromised by a range of external and internal defects, which affect both market value and consumer acceptance. Among the most common external defects are growth cracks, knobs, and misshapen tubers. These defects not only reduce tuber quality but also make fresh market potatoes less desirable for commercial grading and retail distribution [10,11]. Brown center and hollow heart are internal physiological disorders in potato tubers that frequently co-occur and significantly reduce market quality. These defects are particularly detrimental to fresh market appeal, as they compromise internal appearance and consumer satisfaction. Both conditions are commonly associated with physiological stress, especially when environmental conditions change abruptly, such as the occurrence of sudden rainfall following extended dry periods, which disrupts uniform tuber growth and cellular development [12].

In addition to tuber defects, quality traits include specific gravity (SG), starch content (SC), and tuber dry matter (TDM). The most critical indicator of potato tuber quality is SG, defined as the ratio of tuber density to the density of water at a specific temperature. It serves as a proxy for TDM and SC and is influenced by a combination of environmental conditions and agronomic practices throughout the growing season. Both excessive and insufficient N applications can adversely impact tuber growth, yield, and SG. Similarly, the availability and timing of irrigation influences TDM and sugar accumulation. Because photosynthesis directly affects assimilate partitioning to tubers, any factor that alters photosynthetic efficiency can, in turn, impact SG [13]. SC in potato tubers is positively influenced by water availability and N management. Enhanced irrigation generally promotes higher SC, whereas water deficits tend to reduce SC accumulation. However, while adequate N is essential for tuber development, excessive N application may suppress SC synthesis and reduce final tuber SC [14]. TDM, another key quality parameter, is sensitive to both irrigation and N regimes. TDM often decreases with increased irrigation due to dilution effects and reduced carbohydrate concentration. Conversely, deficit irrigation has been associated with higher TDM levels, suggesting a concentration effect under water-limited conditions [14]. While several studies have reported an increase in TDM with higher N rates, others have found no significant response [15].

Limited water supplies, rising irrigation costs, and the increasing price and environmental impact of fertilizers have prompted the adoption of practices to improve water and N use efficiency. Optimal management of irrigation water and N is essential to improve water and nutrient use efficiencies, minimize N losses, and sustain high yields and quality [16]. Due to the persistent supply–demand imbalances and the challenges posed by climate change and population growth, optimizing both water use efficiency (WUE) and nitrogen use efficiency (NUE) is critical for sustainable agricultural production in the Rio Grande watershed. Improving WUE ensures that limited water resources are utilized as effectively as possible, while enhancing NUE minimizes nutrient losses and environmental impacts.

The objectives of this study were to evaluate the effects of deficit irrigation and reduced N application rates on (1) tuber quality of four potato cultivars grown in Colorado’s San Luis Valley and (2) WUE and NUE. Specifically, the study assessed the incidence of common external and internal tuber defects, along with measurements of SG, SC, and TDM. In addition, WUE and NUE were evaluated on a plot scale to determine how integrated irrigation and N management strategies influence tuber quality and resource use efficiency across different cultivars.

2. Materials and Methods

2.1. Experimental Site

The field site was located at Colorado State University’s San Luis Valley Research Center (latitude 37°43′ N, longitude 106°9′ W, and 2310 m altitude), and experiments were carried out during the 2016 and 2017 potato cropping seasons. The soil is classified as a Norte gravelly sandy loam [loamy-skeletal, mixed (calcareous), frigid Aquic Ustorthents] [17]. Annual rainfall is typically 10 to 18 cm, and the crop preceding potato was dry beans (Phaseolus vulgaris). Residual soil NO₃-N concentration was 5.5 mg kg⁻¹ and 6.0 mg kg⁻¹ in 2016 and 2017, respectively (

Table 1. Chemical properties of soil at the experimental site on the San Luis Valley Research Center (CO, USA).

Year	pH	Soluble Salts	Organic Matter	Nitrate–N	Available P (Mehlich-3)	Exchangeable K (NH4OAc)
		dS m−1	%	mg kg−1
2016	8.1	0.23	1.2	5.5	98	367
2017	8.0	0.31	1.5	6.0	98	451

). Soil pH was 8.0–8.1, and organic matter was ≤1.5%.

Four potato cultivars were investigated in a set of four experiments: Canela Russet (medium maturity, with high specific gravity), Mesa Russet (medium maturity with medium specific gravity), Russet Norkotah 3 (early maturity, fresh market, with medium to high specific gravity), and Yukon Gold (early to medium maturity, with yellow flesh, and high specific gravity).

2.2. Experimental Design and Field Layout

Experimental design involved six treatments (3 irrigation levels × 2 fertilizer treatments) and four replications. Each plot consisted of four 8 m long rows which were 0.9 m apart. Cut or whole certified, disease-free seeds were planted 0.3 m apart within rows. Cut seed (~80 to 85 g) was planted with a potato planter to a depth of 10 to 13 cm. The four cultivars were planted in separate parcels as independent experiments.

Daily reference evapotranspiration (ET) was estimated using the Hargreaves method [18] with data obtained from a weather station located at the Research Center [19]. There were three irrigation treatments, the control which provided 100% ET replacement for the crop and two deficit irrigation levels. The deficit irrigation treatments targeted 70 and 80% ET replacement (

Table 2. Irrigation treatments for four potato cultivars grown in 2016 and 2017 at the Colorado State University San Luis Valley Research Center. IRRG1 = lowest irrigation treatment, IRRG2 = moderate irrigation treatment, and IRRG3 = full irrigation treatment.

Cultivar and Year	Irrigation Treatment
	IRRG1	IRRG2	IRRG3
Canela Russet
2016	67% (36 cm)	84% (46 cm)	100% (54 cm)
2017	55% (31 cm)	82% (46 cm)	100% (56 cm)
Mesa Russet
2016	75% (37 cm)	94% (46 cm)	100% (49 cm)
2017	66% (33 cm)	90% (45 cm)	100% (50 cm)
Russet Norkotah3
2016	67% (36 cm)	84% (45 cm)	100% (54 cm)
2017	61% (34 cm)	77% (43 cm)	100% (56 cm)
Yukon Gold
2016	69% (36 cm)	85% (44 cm)	100% (52 cm)
2017	61% (28 cm)	83% (38 cm)	100% (46 cm)

). All experimental plots were provided with 100% ET replacement until tuber bulking began, and irrigation treatments were initiated at this point in the season. A single-line source irrigation technique was used to achieve deficit irrigation levels; the line source irrigation system prevented the randomization of irrigation treatments.

Pre-plant fertilizer was applied as a blanket application across the entire plot area. Specifically, 68 kg N ha⁻¹ [urea ammonium nitrate (32-0-0)] was applied to all plots, banded 5 cm below and 5 cm to the side of each seed piece. In addition, 67 kg ha⁻¹ of ammonium phosphate (10-34-0) and 45 kg ha⁻¹ of potash [KCl (0-0-60)] were applied to all plots as pre-plant fertilizers based on Colorado State University (CSU) fertilizer recommendations for potatoes [20].

Two N application treatments were applied within the growing season in combination with each irrigation treatment. After tuberization, in-season N fertilizer was applied in three split applications at weekly intervals, with the first in-season N application at 64 and 50 days after planting (DAP) in 2016 and 2017, respectively, to achieve total N rates of either 131 or 165 kg N ha⁻¹ (

Table 3. Nitrogen (N) fertilizer application treatments used in 2016–2017 potato experiments at the Colorado State University San Luis Valley Research Center.

Treatment	Low Nitrogen Application (N1)	Recommended Nitrogen Application (N2)
	--------------------kg N ha−1--------------------
Pre-plant	75	75
In season	56 (split application 22-22-12)	90 (split application 34-34-22)
Total N Applied	131	165

). The higher rate (N2) was based on Colorado State University (CSU) fertilizer recommendations for potatoes [20], and the lower rate (N1) represents a 20% reduction from the recommended rate. In-season N fertilizer (urea ammonium nitrate, 32-0-0) was applied using a boom sprayer and was immediately watered into the soil after spraying.

2.3. Data Collection

2.3.1. Irrigation Water Measurement

Rain gauges were installed above the crop canopy in the middle of each line of plots to capture the rainfall and measure the amount of water applied with each irrigation (Table 2). Rain gauges were read immediately after irrigation to minimize evaporative losses. The change in irrigation application rates observed from 2016 to 2017 was due to measured ET differences.

2.3.2. Tuber External and Internal Defects

At harvest, tubers from each plot with growth cracks, knobs, and misshapes were weighed and reported as a percentage of the total yield. Internal defects in tubers were assessed by cutting open the five largest tubers from each plot to quantify the presence of hollow heart and brown center. In cases where a defect was found, an additional five of the largest tubers were sequentially cut open until five consecutive tubers revealed no internal defects. The weight of tubers with defects was measured and reported as a percentage of the total yield.

2.3.3. Tuber-Specific Gravity

Ten clean tubers were selected randomly from each plot and used to determine SG with the water displacement method. In this method, each sample is weighed in air and in water, and SG is calculated as the weight in the air divided by the difference between the weight in air and the weight in water [21].

2.3.4. Starch Content (SC) and Tuber Dry Matter (TDM) Measurement

The following equations were used to calculate the SC [22] and TDM [21]:

SC (%): 17.546 + 199.07 (SG − 1.0988)

TDM (%): −214.9206 + 218.1852 × (SG)

2.3.5. Water Use Efficiency (WUE) and Nitrogen Use Efficiency (NUE)

WUE was calculated as follows: WUE = Tuber Yield (kg ha⁻¹)/water applied through irrigation (mm) + precipitation (mm) during the growing season [23]. NUE was calculated based on the formula NUE = Tuber Yield (kg ha⁻¹)/Total Nitrogen Applied (kg ha⁻¹).

2.4. Statistical Analysis

Analysis of variance (ANOVA) was conducted using the PROC MIXED procedure in SAS (Statistical Analysis System, version 9.4, SAS Campus Drive, Cary, NC 27513, USA). Fisher’s protected least significant difference (LSD) test was used for mean separation with a p-value of 0.05. If significant interaction (p < 0.05) between irrigation and N treatments was detected, pairwise comparisons were performed on the interaction using the SLICE statement to compare water levels within each N level, and Tukey adjustment. The Pearson Correlation Coefficient Analysis was used to assess the relationship between SG, SC, and TDM (Quality Traits) and WUE and NUE (resource use efficiencies) with yield.

3. Results

3.1. Precipitation

The San Luis Valley Research Center recorded precipitation data for the 2016 and 2017 growing seasons, as depicted in Figure 1 [19]. In 2016, rainfall was relatively well distributed throughout the season, except for a pronounced peak in August that coincided with the tuber bulking stage. The total precipitation that year was 86 mm. In contrast, 2017 experienced highly variable rainfall patterns, with dry conditions early in the season and significant peaks in July and September, resulting in a total of 108 mm. Despite receiving more rainfall in 2017 than in 2016, the uneven distribution and unfavorable timing of precipitation likely reduced its effectiveness for supporting potato growth and yield. Previous studies highlight that both the quantity and the timing of precipitation are critical factors affecting potato yields [24].

3.2. Tuber Internal and External Defects

Reducing irrigation water and N application rates did not have any significant effect on internal or external tuber defects in any of the cultivars (Canela Russet, Mesa Russet, Russet Norkotah 3, and Yukon Gold) or years. These results are not presented in detail because the effects were not statistically significant.

3.3. Quality Traits

3.3.1. Canela Russet

Water reductions of 16% and 18% of ET in 2016 and 2017, respectively, demonstrated that moderate deficit irrigation (IRRG2) had the highest SG, SC, and TDM, but these differences were not significant compared to the full irrigation treatment (IRRG3) (

Table 4. Effect of deficit irrigation and nitrogen fertilizer application rates on potato tuber quality parameters of Canela Russet in 2016 and 2017.

		Years
		2016			2017
Treatments		SG	SC	TDM	SG	SC	TDM
Water			----------%----------			----------%----------
IRRG3		1.093 ab (0.001)	16.30 ab (0.17)	23.45 ab (0.19)	1.097 a (0.001)	17.14 a (0.15)	24.37 a (0.22)
IRRG2		1.096 a (0.001)	16.97 a (0.26)	24.19 a (0.29)	1.099 a (0.001)	17.48 a (0.18)	24.75 a (0.16)
IRRG1		1.089 b (0.001)	15.82 b (0.28)	22.93 b (0.31)	1.098 a (0.001)	17.32 a (0.33)	24.57 a (0.36)
Nitrogen
N1		1.093 a (0.001)	16.39 a (0.18)	23.56 a (0.20)	1.098 a (0.001)	17.40 a (0.16)	24.66 a (0.18)
N2		1.092 a (0.001)	16.33 a (0.26)	23.49 a (0.28)	1.097 a (0.001)	17.23 a (0.24)	24.47 a (0.26)
Interaction W within N
Nitrogen	Water
N1	IRRG3	1.092 a (0.001)	16.15 a (0.17)	23.29 a (0.19)	1.098 a (0.001)	17.28 a (0.20)	24.53 a (0.22)
	IRRG2	1.096 a (0.001)	17.01 a (0.26)	24.23 a (0.29)	1.096 a (0.001)	17.04 a (0.15)	24.27 a (0.16)
	IRRG1	1.091 a (0.001)	16.02 a (0.28)	23.15 a (0.31)	1.100 a (0.002)	17.87 a (0.33)	25.18 a (0.36)
N2	IRRG3	1.094 a (0.001)	16.45 a (0.21)	23.61 a (0.23)	1.096 ab (0.001)	16.99 ab (0.23)	24.22 ab (0.25)
	IRRG2	1.096 a (0.003)	16.93 a (0.53)	24.15 a (0.58)	1.100 a (0.003)	17.92 a (0.48)	25.23 a (0.53)
	IRRG1	1.088 a (0.002)	15.62 a (0.33)	22.71 a (0.36)	1.095 b (0.002)	16.76 b (0.32)	23.96 b (0.35)
Source of Variation	DF	p-Value
Water	2	0.0040	0.0071	0.0069	0.6218	0.5352	0.5350
Nitrogen	1	0.7981	0.8173	0.8169	0.5100	0.5022	0.4999
W × N	2	0.4591	0.5578	0.5623	0.0137	0.0147	0.0151

Means ± SE within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (84 and 82% ET), IRRG1: Deficit Irrigation Water (67 and 55% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹). N2: nitrogen recommended level (158 kg N ha⁻¹). W × N: the interaction between water and nitrogen treatments. SG: specific gravity, SC: starch content, TDM: tuber dry matter.

). The mean values for SG, SC, and TDM were higher in 2017 compared to 2016 (Table 4). In contrast, severe deficit irrigation (IRRG1) significantly reduced SG, SC, and TDM in 2016 compared to the IRRG2 treatment. Nitrogen application rate had no effect on SG, SC, and TDM. In 2017, the interaction of water within the N2 rate (recommended N levels) showed that severe deficit irrigation (IRRG1) significantly reduced tuber quality traits; however, IRRG2 showed no significant difference compared to IRRG3 (Table 4). There were no significant interactions in 2016.

3.3.2. Mesa Russet

The values for SG, SC, and TDM were generally lower in 2016 than in 2017 (

Table 5. Effect of deficit irrigation and nitrogen fertilizer application rates on potato tuber quality parameters of Mesa Russet in 2016 and 2017.

		Years
		2016			2017
Treatments		SG	SC	TDM	SG	SC	TDM
Water			----------%----------			----------%----------
IRRG3		1.072 a (0.003)	12.14 a (0.22)	18.89 a (0.30)	1.085 a (0.004)	14.83 a (0.25)	21.84 a (0.33)
IRRG2		1.074 a (0.004)	12.56 a (0.18)	19.36 a (0.27)	1.088 a (0.003)	15.34 a (0.29)	22.40 a (0.36)
IRRG1		1.072 a (0.003)	12.10 a (0.21)	18.86 a (0.28)	1.088 a (0.004)	15.47 a (0.31)	22.55 a (0.39)
Nitrogen
N1		1.074 a (0.002)	12.54 a (0.19)	19.33 a (0.25)	1.088 a (0.003)	15.40 a (0.22)	22.42 a (0.35)
N2		1.071 a (0.003)	12.00 a (0.21)	18.74 a (0.28)	1.086 a (0.004)	15.06 a (0.27)	22.10 a (0.34)
Source of Variation	DF	p-Value
Water	2	0.4111	0.3470	0.3410	0.1426	0.1739	0.1725
Nitrogen	1	0.0691	0.0713	0.0699	0.3001	0.3128	0.3146
W × N	2	0.7610	0.7989	0.7958	0.7557	0.8366	0.8347

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (94 and 90% ET), IRRG1: Deficit Irrigation Water (75 and 66% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹), W × N: the interaction between water and nitrogen treatments. SG: specific gravity, SC: starch content, TDM: tuber dry matter.

). In 2016 and 2017, although irrigation was reduced up to 25% and 45% ET, respectively, and N by ~20%, no significant differences were observed in SG, SC, and TDM. Moreover, the interaction between irrigation water and N application showed no significance in either year (Table 5).

3.3.3. Russet Norkotah 3

The values for SG, SC, and TDM were lower in 2016 than in 2017, regardless of treatment (

Table 6. Effect of deficit irrigation and nitrogen fertilizer application rates on potato tuber quality parameters of Russet Norkotah 3 in 2016 and 2017.

		Years
		2016			2017
Treatments		SG	SC	TDM	SG	SC	TDM
Water			----------%----------			----------%----------
IRRG3		1.079 a (0.002)	13.51 a (0.24)	20.39 a (0.31)	1.081 a (0.003)	13.99 a (0.29)	20.92 a (0.36)
IRRG2		1.078 a (0.004)	13.43 a (0.27)	20.31 a (0.33)	1.083 a (0.002)	14.38 a (0.33)	21.35 a (0.38)
IRRG1		1.073 b (0.002)	12.41 b (0.22)	19.19 b (0.29)	1.084 a (0.003)	14.62 a (0.31)	21.61 a (0.37)
Nitrogen
N1		1.077 a (0.002)	13.22 a (0.25)	20.09 a (0.32)	1.083 a (0.003)	14.54 a (0.30)	21.53 a (0.36)
N2		1.076 a (0.003)	13.01 a (0.26)	19.85 a (0.34)	1.081 a (0.002)	14.11 a (0.28)	21.06 a (0.35)
Source of Variation	DF	p-Value
Water	2	0.0006	0.0007	0.0007	0.3071	0.2706	0.2744
Nitrogen	1	0.3132	0.3181	0.3156	0.1362	0.1839	0.1840
W × N	2	0.7530	0.6562	0.6523	0.7522	0.7730	0.7714

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (84 and 77% ET), IRRG1: Deficit Irrigation Water (67 and 61% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹), W × N: the interaction between water and nitrogen treatments. SG: specific gravity, SC: starch content, TDM: tuber dry matter.

). In 2016 and 2017, moderate deficit irrigation (IRRG2) did not result in significant changes in quality parameters (SG, SC, and TDM) compared to full irrigation. However, the severe deficit irrigation treatment (IRRG1) led to reductions in quality traits in 2016. Nitrogen treatments had no effect, and the interaction between irrigation and N treatments was also not significant (Table 6).

3.3.4. Yukon Gold

In 2016, reducing irrigation by 15% (IRRG2) improved SG, SC, and TDM compared to full irrigation (IRRG3). The results of the 2016 study showed that the mean values for SG, SC, and TDM were less than 2017. In terms of N treatments, N1 (low nitrogen) resulted in significantly higher values for SG, SC, and TDM than N2 (recommended rate) in 2016, but there was no significant impact in 2017. Similarly, the interactions between irrigation and N treatments were not significant in either year (

Table 7. Effect of deficit irrigation and nitrogen fertilizer application rates on potato tuber quality parameters of Yukon Gold in 2016 and 2017.

		Years
		2016			2017
Treatments		SG	SC	TDM	SG	SC	TDM
Water			----------%----------			----------%----------
IRRG3		1.083 b (0.001)	14.47 b (0.20)	21.45 b (0.22)	1.091 a (0.001)	16.07 a (0.13)	23.20 a (0.15)
IRRG2		1.087 a (0.001)	15.08 a (0.28)	22.12 a (0.31)	1.093 a (0.001)	16.27 a (0.18)	23.42 a (0.19)
IRRG1		1.084 b (0.0009)	14.70 ab (0.13)	21.70 ab (0.15)	1.090 a (0.001)	15.84 a (0.14)	22.95 a (0.15)
Nitrogen
N1		1.086 a (0.001)	15.02 a (0.13)	22.05 a (0.13)	1.091 a (0.001)	15.99 a (0.14)	23.12 a (0.15)
N2		1.083 b (0.001)	14.4 b (0.14)	21.46 b (0.14)	1.092 a (0.001)	16.12 a (0.14)	23.26 a (0.16)
Source of Variation	DF	p-Value
Water	2	0.0081	0.0124	0.0125	0.1673	0.2303	0.2261
Nitrogen	1	0.0015	0.0020	0.0021	0.5045	0.5134	0.5144
W × N	2	0.1253	0.1053	0.1030	0.7361	0.7657	0.7666

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (85 and 83% ET), IRRG1: Deficit Irrigation Water (69 and 61% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹), W × N: the interaction between water and nitrogen treatments. SG: specific gravity, SC: starch content, TDM: tuber dry matter.

).

3.4. Resource Use Efficiencies

3.4.1. Canela Russet

The WUE of Canela Russet significantly improved under deficit irrigation (IRRG2 and IRRG1) compared to full irrigation (IRRG3) in 2016. However, in 2017, WUE differences between treatments were less distinct, although IRRG1 still showed significantly higher WUE than IRRG3 (

Table 8. Effect of deficit irrigation and nitrogen fertilizer application rates on water and nitrogen use efficiency of Canela Russet in 2016 and 2017.

		Years
		2016		2017
Treatments		WUE	NUE	WUE	NUE
Water		kg ha−1 mm−1	kg ha−1 kg N−1	kg ha−1 mm−1	kg ha−1 kg N−1
IRRG3		82.92 b (2.74)	322.36 a (17.98)	72.03 b (3.52)	286.47 a (8.50)
IRRG2		102.39 a (3.45)	335.59 a (20.19)	82.21 ab (2.40)	270.14 a (7.69)
IRRG1		98.65 a (4.46)	255.35 b (15.09)	87.19 a (3.87)	193.35 b (9.19)
Nitrogen
N1		94.73 a (3.43)	341.60 a (14.94)	74.74 b (2.51)	261.08 a (13.25)
N2		94.58 a (4.23)	267.27 b (12.52)	86.21 a (3.00)	238.90 b (13.90)
Source of Variation	DF	p-Value
Water	2	0.0056	0.0003	0.0025	<0.0001
Nitrogen	1	0.9745	<0.0001	0.0015	0.0214
W × N	2	0.9556	0.6652	0.6074	0.4567

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (84 and 82% ET), IRRG1: Deficit Irrigation Water (67 and 55% ET) for 2016 and 2017, respectively. N1: nitrogen reduced level (124 kg N ha⁻¹). N2: nitrogen recommended level (158 kg N ha⁻¹) W × N: the interaction between water and nitrogen treatments. WUE: water use efficiency, NUE: nitrogen use efficiency.

). The NUE was not significantly different between IRRG2 and IRRG3 in either year, but IRRG1 consistently resulted in significantly lower NUE in both 2016 and 2017. These results suggest that severe water stress compromised yield and, therefore, reduced NUE. In terms of N rate effects, NUE was significantly higher under the reduced nitrogen rate (N1) than under the recommended rate (N2) in both years, indicating more efficient use of N under limited input. Response of WUE to N rates was inconsistent across years. No significant interaction between irrigation and N rate was observed for either WUE or NUE, indicating that these factors act independently in Canela Russet.

3.4.2. Mesa Russet

WUE and NUE under IRRG2 (a 6% and 10% reduction in irrigation for 2016 and 2017, respectively) were not significantly different from IRRG3 (

Table 9. Effect of deficit irrigation and nitrogen fertilizer application rates on water and nitrogen use efficiency of Mesa Russet in 2016 and 2017.

		Years
		2016		2017
Treatments		WUE	NUE	WUE	NUE
Water		kg ha−1 mm−1	kg ha−1 kg N−1	kg ha−1 mm−1	kg ha−1 kg N−1
IRRG3		82.32 a (4.03)	286.47 a (8.50)	80.20 a (2.42)	258.08 a (14.77)
IRRG2		81.32 ab (2.37)	270.14 a (7.69)	83.41 a (3.13)	271.31 a (18.25)
IRRG1		73.05 b (3.24)	193.35 b (9.19)	71.68 a (4.22)	190.39 b (12.70)
Nitrogen
N1		73.04 b (2.01)	261.08 a (13.25)	79.45 a (2.56)	272.23 a (14.28)
N2		84.75 a (2.56)	238.89 b (13.90)	77.41 a (3.46)	207.62 b (11.71)
Source of Variation	DF	p-Value
Water	2	0.0291	<0.0001	0.0789	<0.0001
Nitrogen	1	0.0006	0.0214	0.6240	<0.0001
W × N	2	0.2915	0.4567	0.7835	0.3554

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (94 and 90% ET), IRRG1: Deficit Irrigation Water (75 and 66% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹), W × N: the interaction between nitrogen and water treatments. WUE: water use efficiency, NUE: nitrogen use efficiency.

). However, IRRG1 (a 25% and 34% reduction) significantly reduced NUE in both years, indicating that severe water stress reduced yield and hindered N uptake and assimilation. WUE was significantly higher under the recommended nitrogen rate (N2) in 2016, while no difference was observed in 2017. Conversely, NUE was significantly higher under the reduced N rate (N1) in both years. These results highlight a trade-off: higher N rates may initially improve water use efficiency, but lower rates optimize NUE. The interaction between water and N was not statistically significant, supporting independent effects.

3.4.3. Russet Norkotah 3

WUE exhibited variable trends between years. In 2016, no significant difference was observed among irrigation treatments, but in 2017, IRRG2 and IRRG1 significantly improved WUE compared to IRRG3 (

Table 10. Effect of deficit irrigation and nitrogen fertilizer application rates on water and nitrogen use efficiency of Russet Norkotah 3 in 2016 and 2017.

		Years
		2016		2017
Treatments		WUE	NUE	WUE	NUE
Water		kg ha−1 mm−1	kg ha−1 kg N−1	kg ha−1 mm−1	kg ha−1 kg N−1
IRRG3		95.26 a (4.16)	300.21 a (25.54)	79.47 b (2.59)	261.93 a (12.01)
IRRG2		90.37 a (2.35)	285.01 ab (11.70)	95.17 a (5.16)	258.54 a (13.62)
IRRG1		79.45 a (6.93)	249.86 b (25.13)	104.78 a (4.63)	208.45 b (3.90)
Nitrogen
N1		92.75 a (3.45)	324.96 a (10.68)	86.74 b (2.99)	257.10 a (11.88)
N2		83.97 a (4.75)	231.76 b (13.21)	99.54 a (5.16)	228.85 a (8.82)
Source of Variation	DF	p-Value
Water	2	0.0570	0.0273	0.0003	0.0012
Nitrogen	1	0.1019	<0.0001	0.0057	0.0190
W × N	2	0.1312	0.1211	0.2651	0.3559

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (84 and 77% ET), IRRG1: Deficit Irrigation Water (67 and 61% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹). W × N: the interaction between water and nitrogen treatments. WUE: water use efficiency, NUE: nitrogen use efficiency.

). This suggests that under reduced water availability, Russet Norkotah 3 demonstrated a degree of resilience and water use optimization, indicating that reduced water input can enhance WUE due to more conservative transpiration and increased biomass per unit of water. NUE significantly declined under IRRG1 in both years compared to IRRG3, which showed higher NUE, confirming that excessive water reduction negatively impacted yield and NUE. Regarding N effects, N1 resulted in significantly higher NUE in 2016, but not in 2017. WUE was significantly higher under N2 in 2017, while in 2016, there was no difference. No significant interaction between irrigation and N rate was detected.

3.4.4. Yukon Gold

WUE responses were inconsistent across the two years. In 2016, WUE significantly increased under IRRG1 compared to IRRG3, while in 2017, no significant differences were found (

Table 11. Effect of deficit irrigation and nitrogen fertilizer application rates on water and nitrogen use efficiency of Yukon Gold in 2016 and 2017.

		Years
		2016		2017
Treatments		WUE	NUE	WUE	NUE
Water		kg ha−1 mm−1	kg ha−1 kg N−1	kg ha−1 mm−1	kg ha−1 kg N−1
IRRG3		90.55 b (4.10)	354.18 a (18.43)	77.35 a (3.11)	309.97 a (14.33)
IRRG2		98.56 ab (5.27)	319.32 ab (12.69)	62.52 a (4.28)	193.62 b (10.62)
IRRG1		111.05 a (6.39)	288.43 b (20.14)	70.58 a (5.31)	172.14 b (11.75)
Nitrogen
N1		102.55 a (4.86)	367.81 a (15.91)	68.43 a (4.07)	246.44 a (12.38)
N2		97.56 a (5.01)	273.48 b (14.27)	71.87 a (4.63)	204.04 b (9.96)
Source of Variation	DF	p-Value
Water	2	0.0445	0.0426	0.1926	<0.0001
Nitrogen	1	0.4312	0.0001	0.5966	0.0441
W × N	2	0.8370	0.5989	0.8741	0.3531

Means within the same columns followed by the same letters are not significantly different (p < 0.05). Values are presented as mean ± standard error (SE) of four replications in parentheses. IRRG3: Full Irrigation Water (100% ET), IRRG2: Deficit Irrigation Water (85 and 83% ET), IRRG1: Deficit Irrigation Water (69 and 61% ET) for 2016 and 2017, respectively. N1: nitrogen low levels (124 kg N ha⁻¹), N2: nitrogen recommendation level (158 kg N ha⁻¹), W × N: the interaction between water and nitrogen treatments. WUE: water use efficiency, NUE: nitrogen use efficiency.

). However, NUE was consistently and significantly higher under IRRG3 than under IRRG1 in both years, indicating a negative impact of severe water stress on N utilization. Nitrogen rate effects on WUE were not significant in either year, but NUE was consistently and significantly higher under N1 compared to N2. These results support the finding that reduced N application enhances NUE across different cultivars. No significant interaction was detected between irrigation and N treatments.

3.5. Correlation Coefficients

3.5.1. The Correlation Between Yield and Quality Traits

Quality traits (SG, SC, and TDM) were significantly and positively correlated with yield across all cultivars in 2016, except for Mesa Russet, which showed positive but not significant correlations (

Table 12. Correlation coefficients relating yield and quality traits for four potato cultivars during the 2016 and 2017 growing seasons.

Year	Trait	Canela Russet	Mesa Russet	Russet Norkotah 3	Yukon Gold
2016	SG	0.7447 ***	0.2804	0.5490 **	0.4344 *
	SC	0.7251 ***	0.3090	0.5434 **	0.4065 *
	TDM	0.7259 ***	0.3094	0.5451 **	0.4049 *
2017	SG	−0.0482	−0.1568	−0.3528	0.3016
	SC	−0.0544	−0.1509	−0.3720	0.2972
	TDM	−0.0532	−0.1499	−0.3704	0.2966

p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). SG: specific gravity, SC: starch content, TDM: tuber dry matter.

). However, in 2017, these correlations were weakly negative and not significant for all cultivars, except for Yukon Gold, which showed weak positive correlations with yield. This suggests a potential influence of seasonal or environmental variability.

3.5.2. The Correlation Between Yield and Resource Use Efficiencies

All cultivars had a highly significant positive correlation between yield and NUE in both years, except for Russet Norkotah 3 and Yukon Gold, which showed a significant positive association only in 2016, indicating that efficient N utilization is generally associated with higher yields and cultivar-specific responses to environmental conditions or variability in N uptake under stress (

Table 13. Correlation coefficients relating yield and resource use efficiencies for four potato cultivars during the 2016 and 2017 growing seasons.

	Trait	Canela Russet	Mesa Russet	Russet Norkotah 3	Yukon Gold
2016	WUE	0.3839	0.3116	−0.2517	−0.1335
	NUE	0.7767 ***	0.66756 ***	0.4049 *	0.5179 **
2017	WUE	0.0264	0.4615 *	−0.5484 **	0.2086
	NUE	0.7976 ***	0.8405 ***	0.3413	0.3208

p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). WUE: water use efficiency. NUE: nitrogen use efficiency.

). For the relationship between yield and WUE, Mesa Russet exhibited a positive, significant correlation in 2017 only, and Russet Norkotah 3 showed a significant negative correlation in 2017. None of the correlations between WUE and yield were significant in 2016.

4. Discussion

4.1. Tuber Internal and External Defects

Quality is one of the most important characteristics of potato [25], and quality is dependent on external and internal aspects of the tuber [26]. As the differences were non-significant (p > 0.05), the corresponding data were not presented. These findings align with previous research indicating that potatoes can tolerate moderate levels of water deficit without incurring substantial reductions in internal or external tuber quality [27,28].

4.2. Quality Traits

In this study, SG, SC, and TDM exhibited similar patterns of response across the four potato cultivars (Canela Russet, Mesa Russet, Russet Norkotah 3, and Yukon Gold). These quality traits are critical indicators of tuber processing and quality [29], and their responses to irrigation and N management offer valuable insights to optimizing production.

For most cultivars, there was no significant difference in SG, SC, and TDM between full irrigation (IRRG3) and moderate deficit irrigation (IRRG2); however, both treatments resulted in significantly higher values for quality traits in 2016 compared to severe deficit irrigation (IRRG1), with higher values under IRRG2 than IRRG3 for Canela Russet and Yukon Gold (Table 4 and Table 7). In contrast, Mesa Russet did not show significant differences among irrigation treatments in either year (Table 5). These findings are consistent with previous research, which has demonstrated that moderate reductions in irrigation can enhance tuber quality traits such as SG, SC, and TDM, while both excessive irrigation and severe deficits are detrimental [30,31,32]. In regard to N management, SG, SC, and TDM were not significantly affected by N rate in most cultivars and years. However, in Yukon Gold in 2016, lower N (N1) was associated with a significantly higher SG compared to the recommended rate (N2). Other researchers have reported that tuber quality differs depending on cultivar, in particular in their response to water stress [32,33]. The yield dilution effect can cause differences in the same cultivar across years, usually causing a slight decrease in quality due to increased tuber mass and resulting in a lower concentration of solids per unit weight [14]. These results underscore the importance of managing both irrigation and N inputs in an integrated manner. Optimizing moderate deficit irrigation (IRRG2) and avoiding excessive N application appear to be key strategies for maximizing SG, SC, and TDM, thereby improving overall tuber quality without compromising yield. The cultivar-specific responses observed also indicate that recommendations should be tailored to the characteristics of each variety for best results.

4.3. Relationship Between Yield and Quality Traits

Yield was generally higher in 2016 [7], while SG, SC, and TDM were higher in 2017 (Table 4, Table 5, Table 6 and Table 7). Yield was positively correlated with SG, SC, and TDM in 2016 but not in 2017 (Table 12). These contrasting trends may be explained by differences in seasonal weather conditions. In 2016, precipitation aligned with the tuber bulking stage, which likely supported both sustained vegetative growth and starch accumulation (Figure 1). In contrast, 2017 experienced less precipitation early in the season followed by uneven rainfall later (July and September), which may have influenced plant productivity during critical growth stages. In addition, the precipitation distribution in 2017 could also help explain why yield and quality traits were not positively correlated that year. In general, optimal management (balanced water and N) can help achieve both good yield and tuber quality [34], but sometimes, management practices or environmental conditions that maximize yield can reduce tuber quality; for example, excessive irrigation or N levels may increase yield but reduce quality. On the other hand, limited irrigation can reduce both yield and quality [35,36].

4.4. Agronomic Water and Nitrogen Use Efficiency

WUE was influenced by irrigation levels during only one of the two growing seasons for most cultivars, except Canela Russet which showed a consistent response across both years (Table 8, Table 9, Table 10 and Table 11). For Canela Russet, the severe deficit irrigation treatment (IRRG1) had significantly higher WUE than full irrigation (IRRG3) in both years. N application rate did not have a consistent effect on WUE across cultivars or years. A significant effect was observed in only one of two years for most cultivars, and no significant effect was found for Yukon Gold in either year. The lack of consistent response may be due in part to environmental variation between the two years. In general, WUE decreased as irrigation level increased, a trend consistent with previous research reporting that applying an 80–90% ET water deficit at the tuber formation stage did not significantly reduce yield (p > 0.05), but significantly improved WUE [37]. Differences in WUE among cultivars were minimal, though year-to-year variability was observed, likely due to climatic factors. Previous studies have found that under moderate water stress, potato transpiration decreases more than photosynthesis, enhancing WUE [16,29,38,39]. However, under severe drought conditions, stomatal closure reduces both transpiration and photosynthesis, leading to declines in both WUE and yield [40,41].

NUE was significantly influenced by both irrigation and N application rates. The response was generally similar among the four potato cultivars and years (Table 8, Table 9, Table 10 and Table 11). NUE was significantly higher under IRRG3 compared to severe deficit irrigation IRRG1, highlighting the importance of adequate water supply for optimal N uptake and yield. These findings are consistent with findings reported in the literature showing that proper irrigation can improve the partial productivity of N fertilizer [42,43]. NUE was consistently higher at the lower nitrogen rate (N1) compared to the recommended rate (N2) in both years, except for Russet Norkotah 3, which showed no significance in one of the two years. These results align with previous researchers who reported that NUE is negatively correlated with the amount of N applied as long as the yield is not limited by N [16,44,45,46]. These results also align with previous research documenting that a lower N treatment resulted in significantly higher N recovery (61% of applied N) [47]. Furthermore, we used a split application of N in both N treatments to improve NUE, which is supported by previous research showing that the timing of N application improves absorption efficiency by targeting N requirements at specific growth stages [48,49]. These findings suggest that, with appropriate irrigation and N management, potatoes can be produced with an acceptable yield and improved NUE.

4.5. Correlation Between Yield and Resource Use Efficiencies

The relationship between yield and WUE varied across cultivars and years (Table 13). While most cultivars showed a positive relationship between WUE and yield, these relationships were generally not statistically significant, and in some cases, negative correlations were observed. These mixed results are consistent with previous research indicating that reducing water application rates can enhance WUE and, in some cases, improve yield as well. Reducing water by less than 45% has been shown to increase potato WUE by approximately 10%, while limiting yield losses to around 16% on average [50]. Thus, mild water stress has the potential to improve WUE without dramatically affecting yield, but severe water stress is likely to reduce yield and WUE. It is evident that cultivar, management practices, and environmental conditions strongly influence the relationship between yield and WUE.

NUE values were consistently and significantly positively correlated with yield for all cultivars, especially in 2017. Increased yield increases NUE by definition, and in our study, a 20% reduction in N application generally did not decrease yield [7], resulting in increased NUE. Splitting N applications at planting and throughout the growing season is considered a Best Management Practice which optimizes both NUE and yield, and this practice was incorporated in our study and likely contributed to the improved NUE as well. This observation agrees with previous findings which highlighted the importance of N management in achieving optimal yield and resource efficiency in potato [51].

5. Conclusions

Deficit irrigation and reduced N application significantly influenced tuber quality traits, WUE, and NUE in the potato cultivars evaluated over two growing seasons in Colorado’s San Luis Valley. Moderate deficit irrigation (~80–85% ET) improved or maintained key quality attributes (SG, SC, and TDM). In contrast, severe deficit irrigation (~60–70% ET) adversely affected these traits in most cultivars. Reducing N application (131 kg N ha⁻¹) improved NUE across all cultivars without negatively impacting yield [7], SG, SC, or TDM, supporting its use as an efficient alternative to the standard recommended rate (165 kg N ha⁻¹). Notably, the combination of moderate water deficit and reduced N proved optimal for improving resource use efficiency while sustaining tuber quality. By applying moderate deficit irrigation (18% reduction) and 20% reduced N fertilizer, growers can improve resource efficiency and maintain tuber quality, contributing to more sustainable and cost-effective potato production systems.