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Sustainability 2017, 9(3), 389; doi:10.3390/su9030389

Article
Phenotypic Responses of Twenty Diverse Proso Millet (Panicum miliaceum L.) Accessions to Irrigation
1
Department of Crop and Soil Sciences, College of Agricultural, Human, Natural Resource Sciences, Washington State University, P.O. Box 646420, Pullman, WA 99164-6420, USA
2
Department of Mathematics and Statistics, Center for Interdisciplinary Statistical Education and Research, Washington State University, Pullman, WA 99164-3113, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Iain Gordon
Received: 17 November 2016 / Accepted: 5 March 2017 / Published: 7 March 2017

Abstract

:
To date, little research has been conducted on the phenotypic responses of proso millet to drought and deficit irrigation treatments in the dryland wheat-based cropping systems of the Palouse bioregion of the U.S. The objectives of this study were to evaluate critical agronomic traits of proso millet, including emergence, plant height, days to heading, days to maturity, and grain yield, with and without supplemental irrigation. Twenty diverse proso millet accessions, originating from Bulgaria, Czechoslovakia, Morocco, the former Soviet Union, Turkey, and the United States, were grown in irrigated and non-irrigated treatments under organic conditions in Pullman, WA, from 2012 to 2014. Irrigation was shown to significantly improve emergence and increase plant height at stem extension and to hasten ripening of all the varieties, whereas heading date was not affected by irrigation in two of the three years tested. Irrigation resulted in higher mean seed yield across all varieties, with ‘GR 665’ and ‘Earlybird’ performing best under irrigation. Seed yield was highest in ‘GR 658’ and ‘Minsum’ in the non-irrigated treatment, suggesting the importance of identification and utilization of varieties adapted to low rainfall conditions. The highest yielding varieties in irrigated systems are unlikely be the highest yielding in dryland systems. Our results suggest that millet has potential as a regionally novel crop for inclusion in traditional dryland cropping rotations in the Palouse ecosystem, thereby contributing to increased cropping system diversity.
Keywords:
irrigation; proso millet; Pacific Northwest; crop rotation; nutrition and health benefits

1. Introduction

Frequent and unpredictable drought conditions, combined with often inadequate access to irrigation, are permanent constraints to the optimization of agricultural production in many regions of the world [1,2]. Development and further refinement of dryland crop production approaches and strategic substitutions of water demanding crops with drought adapted crops can enhance the sustainability of future agricultural production in regions without a reliable supply of water [3,4]. Several species of millets are cultivated primarily in marginal agronomic environments due to their high-water use efficiency and can be grown in arid environments ranging from 200 mm to over 500 mm of average annual rainfall [1]. In addition to drought tolerance, millets can withstand intense heat and are resilient to the extreme climatic and soil conditions prevalent in semi-arid regions [5,6].
Proso millet (Panicum miliaceum L.), also known as white millet, red millet, broomcorn millet, common millet, broomtail millet, and hog millet, is a warm-season grass adapted to diverse soil and climatic conditions. The shallow root system of proso millet, usually limited to the upper 90 cm of soil, confers a comparatively high water use efficiency, and millet varieties are capable of producing seeds from 60 to 110 days after planting [6,7,8]. Proso millet in the U.S. was grown, primarily as a dryland crop, on 204,366 ha in 2016 [9]. Irrigation is typically applied on approximately 4000 ha and about half of these hectares are located in Nebraska [10]. Close to 100 mm of water is required for the initiation of seed formation in proso millet, which is lower than for wheat (127 mm), sunflower (177 mm), and corn (228 mm) [8]. McDonald et al. [11] found that in Colorado, the total annual crop water requirement of proso millet is approximately 330 mm to 355 mm. Proso millet has been shown to produce grain using as little as 152 mm of total water, which is among the lowest of any major cereal [8].
Proso millet is considered the most suitable rotational crop in the majority of dryland wheat production areas in the semi-arid High Plains region of the U.S. [12]. When planted in a wheat/fallow rotation in the High Plains, proso millet improves the control of volunteer wheat and winter annual grassy weeds, reduces insect and disease pressure, and maintains adequate soil moisture for deeper rooted crops due to its shallow root systems and high water use efficiency [8,13,14].
In this study, we evaluated seed yield and important agronomic characteristics of 20 diverse proso millet accessions under irrigated and non-irrigated conditions in the wheat-based farming Palouse environment of eastern Washington, U.S. The overall goal of this study was to explore the potential for proso millet to be included as a rotational crop in dryland farming systems in the Palouse. Our specific objectives were to: (1) identify proso millet genotypes with enhanced emergence, early maturity, and optimal yield under dryland conditions; (2) evaluate proso millet seed yield in the Palouse environment when soil moisture is not the major limiting factor; and (3) determine whether the highest yielding millet varieties under irrigation were also the highest yielding varieties in dryland systems.

2. Materials and Methods

2.1. Location

A three-year study (2012–2014) was conducted on a certified organic research farm located at Tukey Orchard in Pullman, Washington (46.7325°N Lat., 117.1717°W Long.). Meteorological data were obtained from Pullman meteorological station situated at 46.7°N Lat., −117.15°W Long, and elevation 759.86 m. Pullman received total annual precipitation of 496 mm in 2012, 349 mm in 2013, and 430 mm 2014 [15]. The majority of this precipitation occurred during the winter and early in the spring. As is typical, summers were mostly dry and hot (Table 1).

2.2. Experimental Design and Data Collection

The experimental design was a split-plot randomized complete block design with three replicates. Main plots were irrigated and non-irrigated treatments. Sub-plots were 20 accessions (henceforth to be termed varieties) of proso millet (Table 2) obtained from USDA-ARS, National Resource Program, Iowa State University Regional Plant Introduction Station (Ames, IA, USA). The 20 varieties originated from six different countries including Bulgaria, Czechoslovakia, Morocco, the former Soviet Union, Turkey, and the United States. In years two and three of this experiment, seed was used from the previous year’s trial. Care was taken to maintain varietal integrity and seed quality. Seed germination rate was above 98% for all accessions each year in germination tests performed at WSU. Plot size was 0.45 m2. Each plot was hand planted using 33 seeds each, with 30 cm spacing between plots. Growing degree days (GDD) at planting is shown in Table 1. GDD was calculated using a base temperature of 10 °C [15] and millet plots were harvested individually upon maturity.
Irrigation was applied at a rate of 24 mm/week using 15 mL high flow drip tape with 20 cm emitter spacing (Drip Works, Willit, CA, USA). Initial watering dates varied from year to year, 25 June 2012 (655 GDD), 9 July 2013 (641 GDD), and 9 June 2014 (872 GDD), and irrigation was applied twice weekly until harvest.
Percent emergence was estimated by counting the number of emerged seedlings per plot and dividing by 33. Plant height was measured using three randomly selected subsamples per plot at two growth stages: (1) Feekes 8, stem extension/flag leaf visible (PH1); and (2) Feekes 11.4, ripening (PH2) [16,17]. Plant height measurements at stem extension were taken on the following dates: 20 July 2012 (439 GDD), 30 July 2013 (465 GDD), and 10 August 2014 (347 GDD). Heading was quantified by the number of days from planting until 100% heading emergence. Maturity was measured as number of days from planting until harvest.
Plots were harvested individually at maturity using sickles to cut the stems of the plants. All plants in a plot were then bundled and threshed using a Vogel thresher (Bill’s Welding, Pullman, WA, USA). The seeds were then processed with a 3.18 mm (8/64 inch) screen to separate the seed from the larger stem pieces by hands. Seeds were next rubbed to remove the remainder of the seed chaff from the seeds until clean. Seeds were further cleaned using a homemade air-blower to separate the smaller particles and immature seeds from the mature seeds, then the seed was sieved through a 2.78 mm (7/64 inch) screen (Seedburo, Des Plaines, IL, USA) for final removal of any foreign plant material.

2.3. Statistical Analysis

Statistical analysis was performed using the statistical software SAS 9.2 (32) (SAS Institute Inc., Cary, NC, USA). Mixed effects methodology was used to analyze the response data. Continuous responses (plant height, days to heading and maturity, and yield) were either normally distributed or could be made sufficiently normal using a logarithmic transformation and were analyzed using a linear mixed model with PROC MIXED. The binary outcome (plant emergence) was analyzed using a logistic mixed model with PROC GLIMMIX (SAS 9.2). In two cases (plant emergence in 2013 and 2014), no random effects could be estimated and PROC GENMOND—which does not allow random effects—was used to estimate this simpler model. Fixed effects for each model included irrigation, variety, and their interactions. If an interaction and/or main effect were not significant, those terms were removed from the model. A random effect of replicate nested within irrigation status was included in the estimation of each model to account for correlation of measurements within plots. Due to yearly differences in the plants that did not emerge, interaction analyses for variety and year were not estimable and analyses were performed separately for each year. Model assumptions were verified using marginal and conditional studentized residuals from PROC MIXED and studentized residuals from PROC GLIMMIX. A logarithmic transformation was used for yield and plant height to satisfy the homogeneity of variance assumption. Contrasts were calculated to show which of the 20 varieties differed by irrigation status. The statistical significance level was set at α = 0.05. In addition to raw p-values, to ensure an overall false positive level of 0.05 for each trait, p-values were adjusted for multiple comparisons using Hommel’s procedure [18,19].
Spearman’s rank correlation coefficient (RS) was used to determine the level of rank correlation between yield of all the 20 varieties in irrigated and non-irrigated treatments. RS was calculated using the following equation:
R s = 1     6   d 2 n 3 n
where d 2 is the difference in rank change of each variety and summed for all 20 varieties, and n is the number of varieties. Statistical significance was assessed at the 5% significance level.

3. Results

3.1. Yield

In 2012, there was a significant variety × irrigation interaction for yield (p = 0.0057) (Table 3). When comparing responses of varieties across treatments, the results indicated that most of the varieties were significantly affected by irrigation except for Dari, Tlicevskoje, GR 658, GR 664, Bolgar 159, Tuvinskoe, Turghai, Minsum, TU-85-74-03, and TU-85-087-01 (p > 0.05) (Table 4). In addition, the p-values adjusted for multiple comparisons further showed that GR 665, Komsomolskoe 996, and Earlybird were also not affected by irrigation (p > 0.05). In contrast, Kamusinszkoe 67, Kazanskoe 176, Veszelopodoljanszkoe 403, Unikum, Sunup, and Sunrise were significantly affected by irrigation (p < 0.05). The irrigated treatment and non-irrigated treatment yielded a total average of 55 g/plot and 18 g/plot, respectively. The highest yielding variety within irrigated treatment was Veszelopodoljanszkoe 403 (100 g/plot) and Minsum (50 g/plot) was the highest yielding in the non-irrigated treatment. In 2012, grain yield was moderately correlated with PH1 (r = 0.53; p = 0.0004) and strongly correlated with PH2 (r = 0.75; p ≤ 0.0001); however, no correlation was found between grain yield and either days to heading or days to maturity.
In 2013, grain yield was significantly affected by irrigation. When comparing responses of varieties across treatments, all varieties were significantly affected by irrigation (p = 0.0002) (Table 3). This is different from 2012, where some varieties did have significantly higher yields in response to irrigation. These results are interesting due to the increased precipitation in 2013 (~121 mm from June to September) compared to 2012 (~43 mm from June to September). Average yields of irrigated and non-irrigated treatments were 207 g/plot and 5 g/plot, respectively. The highest yielding cultivar within the irrigated treatment was Earlybird (365 g/plot) and Unikum (14 g/plot) was the highest yielding in the non-irrigated treatment. Similar to 2012, grain yield in 2013 was strongly correlated (p < 0.0001) to both PH1 and PH2 (r = 0.81 and r = 0.87, respectively). Again, no relationship was found between yield and either days to heading or days to maturity; however, a marginally significant and relatively weak correlation was found between yield and emergence (r = 0.28; p = 0.09).
In 2014, yield was significantly affected by irrigation; when comparing responses of varieties across treatments, all varieties were significantly affected by irrigation (p = 0.0001), similar to the results found in 2013 (Table 3). The irrigated and non-irrigated treatments had mean plot yields of 21 g/plot and 4 g/plot, respectively. The highest yielding variety within the irrigated treatment was GR 665 (112 g/plot), and Turghai and Sunup (12 g/plot each) were the highest yielding varieties in the non-irrigated treatment (Table 5). Pearson correlation results in 2014 were quite different from 2012 and 2013. For example, no relationship was found between grain yield and PH1, or emergence, but correlations were found between grain yield and days to heading (r = 0.55; p = 0.005), days to maturity (r = 0.47; p = 0.02), and PH2 (r = 0.45, p < 0.05).

3.2. Emergence and Plant Height

Irrigation had a significant impact on plant emergence and stand establishment. Mean emergence rates were 52% in irrigated treatments and 24% in the non-irrigated treatments across all of the three growing seasons. In 2013, there was a significant interaction between irrigation and variety (p = 0.0039) (Table 3). Irrigation significantly affected the emergence rates of the varieties Tlicevskoje, GR 658, GR 664, Kamusinszkoe 67, and Minsum (Table 4). Hommel-adjusted p-values were estimated (p > 0.05) across all varieties except variety GR 658 (p = 0.0162). In 2014, there was a significant interaction between irrigation and variety (p < 0.0001); irrigation significantly affected the emergence rate of all the varieties (p < 0.0001) except Turghai (p = 0.2071) (Table 3 and Table 4). Hommel-adjusted p-values were estimated (p < 0.05) across all varieties except Turghai (p = 0.2071). In 2013 and 2014, there was a significant interaction between variety and irrigation on emergence (Table 3).
Across all three years, the varieties with the highest emergence rates under irrigation were Unikum, GR 664, Tlicevskoje, GR 665, and GR 658, with 94%, 84%, 83%, 70%, and 68% emergence, respectively, whereas Turghai, Huntsman, Minsum, TU-85-087-01, and Sunup had 13%, 19%, 30%, 32%, and 34% emergence, respectively. In the non-irrigated treatment, Minsum, GR 665, Unikum, Tlicevskoje, and Veszelopodoljanszkoe 403 had the highest emergence rates, with 53%, 49%, 46%, 45%, and 34%, respectively. Turghai, TU-85-087-01, Huntsman, Kamusinszkoe 67, and Tuvinskoe had low emergence rates with 10%, 11%, 12%, 13%, and 17% in the non-irrigated treatment, respectively (Table 5). Turghai, TU-85-087-01, and Huntsman showed the lowest emergence across irrigation treatment, whereas GR 665, Unikum, and Tlicevskoje had among the highest emergence across irrigation treatment. Minsum had 30% emergence in the irrigated treatment, and 53% emergence in the non-irrigated treatment.
In all three years, irrigation had a significant effect on PH1 and PH2 across all varieties (p < 0.0001) (Table 4). A significant interaction between irrigation and variety was detected at PH2 in 2012 and 2013 (Table 3). No significant variety × irrigation interaction was found at stem extension (PH1) in any of the three years tested (Table 3). Several varieties in the irrigated treatment lodged before harvest. In 2012, lodged varieties included Unikum, TU-85-074.03, and TU-85-087-01. In 2013 and 2014, varieties that lodged before harvest included Dari, Tuvinskoe, Veszelopodoljanszkoe 403, Unikum, Minsum, and TU-85-074-03. Other varieties either remained completely upright or showed minor lodging. For all three years of the experiment the non-irrigated plots did not show any signs of lodging.

3.3. Days to Heading and Maturity

Irrigation did not have an effect on heading date in 2012 and 2014; however, in 2013, a significant variety × irrigation interaction was observed (Table 3). In 2013, days to heading of varieties such as Dari, GR 658, Komsomolskoe 996, Tuvinskoe, Veszelopodoljanszkoe 403, Unikum, and TU-85-074-03 were significantly affected by irrigation treatment (p < 0.05) (Table 4).
Turghai, Bolgar 159, Kazanskoe 176, Dari, and Earlybird had the earliest heading dates in both irrigated and non-irrigated fields with 49, 50, 51, 52, and 52 days, respectively. GR 664, Tlicevskoje, GR 658, GR 665, and Huntsman had delayed heading dates in both irrigated and non-irrigated treatments at 75, 75, 73, 71, and 71 days, respectively (Table 5). Days to heading was strongly correlated to days to maturity (r = 0.76; p < 0.0001) and moderately correlated to grain yield (r = 0.43; p < 0.0001) (Table 6), but showed no relationship with other traits.
All varieties except Bolgar 159, Kamusinszkoe 67, Kazanskoe 176, and TU-85-074-03 were affected by irrigation (Table 4). In addition to those varieties that were not affected by irrigation, the Hommel-adjusted p-values indicated that maturity for Dari, Veszelopdoljanszkoe 403, Sunup, and Earlybird were also not affected by irrigation (p > 0.05). Tlicevskoje, GR 664, GR 665, Komsomolskoe 996, Tuvinskoe, Unikum, and Minsum were significantly affected by irrigation (p < 0.05).
In 2014, there was a highly significant irrigation × variety interaction (p < 0.0001) (Table 3). Irrigation had no effect on time to maturity for all varieties tested except Komsomolskoe 996 and Kazanskoe 176 (p < 0.0001) (Table 4). Hommel-adjusted p-values were estimated (p < 0.0001) for the same varieties (Komsomolskoe 996 and Kazanskoe 176) (Table 4). However, our data were not consistent with other reports on soybean [20], pea [21], and corn [22], where water deficit decreased seed-filling duration. Across all three years, the five varieties with the quickest maturity in both irrigated and non-irrigated fields were Bolgar 159, Kamusinszkoe 67, TU-85-087-01, Turghai, and Tuvinskoe with 82, 83, 85, 86, and 86 days, respectively. Tlicevskoje, GR 665, GR 664, GR 658, and Huntsman required more days to maturity in both irrigated and non-irrigated with 115, 115, 114, 110, and 107 days, respectively (Table 5). Days to maturity was negatively correlated with PH1 (r = −0.37; p < 0.0001) and PH2 (r = −0.23; p = 0.017) (Table 6).

4. Discussion

4.1. Yield

Selection of varieties with high grain yields in drought stressed conditions is a major goal in many cereal breeding programs [23]. Grain yield is the result of the expression and association of several plant growth components and conditions [24]. Abiotic stressors such as extreme temperature and low water availability are often the most important restricting factors in the growth and productivity of major cereal crop species [2,25]. As expected, irrigation increased grain yield of proso millet significantly in this present study (Table 4). Across all three years, grain yields were highest in irrigated treatments (Table 5) and the top five yielding varieties were GR 665, Earlybird, Sunup, Sunrise, and GR 664 with 166, 146, 141, 136, and 125 g/plot, respectively.
These results are consistent with previous reports which showed that water stress in millet reduced seed yield [26]. Yadav et al. [27] reported that grain yield decreased 5% to 19% in terminal drought stress environments compared to a fully irrigated treatment. In this study, we were able to identify specific varieties which yielded well despite conditions of drought. GR 658, Minsum, TU-85-074-03, Turghai, and Tuvinskoe were high yielding in the non-irrigated treatments with 29, 27, 24, 21, and 20 g/plot, respectively. The first two weeks after planting are a critical period when determining the success of a proso millet crop in the Palouse. In 2012, even though drought was the most severe from July to September, not all varieties were responsive to irrigation due to the adequate precipitation received in June during the first two weeks after planting in 2012. This is in contrast to 2014, which had precipitation more evenly distributed over the growing season, but significantly less during the important weeks directly after planting. Reduction of grain yield under conditions of drought stress can be caused by several regulative mechanisms that plants use to withstand against water stress, such as reduction in number of tiller for millet and reduction in ear size for maize [26,28]. Hussain et al. [29] reported that drought causes impaired mitosis, cell elongation, and expansion, leading to the reduction of plant growth and yield traits.
Across all three years, grain yield was positively correlated with plant height (r = 0.45, p < 0.0001 for PH1; r = 0.65, p < 0.0001 for PH2) and days to heading (r = 0.42, p < 0.0001), but did not show any relationship with days to maturity (Table 6). Spearman’s rank correlation coefficient (RS) for yield was non-significant (p < 0.05) for varietal changes in rank between irrigated and non-irrigated treatments. RS was 0.18, 0.40, and 0.29 in 2012, 2013, and 2014, respectively (Figure 1). Because there was no significant correlation in rank among the twenty varieties for yield between irrigated and non-irrigated treatments (Figure 1), we suggest that the varieties optimally adapted to dryland farming systems are not necessarily the same varieties best adapted to irrigated farming systems. To test for the optimal irrigation requirements of proso millet in the Palouse, a potential next step would be to choose a smaller set of varieties, and grow them in larger plots with more irrigation treatments.

4.2. Emergence and Plant Height

Water deficit causes impaired germination and poor crop stand establishment [30], and water availability during the first two weeks after planting proso millet are the most critical periods when growing proso millet; during this period even a light rain can be very helpful in boosting germination rates [14]. Irrigation had a significant impact on plant emergence and stand establishment. Mean emergence rates were 52% in irrigated treatments and 24% in the non-irrigated treatments across all of the three growing seasons. Similarly, in sunflower, Kaya [31] reported that water deficit severely reduced germination and seedling stand, and delayed germination by one to two days.
In the present study, the varieties Minsum, GR 665, Unikum, Tlicevskoje, and Veszelopodoljanszkoe 403 had the highest emergence rates without supplemental irrigation, whereas Turghai, TU-85-087-01, Huntsman, Kamusinszkoe 67, and Tuvinskoe had the lowest emergence rates (Table 5). This information is particularly useful to farmers without access to irrigation. Interestingly, Minsum was the only variety to consistently have higher emergence in the non-irrigated treatment than in the irrigated treatment. Across years and treatments, emergence was positively correlated with plant height (r = 0.60; p < 0.0001 for PH1; r = 0.41; p < 0.0001 for PH2) but did not show any relationship with emergence, days to heading, or days to maturity (Table 6).
Across all three years, each variety in the irrigated treatment was taller than in the non-irrigated treatment at PH1 and ripening (PH2) (Table 5). Similarly, drought stress and water scarcity have been reported to reduce plant height on switchgrass (Panicum virgatum), channel millet (Echinochloa turneriana), barnyard millet (Echinochloa crus-galli), and pearl millet (Pennisetum americanum) [32,33]. Drought reduces leaf size, stem extension, and root proliferation, and this causes disruption of photosynthetic pigments and reduces the gas exchange leading to a reduction in plant growth and productivity [23,24]. Cell elongation of higher plants can be inhibited by interruption of water flow from xylem to the surrounding elongating cells under water deficit conditions [34].

4.3. Days to Heading and Maturity

The appropriate matching of the pattern of inflorescence development and the time of flowering to the temporal variation in water availability is recognized as one of the most important traits conferring adaptation to drought [35,36].
The process of grain filling, the accumulation of reserve nutrients in the developing and maturing grain, is also sensitive to environmental conditions strongly affecting final yield [37]. Our study indicated that no irrigation effect was observed across varieties in 2012 for days to maturity. In 2013, there was a significant variety × irrigation interaction (p = 0.0015) (Table 3). Days to maturity was negatively correlated with PH1 (r = −0.37; p < 0.0001) and PH2 (r = −0.23; p = 0.017) (Table 6), indicating that the shorter plants tended to mature more quickly than the taller plants.
The most significant factors for heat stress-related yield loss in cereals include the high-temperature-induced shortening of development of vegetative phases, reduced light perception over the shortened life cycle, and perturbation of the processes associated with carbon assimilation (transpiration, photosynthesis, and respiration) [38]. It is critical to recognize how a particular crop shows signs of sensitivity to drought stress during floral initiation. Drought stress in barley was shown to be more sensitive during and just prior to spike emergence [39,40,41]. Water stress during flowering induction and inflorescence development was reported to cause a delay in flowering (anthesis) in pearl millet and sorghum [25]. Wopereis et al. [42] also reported a delay in flowering and maturity of two lowland rice cultivars caused by drought stress. However, the results from our study indicated that this does not necessarily apply to proso millet; with few exceptions, water stress did not affect flowering of proso millet.

5. Conclusions

Irrigation resulted in higher mean seed yield across all varieties, with ‘GR 665’ and ‘Earlybird’ performing best under irrigation, and ‘GR 658’ and ‘Minsum’ achieving the highest yields in the non-irrigated treatment. The Spearman’s rank correlation coefficient for yield was non-significant across varieties between irrigated and non-irrigated treatments. Irrigation was shown to significantly improve emergence and increase plant height at stem extension and ripening of all the varieties; whereas heading date was not affected by irrigation in two of the three years tested. Interestingly, Minsum was the only proso millet variety which achieved higher percent emergence under dryland conditions than under irrigation. This could be a useful trait to Palouse farmers, and future studies should explore and exploit possible mechanisms of, and explanations for, this important trait.
Our results indicate that: (1) the highest yielding varieties in irrigated systems are unlikely to be the highest yielding in dryland systems; and (2) in order to optimize yield of proso millet in dryland conditions, it is necessary to identify and utilize varieties adapted to low rainfall conditions. Our results further show that although irrigation results in higher yields compared to dryland production, the increased plant height due to irrigation also can result in lodging in certain varieties. Therefore, selection of millet varieties should be conducted with the production system of the target farmers in mind.

Acknowledgments

We thank Washington State University College of Agricultural, Human, and Natural Resource Sciences Undergraduate Research Internship Program and Washington State University Center for Transformational Learning and Leadership International Immersion for funding the research project that has generated this work. We also thank Washington State University Sustainable Seed Systems Lab (http://www.sustainableseedsystems.org/) for providing tools, guidance, and supervision on this work.

Author Contributions

Cedric Habiyaremye carried out the research and wrote the manuscript. Todd Coffey and Kevin M. Murphy edited the manuscript. Kevin M. Murphy conceived and coordinated the experiment. Victoria Barth and Kelsey Highet provided critical data and carried out the field work. All authors read and approved the final manuscript.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Spearman’s rank yield correlation irrigated vs non-irrigation treatments. The yield change in rank between Ir: irrigation (irrigated treatment) and N-Ir: non-irrigation (non-irrigated treatment) of proso millet varieties. The top five ranking varieties for yield in both irrigated and non-irrigated treatments were compared at each year. RS: Spearman’s rank correlation. Varieties are ranked from 1 = highest yield to 20 = lowest yield. RS = 0.18 (2012), RS = 0.40 (2013), and r = 0.29 (2014). Spearman’s rank correlation coefficient, tested (p < 0.05).
Figure 1. Spearman’s rank yield correlation irrigated vs non-irrigation treatments. The yield change in rank between Ir: irrigation (irrigated treatment) and N-Ir: non-irrigation (non-irrigated treatment) of proso millet varieties. The top five ranking varieties for yield in both irrigated and non-irrigated treatments were compared at each year. RS: Spearman’s rank correlation. Varieties are ranked from 1 = highest yield to 20 = lowest yield. RS = 0.18 (2012), RS = 0.40 (2013), and r = 0.29 (2014). Spearman’s rank correlation coefficient, tested (p < 0.05).
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Table 1. Precipitation and temperature recorded during the growing season (June to September of 2012, 2013, and 2014) in Pullman, WA.
Table 1. Precipitation and temperature recorded during the growing season (June to September of 2012, 2013, and 2014) in Pullman, WA.
YearMonthsGrowing Degree Days at PlantingTotal Precipitation [mm]Average Maximum Day Temperature [°C]
2012June74842.9319.8
July 027.8
August 029.5
September 024.6
2013June86254.3621.6
July 4.8329.6
August 6.3528.9
September 55.1222.1
2014June88119.0521.2
July 11.1830.8
August 9.1428.8
September 4.0624.2
Meteorological data were collected from Pullman, WA meteorological station situated at 46.7°N Lat., −117.15°W Long, and elevation 759.86 m. Source: [15].
Table 2. Twenty accessions of proso millet grown at the organic research farm at Tukey Orchard in Pullman, Washington in 2012, 2013, and 2014.
Table 2. Twenty accessions of proso millet grown at the organic research farm at Tukey Orchard in Pullman, Washington in 2012, 2013, and 2014.
ItemAccession NumberAccession NameYear CollectedOriginLatitudeLongitude
1PI 171727Dari1948Bolu, Turkey 40.6792°N31.5583°E
2PI 346937Tlicevskoje1969Former Soviet UnionN/AN/A
3PI 517017GR 6581986Ouarzazate, Morocco 30.9167°N 6.9167°W
4PI 517018GR 6641986Ouarzazate, Morocco 30.9335°N 6.9370°W
5PI 517019GR 6651986Ouarzazate, Morocco30.9335°N 6.9370°W
6PI 531398Bolgar 1591989Bulgaria42.7500°N25.5000°E
7PI 531410Kamusinszkoe 671989Former Soviet UnionN/AN/A
8PI 531411Komsomolskoe 9961989Former Soviet UnionN/AN/A
9PI 531412Kazanskoe 1761989Former Soviet UnionN/AN/A
10PI 531429Tuvinskoe1989Former Soviet UnionN/AN/A
11PI 531430Veszelopodoljanszkoe 4031989Former Soviet UnionN/AN/A
12PI 531431Unikum1989Czechoslovakia50.0833°N14.4167°E
13PI 536011Sunup1989Nebraska, United States 41.2324°N 98.4160°W
14PI 578073Earlybird1994Nebraska, United States41.2324°N 98.4160°W
15PI 578074Huntsman1994Nebraska, United States41.2324°N 98.4160°W
16PI 583347Sunrise1994Nebraska, United States41.2324°N 98.4160°W
17PI 649382Turghai1961North Dakota, United States 47.0000°N 100.0000°W
18PI 649385Minsum1980Minnesota, United States 46.0000°N 94.0000°W
19PI 654403TU-85-074-031986Bitlis, Turkey 38.4000°N 42.1083°E
20PI 654404TU-85-087-011986Bitlis, Turkey 38.4000°N 42.1083°E
N/A: Not available (The latitude and longitude information are not available).
Table 3. Analysis of Variance with F value for plant height, days to maturity, days to heading, and yield for proso millet varieties grown with and without irrigation over three crop years.
Table 3. Analysis of Variance with F value for plant height, days to maturity, days to heading, and yield for proso millet varieties grown with and without irrigation over three crop years.
YearsEffectDFEmergence RatePH1PH2DHDMYield
2012Irrigation
Variety
Irrigation × Variety
1
19
19
N/A18.06 *
3.20 ***
197.77 **
3.34 ***
1.78 *
46.94 ***12.87 ***81.89 ***
2.51 **
2.30 **
2013Irrigation
Variety
Irrigation × Variety
1
19
22.26 ***
248.74 ***
39.42 **
1304.54 ***
3.37 ***
2062.74 ***
8.36 ***
4.46 ***
13.31
17.59 ***
6.05 ***
(DF = 11)
101.94 ***
40.39 ***
3.13 **
(DF = 14))
3.35 ***
2.37 **
2014Irrigation
Variety
Irrigation × Variety
1
19
14
739.35 ***
91.04 ***
76.58 ***
608.05 ***122.48 ***
2.16 *
96.97 ***13.27 ***
41.60 ***
6.35 ***
43.03 ***
2.99 ***
DF: Degrees of freedom; PH1: plant height at stem extension; PH2: plant height at ripening. DH: days to heading, DM: days to maturity. Significant level at (p < 0.05) while * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 4. Mean Difference between irrigation and no irrigation for each variety of each trait: plant height, days to maturity, days to heading, and yield.
Table 4. Mean Difference between irrigation and no irrigation for each variety of each trait: plant height, days to maturity, days to heading, and yield.
Plant Name/YearEmergencePH1PH2DHDMYield
2012
DariNDC22.98 *4.12 ***NIENIE0.63
TlicevskojeNDC4.45 ***NIENIE1.68
GR 658NDC6.20 ***NIENIE0.71 *
GR 664NDC6.00 ***NIENIE1.60
GR 665NDC8.16 ***NIENIE2.76 **
Bolgar 159NDC4.00 ***NIENIE1.18
Kamusinszkoe 67NDC4.85 ***NIENIE4.00 ***
Komsomolskoe 996NDC5.14 ***NIENIE2.89 **
Kazanskoe 176NDC6.32 ***NIENIE3.82 ***
TuvinskoeNDC2.32 *NIENIE0.05
Veszelopodoljanszkoe 403NDC5.18 ***NIENIE4.11 ***
UnikumNDC5.55 ***NIENIE4.00 ***
SunupNDC3.18 **NIENIE3.80 ***
EarlybirdNDC4.12 ***NIENIE2.83 **
HuntsmanNDC5.38 ***NIENIE2.17 *
SunriseNDC3.34 **NIENIE3.21 **
TurghaiNDC4.40 ***NIENIE0.35
MinsumNDC5.10 ***NIENIE0.29
TU-85-074-03NDC4.57 ***NIENIE−0.50
TU-85-087-01NDC5.55 ***NIENIE1.26
2013
Dari1.04 14.39 ***−2.86 **−2.71 **
Tlicevskoje8.73 ** n/an/a−3.25 **
GR 65811.22 *** 17.42 ***3.44 **n/a
GR 6646.41 * 17.43 ***−0.42−3.83 ***
GR 6651.93 19.35 ***n/a−4.75 ***
Bolgar 1593.09 10.61 ***0.190.02
Kamusinszkoe 676.87 ** 9.73 ***0.07−0.21
Komsomolskoe 9963.83 16.20 ***−3.23 **−4.53 ***
Kazanskoe 1761.51 15.17 ***−0.00−0.00
Tuvinskoe2.5263.32 ***17.05 ***−3.64 ***−6.61 ***95.04 ***
Veszelopodoljanszkoe 4031.55 16.04 ***−3.61 **−2.65 *
Unikum2.86 13.32 ***−4.21 ***−4.75 ***
Sunup0.07 13.44 ***n/a−2.10 *
Earlybird0.60 12.60 ***n/a−2.10 *
Huntsman0.13 n/an/an/a
Sunrise1.14 n/an/an/a
Turghai0.21 16.98 ***n/an/a
Minsum3.88* 9.70 ***n/a−4.64 ***
TU-85-074-030.07 n/a−3.49 **−1.88
2014
Dari18.43 *** NIE−0.41
Tlicevskoje1720.2 *** NIE n/a
GR 65832.63 *** NIE−0.65
GR 66421.14 *** NIE−0.00
GR 66534.63 *** NIE−0.65
Bolgar 1591554.7 *** NIEn/a
Kamusinszkoe 671516.2 *** NIEn/a
Komsomolskoe 99627.58 *** NIE−6.86 ***
Kazanskoe 17633.89 *** NIE−7.03 ***
Tuvinskoe12.93 ***2.47 ***65.49 ***NIE0.87 *3.37 ***
Veszelopodoljanszkoe 40329.20 *** NIE−1.31 *
Unikum40.80 *** NIE−0.46
Sunup14.59 *** NIE0.44
Earlybird14.89 *** NIE1.23 *
Huntsman8.65 ** NIE0.00
Sunrise16.22 *** NIE0.00
Turghai1.59 NIE0.55
Minsum1431.1 *** NIEn/a
TU-85-074-031521.0 *** NIEn/a
TU-85-087-0115.86 *** NIE0.00
PH1: plant height at stem extension; PH2: plant height at ripening. DH: days to heading, DM: days to maturity. NDC: No data was recorded (in 2012, emergence data were not recorded); n/a: not available (missing data). Significant level at (p < 0.05) while * p < 0.05, ** p < 0.01, *** p < 0.001 (p-values not adjusted). When interaction effect was significant, mean differences are shown for each variety; when irrigation effect was significant but interaction was not, mean differences are the same for each variety; when no interaction or irrigation main effect was significant, NIE (no irrigation effect) was displayed.
Table 5. Mean data across years 2012, 2013, and 2014 for each trait in irrigated and non-irrigated treatments.
Table 5. Mean data across years 2012, 2013, and 2014 for each trait in irrigated and non-irrigated treatments.
Plant Name/YearEmergence Rate (%)PH1 (cm)PH2 (cm)DH (Day)DM (Day)Yield
(g/Plot)
Ir.N-Ir.Ir.N-Ir.Ir.N-Ir.Ir.N-Ir.Ir.N-Ir.Ir.N-Ir.
2012
Darin/an/a9368135101474690882816
Tlicevskojen/an/a74581299371751101057125
GR 658n/an/a71561459569731081085429
GR 664n/an/a805715310472691101086921
GR 665n/an/a69481498271731081109519
Bolgar 159n/an/a855912795444581826826
Kamusinszkoe 67n/an/a86651298950508088352
Komsomolskoe 996n/an/a90701359350498190306
Kazanskoe 176n/an/a92591247245447990404
Tuvinskoen/an/a9281129110504882796738
Veszelopodoljanszkoe 403n/an/a846313492504981901006
Unikumn/an/a83471308548518485724
Sunupn/an/a906813210654528898615
Earlybirdn/an/a796012894585291914912
Huntsmann/an/a7553127836662951015311
Sunrisen/an/a79601199159569193315
Turghain/an/a8765143107504781794629
Minsumn/an/a856214098535385867650
TU-85-074-03n/an/a846413496565591842645
TU-85-087-01n/an/a86661369152519185259
Mean 836113494565590925518
LSD (p < 0.05) 2.5 5 4 8.1 11.5
2013
Dari4331.7952214115607086981649
Tlicevskoje83.34578231573776n/a1141252381
GR 65863.321.78628164n/a7666108n/a180n/a
GR 66483.35092281684974761081212795
GR 66566.783.391311614376n/a1081222909
Bolgar 15948.328.382271212960608382891
Kamusinszkoe 6741.713.3883312945666690911669
Komsomolskoe 99666.743.39230137376673911052718
Kazanskoe 1766045923412532606083831842
Tuvinskoe38.321.7862814326647686108882
Veszelopodoljanszkoe 40366.750923213637647391991983
Unikum93.378.396371304960698810226814
Sunup28.33071221513374n/a1081173441
Earlybird403083241463672n/a1081173658
Huntsman11.71564n/a140n/a76n/a108n/a155n/a
Sunrise352579n/a155n/a74n/a108n/a336n/a
Turghai106.772n/a146n/a66n/a90n/a64n/a
Minsum3053.379271523569n/a1011172273
TU-85-074-0326.731.7783112438667690981293
TU-85-087-0121.78.39333121n/a646687n/a97n/a
Mean48358429142366869971062065
LSD (p < 0.05)25 3 8 4 3 43
2014
Dari4812901996324949929352
Tlicevskoje83n/a75n/a75n/a74n/a113n/a19n/a
GR 6587412781710017737511111326n/a
GR 66485381n/a94n/a798011311328n/a
GR 665741587798117170111113112n/a
Bolgar 15956n/a69n/a69n/a45n/a94n/a11n/a
Kamusinszkoe 6747n/a83n/a80n/a51n/a93n/a4n/a
Komsomolskoe 9966612775911751519211381
Kazanskoe 176738922891314848861036n/a
Tuvinskoe36127810671351n/a8986n/an/a
Veszelopodoljanszkoe 4036518901974165151939712n/a
Unikum9615941669144949929316n/a
Sunup40187399924545494931912
Earlybird49148210862555519693244
Huntsman2696610909707011311326n/a
Sunrise459755967656511311339n/a
Turghai1714801311360515194932612
Minsum30n/a78n/a109n/a54n/a93n/a34n/a
TU-85-074-0348n/a75n/a47n/a54n/a96n/a4n/a
TU-85-087-01421579166218555586867n/a
Mean5512.480138521575898101226.2
LSD (p < 0.05)12 3 8 1 3 7
Ir: irrigation (irrigated treatment); N-Ir: non-irrigation (non-irrigated treatment); n/a: not available (there was not data available). For the case of 2012 emergence rate data were not recorded. LSD: Least Significant Deference. LSD comparisons significant at the 0.05 level.
Table 6. Pearson correlation coefficient for percent emergence (PE), plant height (PH1 and PH2), days to heading (DH), days to maturity (DM), and yield, from 2012 to 2014.
Table 6. Pearson correlation coefficient for percent emergence (PE), plant height (PH1 and PH2), days to heading (DH), days to maturity (DM), and yield, from 2012 to 2014.
PH1PH2DHDM
PH1
PH20.86 ***
DH−0.120.09
DM−0.37 ***−0.23 *0.76 ***
Yield0.45 ***0.65 ***0.42 ***0.11
* p < 0.05, *** p < 0.001.
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