Comparative Drought Response in Eleven Diverse Alfalfa Accessions

Anower, M. Rokebul; Boe, Arvid; Auger, Donald L.; Mott, Ivan W.; Peel, Michael D.; Xu, Lan; Kanchupati, Praveena; Wu, Yajun

doi:10.1111/jac.12156

Cited by 27 publications

(32 citation statements)

References 59 publications

(122 reference statements)

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“…Erice et al [61] found that the WUE increased under a drought of 14 days and declined after a recovery period. Anower et al [3] found that the WUE increased with less irrigation applied, but the rising range varied between cultivars. Other studies found that the WUE decreased under dry conditions due to the differences in climate [30,50,62] The highest average WUE was obtained from the first growth period and decreased with successive growth periods.…”

Section: Water Use Efficiencymentioning

confidence: 97%

“…The groundwater table is 40-50 m below the ground surface. The soil in the experimental field was sandy loam with a mean dry bulk density of 1.52 g/cm 3 , a porosity of 52%, and a field capacity (FC) of 0.29 cm 3 /cm 3 for the 0-160 cm layer. Meteorological data, including precipitation, solar radiation, wind speed, air temperature, and relative humidity, were downloaded from the automatic weather station located in the experimental station.…”

Section: Experimental Sitementioning

confidence: 99%

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Alfalfa Water Use and Yield under Different Sprinkler Irrigation Regimes in North Arid Regions of China

2017

Sustainability

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Alfalfa (Medicago sativa) is one of the major crops grown in Northern China in recent years, however, the current serious water shortage conditions present a challenge to the growth of this crop, especially if efficient use of water is considered in forage production for sustainability. This study aimed to evaluate alfalfa productivity and water use efficiency (WUE) under different sprinkler irrigation levels. This experiment was conducted at Shiyanghe Experimental Station for Water-Saving in Agriculture and Ecology of China Agricultural University in Wuwei, Gansu, China, over a period of two years. There were three irrigation treatments: A1: 100% measured evapotranspiration (ETc) of alfalfa; A2: irrigation amount was 66% of A1; A3: irrigation amount was 33% of A1; and a control of A4: no irrigation during the growing season. A randomized block design with three replications were applied. The results showed that the ETc and forage yield of alfalfa decreased, while WUE and crude protein (CP) increased with the decreasing irrigation amounts. The seasonal average ETc and yield ranged from 412 mm to 809 mm and from 11,577 to 18,636 kg/ha, respectively, under different irrigation levels. The highest yields were obtained from the first growth period in all treatments in both years, due to the winter irrigation and the longest growth period. Alfalfa grown under lesser irrigation treatment conditions had higher variability in ETc and yield, mainly due to the variability in the amount of rainfall during the growth period. The seasonal average WUE of treatments ranged from 22.78 to 26.84 kg/(mm·ha), and the highest WUE was obtained at the first growth period, regardless of treatments. Seasonal average CP content ranged from 18.99% to 22.99%. A significant linear relationship was found between yield and ETc or irrigation amount, and the fitting results varied between growth periods and years. The present results also implied that winter irrigation provided the space for saving water and should be applied at the end of each growing season to fill the soil profile, and to maintain a greater yield in the next growing season. During the growing season, more irrigation should be concentrated in the early growth period, especially in the second growth period.

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Section: Water Use Efficiencymentioning

confidence: 97%

Section: Experimental Sitementioning

confidence: 99%

Alfalfa Water Use and Yield under Different Sprinkler Irrigation Regimes in North Arid Regions of China

2017

Sustainability

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“…Alfalfa is one of the most commonly grown forage crops in the world due to its quality and quantity of production, perennial growth and its capability to improve the soil nitrogen holding of the cultivated land (Rokebul Anower et al., , ; Campanelli et al., ; Rokebul Anower et al., ). Alfalfa is considered a salt‐sensitive crop and its production is hampered when soil salinity reaches above 22 m M NaCl (Campanelli et al., ; Rokebul Anower et al., ).…”

Section: Introductionmentioning

confidence: 99%

Physiological processes associated with salinity tolerance in an alfalfa half‐sib family

Anower

Peel

Mott

et al. 2017

J Agronomy Crop Science

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We previously reported an alfalfa half‐sib family, HS‐B, with improved salt tolerance, compared to parental plants, P‐B. In this study, we conducted additional experiments to address potential physiological mechanisms that may contribute to salt tolerance in HS‐B. Vegetatively propagated HS‐B and P‐B plants were treated with a nutrient solution (control) or a nutrient solution containing NaCl (EC = 12 dS/m). Shoots and roots were harvested at various time points after treatment for quantification of proline, soluble sugar, and H2O2 using spectrophotometers. Subcellular localization and quantification of Na in roots were conducted using a Na+‐specific dye under a confocal microscope. HS‐B produced 86 and 89% greater shoot and root dry biomass, respectively, compared to parental plants, P‐B, under salinity in the greenhouse. Under saline conditions the HS‐B shoots accumulated 115% and roots 55% more soluble sugars than P‐B counterparts. The non‐saline HS‐B shoots, however, showed 72% less soluble sugars than the non‐saline P‐B plants. Under saline conditions HS‐B accumulated 39% less proline in shoots, while roots accumulated 56% more proline, compared to their P‐B parents. HS‐B plants also showed a greater reduction of stomatal conductance under mild saline stress. HS‐B shoots and roots contained 3–4 times less reactive oxygen species (H2O2) after salt treatment compared to P‐B plants. Sodium localization and distribution analysis using Na+‐specific dye revealed HS‐B plants accumulated 88% and 48% less Na+ in stele and xylem vessels compared to P‐B. The study provides insights into the potential mechanisms that may contribute to salt tolerance in HS‐B: maintaining RWC by accumulating soluble sugars while reducing transpiration, maintaining healthy status by reducing oxidative stresses, and preventing salt toxicity by reducing accumulation of Na+ inside root cells and xylem.

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“…where 'g' and 'h' are allometric fit parameters. In analogy to the previous published approach for drought stress adaption (Ratjen et al 2016), an enhanced partitioning model was parameterized. The differential of Eqn 1 was extended by a correction term (cf) which allows the consideration of N shortage.…”

Section: Allometric Leaf-stem Partitioning and Its Adjustment To N Dementioning

confidence: 99%

“…Under growth-limiting conditions, leaf area development is reduced mainly via three different pathways: (i) total dry matter production through a reduced light use efficiency (Jackson et al 1981), (ii) an increase of the root: shoot ratio (Asseng et al 1998) and (iii) a reduction in leaf: stem ratio (Kumakov et al 2001). We previously found a shift in allometric partitioning towards stem fraction under drought and provided a drought-sensitive model for leaf: stem partitioning (Ratjen et al 2016). However, for wheat, the relevance of a change in leaf: stem allocation of dry matter under N-limited conditions was not analysed yet systematically.…”

Section: Introductionmentioning

confidence: 99%

Modelling N and Dry Matter Partitioning between Leaf and Stem of Wheat under Varying N Supply

Ratjen¹,

Kage²

2016

J Agronomy Crop Science

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The fraction of dry matter and nitrogen (N) allocated to leaves is of high importance for wheat crop simulators, because it has an impact on N demand, evapotranspiration, light interception and light use efficiency. For the vegetative phase of wheat, a robust empiric description of the influence of N nutrition status (NNI) on this pattern is still pending. We investigated the influence of NNI on leaf: stem partitioning of wheat (Triticum aestivum L.), until end of leaf growth. The evaluation based on N rate experiments (0–320 kg N ha−1) from three subsequent seasons (2003/4 to 2005/6), with five modern bread wheat cultivars, carried out near Kiel (northern Germany). A previously published model was adapted for describing the influence of NNI on dry matter partitioning. Starting from the allometric leaf: stem relationship of situations with NNI ≥1, a correction term was used, to describe the partitioning under varying N supply. The correction term assumes a linear increase of the stem fraction, proportional to the difference between a NNI threshold and actual NNI. The allometric partitioning was found to shift towards stem fraction, if the NNI falls below 1.38. The slope of the relative increase was determined with 0.6. Both dimensionless parameters of the correction term were found to be highly significant. The second aim was to quantify how N status impacts the N allocation between shoot organs. Dry matter‐based N dilution curves were fitted for stem (plateau power) and leaf (plateau linear), for situations with sufficient N supply (NNI ≥1). The ‘expected’ shoot N demand was calculated as a function of observed dry matter and N dilution for both organs. The N deficit was defined as difference between expected and observed shoot N. Plotting stem against shoot N deficit reveals that 63 % of the shoot deficit was allocated to the stem (R2 = 0.98). Implications for crop modelling are discussed.

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Comparative Drought Response in Eleven Diverse Alfalfa Accessions

Cited by 27 publications

References 59 publications

Alfalfa Water Use and Yield under Different Sprinkler Irrigation Regimes in North Arid Regions of China

Alfalfa Water Use and Yield under Different Sprinkler Irrigation Regimes in North Arid Regions of China

Physiological processes associated with salinity tolerance in an alfalfa half‐sib family

Modelling N and Dry Matter Partitioning between Leaf and Stem of Wheat under Varying N Supply

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