AJCS 7(11):1670-1681 (2013) ISSN:1835-2707 Genetic diversity of water use efficiency in Jerusalem artichoke (Helianthus tuberosus L.) germplasm Anon Janket1, Sanun Jogloy1*, Nimitr Vorasoot1, Thawan. Kesmala1, C. Corley Holbrook2 and Aran Patanothai1 1Department of Plant Science and Agricultural Resources, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand 2USDA-ARS, Crop Genetics and Breeding Research Unit, Coastal Plain Experimental Station, Tifton, GA 31793, USA *Corresponding author: [email protected] Abstract Genetic diversity in crop germplasm is an important resource for crop improvement, but information on genetic diversity is rare for Jerusalem artichoke, especially for traits related to water use efficiency. The objectives of this study were to investigate genetic variations for water use and water use efficiency in Jerusalem artichoke accessions and to identify superior genotypes for these characters under different water regimes. Forty Jerusalem artichoke accessions were arranged in a strip plot design with four replications for two years. Three strip plots represented three water regimes (W1 = 100%, W2 = 75% and W3 = 45% of crop water requirement). Data were recorded for tuber dry weight, biomass, relative water content, water use and water use efficiency. The effects of water regimes and Jerusalem artichoke accessions were significant for all characters. Genotypes contributed the largest portions for water use efficiency for biomass and tubers. These results documented genetic diversity for water use efficiency in Jerusalem artichoke. The genotypes with high water use efficiency for biomass were HEL 231, HEL 65 and JA102×JA89(8). HEL 65 had high water use efficiency for tubers. These genotypes should be useful in future breeding programs for higher water use efficiency. Keywords: Diversity, Drought resistance, Sun-choke, Transpiration efficiency, Water stress. Abbreviations: WU- Water use; WUEb- Water use efficiency for biomass; WUEt- Water use efficiency for tuber. Introduction Jerusalem artichoke (Helianthus tuberosus L.) is an and 22.8% (Losavio et al., 1997). Among inulin containing underutilized crop that originated in the temperate regions of and sugar containing crops, Jerusalem artichoke is more North America. It has been known as “potato for the poor” susceptible to water stress than sugar beet and root chicory and was consumed as vegetable by native Americans and the (Schittenhelm, 1999). The previous studies indicated that the early settlers (Cosgrove et al., 1991). Jerusalem artichoke crop requires adequate soil moisture for optimum yield. The stores inulin in stems and tubers, which can be used as raw questions arising from the previous studies are “1) what is the material for supplementing various value-added and health optimal amount of water to be applied to Jerusalem artichoke food products (Kay and Nottingham, 2008; Roberfroid, with supplemental irrigation or full irrigation under rainfed 2000). More recently, interest in Jerusalem artichoke research conditions, and 2) is there variation in water use efficiency has increased substantially as indicated by the number of among Jerusalem artichoke accessions under different water research articles in the freely-accessed sources. This is gradients?” These questions are important for water because it can be grown in a wide range of environments management of the crop and further improvement of water (Pimsean et al., 2010), while other inulin producing crops use efficiency by the crop. Jerusalem artichoke varieties with such as root chicory (Chicorium intybus var. sativum) and high water use efficiency should be more productive under globe artichoke (Cynara cardunculus var. scolymus) have a water limited conditions. The trait can be used as a selection rather limited production range in the temperate regions or criterion for drought resistance (Teare et al., 1982). The use high altitude areas (Burke, 2005; Robert et al., 2007). of water use efficiency, which is relatively simple to assess, Jerusalem artichoke has been grown in many parts of the as an indicator trait for the more complex and difficult to world and production conditions range from rainfed to fully access trait of drought resistance would be effective and irrigated and the crop can be grown in all seasons in a wide efficient. Variation in water use efficiency among genotypes range of climates, although the productivity varies greatly has been reported in other crops such as peanut (Arachis across regions (Baldini et al., 2006; Rodrigues et al., 2007). hypogaea L.) (Jongrungklang et al., 2008; Puangbut et al., Drought is a recurring problem for crops including Jerusalem 2009), Isabgol (Plantago ovata) and French phyllium artichoke grown in most growing conditions. When only 50% (Plantago psyllium) (Rahimi et al., 2011) and Cotton of the water requirement was available, tuber yield of (Gossypium herbaceum L.) (Tennakoon and Milroy, 2002). Jerusalem artichoke was reduced by 20% (Conde et al., 1991) Previous investigations on water use and water use efficiency 1670 Table 1. Mean squares for water use (WU), water use efficiency for biomass (WUEb) and water use efficiency of tubers (WUEt) of 40 Jerusalem artichoke genotypes grown under three water regimes (W1,W2 and W3) in the dry seasons 2010/11 and 2011/12. Mean square Source of variation DF WU WUEb WUEt Year (Y) 1 33ns (0.0) 2.36056** (20.0) 0.63644** (10.4) Reps within Year 6 19648 (5.8) 0.02775 (1.4) 0.02216 (2.2) Water regimes (W) 2 894720** (88.4) 0.06598** (1.1) 0.04403** (1.4) Y×W 2 2683ns (0.3) 0.00148ns (0.0) 0.00468ns (0.2) Error (a) 12 2914 (1.7) 0.00419 (0.4) 0.00157 ( 0.3) Genotypes (G) 39 792** (1.5) 0.14837** (49.0) 0.06839** (43.7) Y ×G 39 152** (1.5) 0.03142** (10.4) 0.02557** (16.4) Error (b) 234 73 (0.8) 0.00191 (3.8) 0.00145 (5.6) W×G 78 59** (0.2) 0.00633** (4.2) 0.00533** (6.8) Y×W ×G 78 39ns (0.2) 0.00616** (4.1) 0.00449** (5.7) Error (c) 468 32 (0.7) 0.00140 (5.6) 0.00095 (7.3) CV (%) (a) 36.36 21.51 17.63 CV (%) (b) 5.77 14.52 16.95 CV (%) (c) 3.83 12.44 13.71 ns, *, ** = non-significant and significant at P < 0.05 and P < 0.01 probability levels, respectively. Values in parenthesis are percentages of sum squares. W1= 100%ET, W2= 75%ET and W3=45%ET. (a) (c) 40 Tmax Tmin 40 Tmax Tmin o( erutarepm)C 2300 o( erutarepm)C 2300 et riA10 et riA 10 0 0 1 15 29 43 57 71 85 1 15 29 43 57 71 85 Days after transplanting Days after transplanting (b) (d) Rain (mm) Rain (mm) )%( ytidimuh evitaleR 11022468000000 RPaenla etivvaep houramtiiodnit y(m (%m)) 123456789000000000 )mm( noitaropavenap dna niaR )%( ytidimuh evitaleR 11022468000000 RPaenla etivvaep houramtiiodnit y(m (%m)) 123456789000000000 )mm( noitaropavenap dna niaR 0 0 0 0 1 15 29 43 57 71 85 1 15 29 43 57 71 85 Days after transplanting Days after transplanting Fig 1. Maximum air temperatures (T-max), minimum air temperatures (T-min) (OC), rainfall (mm), pan evaporation (mm) and relative humidity(RH) (%) during the crop growth period of Jerusalem artichoke in the dry season 2010/11 (a),(b) and the dry season 2011/12 (c),(d) conducted so far have been limited to 6 Jerusalem artichoke Results genotypes (Yang et al., 2010). Studies on a wide range of diverse genotypes are required to fully exploit genetic Meteorological conditions, soil moisture status and variations in these characters. The objectives of this study variation of plant water status were to compare water use efficiency among Jerusalem artichoke genotypes under different water gradient conditions Average daily maximum (T-max) and minimum temperature and to identify Jerusalem artichoke genotypes with high (T-min) were slightly different between years. Means of T- water use efficiency. The information obtained in this study max in the first year and the second year were 30.3 oC and will be useful for irrigation management of Jerusalem 30.5 oC, respectively. Means of T-min in the first year and the artichoke and breeding of Jerusalem artichoke for high water second year were 18.4 oC and 19.5 oC, respectively. Daily pan use efficiency. evaporations ranged from 2.0 to 7.7 mm in the first year and 2.2 to 9.8 mm in the second year. 1671 Table 2. Ten selected genotypes with the highest water use (WU), water use efficiency for biomass (WUEb) and water use efficiency for tubers (WUEt) and 10 selected genotypes with the lowest performance for these traits and drought tolerance index (DTI) selected from 40 Jerusalem artichoke genotypes in the dry seasons 2010/11. Water use (WU) Water use efficiency for biomass (WUEb) DTIa Water use efficiency for tubers (WUEt) DTI DTI Group No. (mm) (kg mm-1 ha-1) (kg mm-1 ha-1) Genotypes W1 W2 W3 W2 W3 Genotypes W1 W2 W3 W2 W3 Genotypes W1 W2 W3 W2 W3 High 1 HEL 62 217.5 a 161.8 a 93.3 b 0.74 0.43 HEL 53 32.7 a 36.6 a 31.4 a 1.12 0.96 HEL 53 24.8 a 27.2 a 32.0 a 1.10 1.29 2 HEL 246 211.2 ab 157.7 ab 114.7a 0.75 0.54 HEL 253 32.0 a 28.5 b 31.9 a 0.89 1.00 HEL 335 24.3 a 18.9 ab 13.2 g-k 0.78 0.54 3 KKUAc001 210.3 abc 158.3 ab 93.1 b 0.75 0.44 HEL 335 30.7 ab 20.4 e-h 19.2 e-i 0.66 0.62 HEL 65 22.5 ab 15.9 c-f 22.8 c 0.70 1.01 4 HEL 256 209.6 a-d 158.7 ab 93.3 b 0.76 0.44 HEL 256 30.7 ab 24.0 cde 26.9 a-d 0.78 0.88 HEL 256 22.1 abc 12.9 e-i 14.5 e-j 0.58 0.66 5 JA 125 209.3 a-d 155.8 a-e 92.4 b 0.74 0.44 HEL 61 28.7 bc 22.1 bc 22.8 c-f 0.77 0.79 HEL 61 22.1 abc 15.7 c-f 17.9 def 0.71 0.81 6 HEL 257 209.0 a-d 155.4 a-f 92.6 b 0.74 0.44 HEL 65 28.3 bc 21.1 efg 28.5 ab 0.75 1.01 HEL 253 22.0 abc 16.1 cde 20.1 cd 0.73 0.91 7 JA 77 208.9 a-d 158.0 ab 92.3 b 0.76 0.44 JA102XJA89(8) 28.0 bc 21.5 ef 28.4 ab 0.77 1.01 JA 89 21.4 a-d 20.9 b 26.7 b 0.98 1.25 8 JA 67 208.9 a-d 157.1 abc 92.3 b 0.75 0.44 JA 89 25.7 cd 27.5 bc 27.7 ab 1.07 1.08 JA102XJA89(8) 20.4 a-e 16.1 cde 17.9 def 0.79 0.88 9 HEL 53 208.7 a-d 157.8 ab 93.1 b 0.76 0.45 HEL 231 25.7 cd 26.1 bcd 24.3 b-e 1.02 0.95 HEL 231 19.7 a-f 16.0 c-f 19.5 cd 0.81 0.99 10 HEL 335 208.1 a-d 158.1 ab 93.4 b 0.76 0.45 KKUAc001 24.0 d 22.7 de 27.2 abc 0.95 1.33 KKUAc001 17.3 a-g 20.5 b 19.7 cd 1.19 1.14 Low 1 HEL 253 194.7 b-f 157.9 ab 93.4 b 0.81 0.48 JA 125 10.2 m-p 13.7 j-o 13.3 jp 1.35 1.31 JA 36 8.4 g-j 5.1 pq 7.1 n 0.60 0.85 2 JA 21 194.5 b-f 146.6 i-m 86.8 b 0.75 0.45 JA 36 9.9 n-q 9.2 p-s 8.5 p 0.93 0.86 HEL 62 8.3 a-j 8.4 k-p 8.4 lmn 1.01 1.01 3 HEL 65 194.5 b-f 156.5 a-d 91.1 b 0.80 0.47 JA 60 9.4 n-r 10.7 n-r 10.1 nop 1.14 1.07 JA 125 8.3 g-j 10.1 g-n 11.3 j-n 1.22 1.36 4 HEL 324 193.7 b-f 145.6 j-m 86.5 b 0.75 0.45 JA 109 9.3 n-r 13.7 j-o 20.3 e-h 1.47 2.17 JA 60 7.8 g-j 9.1 i-o 10.7 j-n 1.17 1.37 5 JA 3 193.3 b-f 144.7 klm 86.4 b 0.75 0.45 JA 46 8.8 n-r 10.9 m-r 12.2 k-p 1.23 1.39 JA 109 6.8 g-j 9.6 h-o 17.2 d-h 1.41 2.53 6 JA 76 192.5 c-f 156.6 a-d 93.1 b 0.81 0.48 JA 97 8.6 o-r 8.7 qrs 15.5 h-n 1.01 1.80 JA 61 6.5 a-j 6.1 opq9 .5 k-n 0.93 1.45 7 JA 36 191.7 c-f 143.4 lm 85.5 b 0.75 0.45 JA 77 7.5 pqr 8.5 qrs 8.5 p 1.13 1.12 JA 77 6.3 hij 7.1 l-q 7.1 ln 1.12 1.12 8 JA 6 191.5 def 146.6 i-m 86.6 b 0.77 0.45 JA 1 6.9 qr 5.6 s 9.1 p 0.82 1.33 JA 97 6.0 ij 6.8 m-q1 1.5 j-n 1.13 1.92 9 JA 16 188.9 ef 141.8 m 84.7 b 0.75 0.45 JA 70 6.8 qr 7.9 rs 10.3 m-p 1.16 1.52 JA 1 5.8 ij 4.7 q 7.9 mn 0.82 1.36 10 JA 15 181.8 f 148.6 e-m 85.2 b 0.82 0.47 JA 61 6.3 r 7.1 rs 9.4 op 1.12 1.48 JA 70 5.5 j 6.6 n-q 8.4 lmn 1.19 1.52 Mean 201.8 A 152.5 B 90.5 C 0.76 0.45 16.9 AB 15.7 B 17.7 A 0.97 1.21 13.45 A 12.15B 14.27 A 0.94 1.14 Min 181.8 141.8 84.7 0.73 0.43 6.3 5.6 8.5 0.66 0.62 5.5 4.7 7.1 0.58 0.54 Max 217.5 161.8 114.7 0.82 0.54 32.7 36.6 31.9 1.47 2.17 24.8 27.2 32.0 1.41 2.52 Maximum, minimum and mean values were calculated from 40 genotypes, For comparison among Jerusalem artichoke genotypes and for comparison among water regimes, Means in the same column followed by the same letter(s) are not significantly different at P < 0.05 probability levels by Duncan's multiple range test (DMRT). aDTI = Drought tolerance index was calculated by the ratio of stressed conditions / non stressed conditions. W1= 100%ET, W2= 75%ET and W3=45%ET 1672 (d) 0.250 W1 W2 W3 noitcarf e 00..220500 W1 W2 W3 (a) noitcarf emu 0.200 (d) m lo 0.150 ulo 0.150 v e v eruts 0.100 rutsiom 0.100 iom lio lioS 0.050 S 0.050 7 14 21 28 35 42 49 56 63 70 77 84 7 14 21 28 35 42 49 56 63 70 77 Days after transplanting Days after transplanting 0.250 W1 W2 W3 0.250 W1 W2 W3 n n oitcarf em0.200 (b) oitcarf em 0.200 (e) u u lo0.150 lo 0.150 v v eru eru tsio0.100 tsio 0.100 m m lio lio S S 0.050 0.050 7 14 21 28 35 42 49 56 63 70 77 7 14 21 28 35 42 49 56 63 70 77 84 Days after transplanting Days after transplanting (f) 0.250 W1 W2 W3 0.250 W1 W2 W3 n no oitcarf e0.200 (c) itcarf em0.200 m u ulov erutsiom lio00..110500 lov erutsiom lioS00..110500 S 0.050 0.050 7 14 21 28 35 42 49 56 63 70 77 7 14 21 28 35 42 49 56 63 70 77 84 Days after transpanting Days after transplanting Fig 2. Soil moisture volume fractions for three soil water regimes (W1= 100%ET, W2= 75%ET and W3= 45%ET) of three soil depths at 30 cm (a), 60 cm (b) and 90 cm (c) in the dry seasons 2010/11 and the dry season 2011/12 (d-f). Daily maximum relative humidity ranged from 69 to 98 % in b,e). There was no difference in soil moisture at 90 cm depth the first year and 71 to 99% in the second year (Fig. 1a,c). (Fig. 2 c,f). Relative water contents (RWC) at 40, 60 and 70 There was no rainfall during the experimental period in DAT for W1 were higher than those for W2, and relative 2010/11 but rainfall of 174.6 mm was recorded in 2011/12 at water contents for W2 were higher than those for W3 in both 1–6 days after transplanting (DAT) (Fig. 1b,d). The rainfall years, indicating that the control of water supply for all water did not cause significant difference among water treatments regimes was reasonably good (Fig 3). because it occurred during pre-treatment period, when all treatments received the same amount of water. Soil moisture Combined analysis of variance contents of different water regimes (W1–W3) were clearly different at the soil depth of 30 cm, starting from 21 DAT Combined analysis of variance showed significant when water was supplied to the crop by line- source sprinkler differences between water regimes (W) and Jerusalem irrigation system for a week (Fig. 2 a,d). Soil moisture content artichoke genotypes (G) for WU, WUEb and WUEt (Table for W1 was slightly lower than field capacity but higher than 1). The difference in years (Y) was significant for most W2 because deep water loss was ignored and the soil is well- characters (P<0.01) except for WU, and the differences drained. The differences in soil moisture content among water among genotypes for WU were significant but accounted for regimes were significant, but differences in soil moisture only 1.5% of total variation. Year × water interactions were content were reduced with the depth of the soil profile (Fig 2 not significant for all characters, whereas the interactions 1673 between water and genotypes were significant for all However, JA 125 and JA 61 had low WUEb but their WUEt characters. Y × G interactions for WUEb (10.4% of SS) and was relatively high under W1. In contrast, JA 67 and JA 77 WUEt (16.4% of SS) were much larger than that for WU had low WUEt but WUEb was relatively high. JA 70, JA (1.5% of SS), the variations among genotypes for these traits 109, HEL 62 and JA 36 showed consistently low WUEt were also higher (49.0% of SS for WUEb and 43.7% of SS across water regimes. JA 89, KKUAc001, JA102×JA89(8), for WUEt). Year × water × genotype interactions were HEL 231 and HEL 65 had high WUEb across years under significant for WUEb and WUEt (P≤0.01) but not for WU. W1, whereas JA 89, JA102 × JA89(8) and HEL 65 had high Water regimes accounted for small percentages of variations WUEt. Three genotypes (HEL 231, HEL 65 and in WUEb and WUEt (1.1–1.4%). The contribution of JA102×JA89(8)) had consistently high WUEb across water genotype × water regime interaction was higher than that of regimes and years, and HEL 65 had high WUEt across water water regimes but it was still lower than the contribution of regimes and years. There were 6 genotypes (JA61, JA 70, JA genotypic differences to WUEb and WUEt. 1, JA 109, JA 60 and JA 36) showing consistently low WUEb across years under W1 and 7 genotypes (JA 70, JA 1, JA 109, Water use and water use efficiency HEL 62, JA 36, JA 60 and JA 77) showing consistently low WUEt under W1. However, there were only four genotypes As the interactions between genotype and year were (JA 70, JA 1, JA 60 and JA 36) with consistently low WUEb significant for WU, data were analyzed by year (Tables 2 and across water regimes and years and three genotypes (JA 70, 3). WU in both years depended largely on water regimes, in HEL 62 and JA 36) with consistently low WUEt across water which the highest WU was observed for W1 and the lowest regimes and years. Correlation coefficients between the data WU was recorded for W3. Genotypic variations for WU were of two years (2010/11 and 2011/12) for water use efficiency low for all water regimes in both years, and the variations for biomass WUEb and water use efficiency for tuber yield were lowest for W3. Drought tolerance indices for WU were (WUEt) were calculated for three water regimes (Fig. 4). higher for W2 in both years, indicating that under water stress Correlation coefficients for (WUEb) were positive and less water used by plants. The identification of superior significant for all water regimes, being 0.71**, 0.57** and genotypes for WU was difficult because of low variation for 0.48** for W1, W2 and W3, respectively (Fig. 4 a,b,c). this trait and high Y × G interaction. As the interactions for Correlation coefficients for WUEt were lower but positive WUEb and WUEt between genotype and year, genotype and and significant, being 0.59**, 0.29* and 0.31* for W1, W2 water regime and secondary level of interaction were high but and W3, respectively (Fig. 4 d,e,f). Correlation coefficients much lower than that for genotype main effect, the data for between years for WUEb and WUEt were lower in the two years were analyzed separately (Tables 2 and 3). The drought treatments of W2 and W3 (Fig. 4 b,c and e,f), and variations in these traits were due largely to variations in correlation coefficients for WUEb were higher than for genotypes. Water regime contributed less to total variations WUEt for all water regimes. Drought at moderate level (W2) compared to genotype main effect, but the differences in caused 7.1 and 9.6% reductions in WUEb and WUEt, water regimes did not show consistent patterns between respectively, but drought at severe level (W3) caused slight years. Drought tolerance indices across years for WUEb and increases in WUEb (4.2%) and WUEt (5.4%). The reductions WUEt for W3 in general were consistently higher than those in 2010/11 were higher than in 2011/12 (data not shown). In for W2. The data indicated that W3 could somewhat increase 2010/11, the DTI ranged in all drought conditions from 0.54 water use efficiency. The genotypes with high or low WUEb to 2.52 (Table 2). The genotypes showing high DTI for and WUEt could then be identified. HEL 53, JA 89, KKUAc001, JA102×JA89(8), HEL 253, HEL 231, HEL 65 WUEb and WUEt were JA 109, JA 97, HEL 324, JA 70 and JA 61 in W3 ranged from 1.44 to 2.52. In the experiment in and HEL 61 had consistently high WUEb and WUEt across water regimes in 2010/11. HEL 335 had consistently high 2011/12, the DTI ranged in all drought conditions from 0.54 WUEb and WUEt under W1 and W2, whereas HEL 256 had to 1.73 (Table 3). The genotypes with high DTI for WUEb high WUEb across water regimes but WUEt exhibited high were JA 3, JA 15, HEL 253, JA 38 and JA 61 in W3 ranged water use efficiency under W1 only. JA 61, JA 70, JA 1, JA from 1.33 to 1.57 and DTI for WUEt the genotypes with high 77, JA 97, JA 46, JA 109, JA 60, JA 36 and JA 125 had low DTI were JA 3, JA 67, JA 38, JA 132 and JA 92 ranged from WUEb under W1 in 2010/11, whereas JA 61, JA 70, JA 1, JA 1.30 – 1.73. 77, JA 60 and JA 36 had consistently low WUEb across water regimes. The genotypes with low WUEb also had low Cluster analysis WUEt except for HEL 62 showing low WUEt only and JA 46 showing low WUEb only. JA 70, JA 1, JA 77, JA 61 and JA Based on combined data for WUEb and WUEt of two 36 showed consistently low WUEb and WUEt across water drought levels for two years, a dendrogram could divide 40 regimes. In the experiment in 2011/12, HEL 256, JA 89, JA Jerusalem artichoke genotypes into five clusters (R-square = 6, HEL 231, HEL 65, CN 52867, KKUAc001, HEL 324, 0.85) (Fig. 5). Nine Jerusalem artichoke genotypes formed JA102×JA89(8) and JA 16 had high WUEb under W1, and, cluster 1, which was characterized by low water use among these genotypes, JA 6, HEL 231, HEL 65 and efficiency under drought conditions. Cluster 2 comprised 7 JA102×JA89(8) had high water use efficiency across water genotypes, which was characterized by relatively low water regimes. HEL 256, JA 89, JA 6, HEL 65, HEL 257, CN use efficiency under drought conditions. Cluster 3 included 52867 , JA 122, JA 16, HEL 324 and JA102×JA89(8) had 12 genotypes, which was characterized by intermediate to high WUEt under W1. Among these accessions, there were 3 relatively high water use efficiency under drought conditions, genotypes (JA 6, HEL 65 and CN 52867) with high water use but a few genotypes had relatively low water use efficiency. efficiency across water regimes. The genotypes with low Cluster 4 had 5 genotypes, which are characterized by WUEb under W1 were JA 1, JA 70, JA 36, JA 109, HEL 62, relatively high water use efficiency under drought conditions. JA 60, JA 46, JA 61, JA 125, JA 92, and the genotypes Cluster 5 had 7 genotypes, which was characterized by high showing consistently WUEb across water regimes were JA 1, water use efficiency under drought conditions. JA 92, JA 70, JA 36, JA 109, JA 60, JA 46 and HEL62. Most genotypes showing low WUEb also had low WUEt. 1674 Table 3. Ten selected genotypes with the highest water use (WU), water use efficiency for biomass (WUEb) and water use efficiency for tubers (WUEt) and 10 selected genotypes with the lowest performance for these traits and drought tolerance index (DTI) selected from 40 Jerusalem artichoke genotypes in the dry seasons 2011/12. Water use (WU) Water use efficiency for biomass (WUEb) DTIa Water use efficiency for tubers (WUEt) DTI DTI Group No. (mm) (kg mm-1 ha-1) (kg mm-1 ha-1) Genotypes W1 W2 W3 W2 W3 Genotypes W1 W2 W3 W2 W3 Genotypes W1 W2 W3 W2 W3 High 1 HEL 62 215.9 a 163.5 abc 103.3 abc 0.76 0.48 HEL 256 35.6 a 20.7 j-p 28.1 a-h 0.58 0.79 HEL 256 27.6 a 14.8 g-m 17.5 f-m 0.54 0.64 2 HEL 65 214.8 ab 164.4 ab 104.5 ab 0.77 0.49 JA 89 32.5 ab 23.9 d-k 26.7 c-j 0.74 0.82 JA 89 23.5 b 16.3 d-j 18.9 d-h 0.69 0.80 3 HEL 256 212.6 abc 166.4 a 105.6 a 0.78 0.50 JA 6 31.7 bc 31.9 a 31.2 a-d 1.01 0.99 JA 6 23.1 bc 21.1 ab 23.8 abc 0.91 1.03 4 HEL 253 210.0 a-d 162.9 abc 103.2 abc 0.78 0.49 HEL 231 31.2 bcd 26.7 b-f 31.7 abc 0.86 1.01 HEL 65 22.5 bcd 20.3 ab 21.9 a-e 0.90 0.98 5 HEL 335 208.6 a-e 163.4 abc 100.8 a-e 0.78 0.48 HEL 65 30.3 b-e 30.3 abc 29.7 a-e 1.00 0.98 HEL 257 21.3 b-e 18.7 b-f 20.7 b-f 0.88 0.97 6 JA 132 207.3 a-f 158.5 b-e 101.1 a-e 0.76 0.49 CN 52867 29.9 b-e 27.3 b-e 27.3 a-i 0.91 0.91 CN 52867 21.0 b-f 20.3 ab 25.1 a-d 0.97 1.20 7 JA102XJA89(8) 207.3 a-f 153.7 d-i 99.6 b-g 0.74 0.48 KKUAc001 28.9 b-f 28.0 a-d 26.9 c-i 0.97 0.93 JA 122 20.2 c-g 19.6 abc 17.9 f-k 0.97 0.89 8 JA 76 206.5 a-g 158.4 b-e 99.9 b-f 0.77 0.48 HEL 324 28.0 c-g 24.1 d-j 29.5 a-e 0.86 1.05 JA 16 19.7 g-h 16.6 c-i 14.4 j-o 0.84 0.73 9 JA 37 206.0 a-g 158.3 b-e 100.3 b-e 0.77 0.49 JA102XJA89(8) 27.9 d-g 30.1 abc 28.7 a-f 1.08 1.03 HEL 324 19.5 d-i 15.5 f-k 17.7 f-l 0.79 0.91 10 JA 67 205.8 a-g 160.1 a-d 101.9 a-d 0.78 0.50 JA 16 27.7 d-g 23.9 d-k 20.1 l-m 0.86 0.73 JA102XJA89(8) 19.5 d-i 19.9 abc 18.2 e-j 1.02 0.93 Low 1 JA 114 187.2 l-q 144.6 k-n 93.0 j-o 0.77 0.50 JA 92 18.0 o-u 21.3 h-o 22.7 h-o 1.19 1.26 JA 77 13.3 n-t 15.0 g-l 16.7 f-n 1.13 1.26 2 CN 52867 187.0 l-q 147.6 h-m 95.0 f-n 0.79 0.51 JA 125 17.5 p-u 16.7 p-s 17.5 o-r 0.96 1.00 JA 46 13.0 o-t 13.1 j-o 14.7 i-o 1.01 1.13 3 JA 3 186.2 m-q 141.4 lmn 91.8 l-o 0.76 0.49 JA 61 17.4 p-u 19.2 l-q 23.1 h-n 1.10 1.33 JA 92 12.9 o-t 15.6 f-k 16.9 f-n 1.21 1.30 4 JA 38 186.0 m-q 145.1 j-n 93.8 h-o 0.78 0.50 JA 46 16.9 p-u 17.8 n-s 18.7 n-r 1.06 1.11 JA 67 12.8 o-t 12.9 k-o 18.5 e-i 1.01 1.44 5 JA 5 185.2 n-q 143.8 k-n 92.7 k-o 0.78 0.50 JA 60 16.5 r-u 14.9 rs 18.9 m-r 0.91 1.15 JA 60 12.5 p-t 11.7 mno 15.0 h-o 0.94 1.20 6 HEL 324 184.7 n-q 138.7 n 90.6 no 0.75 0.49 HEL 62 16.3 r-u 15.7 qrs 20.3 l-p 0.96 1.24 JA 36 11.6 q-t 11.9 l-o 9.6 q 1.03 0.83 7 JA 36 181.2 opq 142.1 lmn 91.7 mno 0.78 0.51 JA 109 16.1 stu 16.0 qrs 14.9 qr 0.99 0.92 HEL 62 11.5 rst 11.0 no 13.4 nop 0.96 1.17 8 JA 122 180.9 opq 141.2 mn 91.9 l-o 0.78 0.51 JA 36 15.9 tu 15.8 qrs 16.1 pqr 1.00 1.01 JA 109 11.3 rst 10.8 o 9.7 q 0.95 0.86 9 JA 16 179.4 pq 140.1 mn 90.7 no 0.78 0.51 JA 70 14.5 u 14.0 s 13.9 r 0.96 0.95 JA 1 10.9 st 14.1 h-n 8.7 q 1.29 0.80 10 JA 6 176.6 q 139.0 n 89.9 o 0.79 0.51 JA 1 14.5 u 17.2 o-s 14.3 r 1.19 0.99 JA 70 10.2 t 10.3 o 10.1 pq 1.01 0.99 Mean 196.9 A 152.0 B 97.1 C 0.77 0.49 23.2 AB 22.5 B 24.4 A 0.98 1.07 16.6 AB 16.2 B 17.3 A 0.99 1.06 Min 176.6 138.7 89.9 0.74 0.48 14.5 14.0 13.9 0.58 0.73 10.2 10.3 8.7 0.53 0.63 Max 215.9 166.4 105.6 0.79 0.51 35.6 31.9 32.5 1.19 1.57 27.6 22.4 25.1 1.29 1.73 Maximum, minimum and mean values were calculated from 40 genotypes, For comparison among Jerusalem artichoke genotypes and forcomparison among water regimes, Means in the same column followed by the same letter(s) are not significantly different at P < 0.05 probability levels by Duncan's multiple range test (DMRT). aDTI = Drought tolerance index was calculated by the ratio of stressed conditions / non stressed conditions. W1= 100%ET, W2= 75%ET and W3=45%ET. Table 4. Chemical and physical properties of the soil in the experimental fields at the depth 0-30 cm Particle size, mum Exchangeable EC (1:5 H20) CEC OM Total N Available P (USDA system) Fields pH (1:1 HO) Texture class 2 (dS/m) (cmol/kg) (%) (%) (mg/kg) Sand (%) Silt (%) Clay (%) K (cmol/kg) Ca cmol/kg) 2.0 – 0.05 0.05– 0.002 <0.002 2010/11 6.08 0.03 5.22 0.44 0.02 23.95 0.084 1.043 85.08 7.30 7.62 Loamy sand 2011/12 6.12 0.02 5.93 0.42 0.01 37.97 0.097 1.120 90.29 8.05 1.66 Sand EC = Electrical conductivity, CEC= Cation exchange capacity and OM = Organic matter. 1675 (a) (b) W1 100 W1 100 W2 )%( tn 90 WW23 )%( tne 90 a a W3 etnoc retaw evitale 678000 a b c a b c a b c tnoc retaw evtaleR 678000 b c b c a b c R 50 50 40 DAT 60DAT 70DAT 40 DAT 60 DAT 70 DAT Days after transplanting Days after transplanting Fig 3. Relative water content (%) at 40, 60 and 70 days after transplanting (DAT) of 40 Jerusalem artichoke genotypes grown under different water regimes in the dry season 2010/2011 (a) and the dry season 2011/2012 years (b) Means in the same date with the same letter are not significant at P < 0.05 probability level by DMRT. Fig 4. Relationships between years for water use efficiency for biomass (a-c) and water use efficiency for tubers (d-f) of 40 Jerusalem artichoke genotypes under three water regimes in 2010/11 and 2011/12. 1676 Discussion planting dates (Puangbut et al., 2011). However, water use efficiency for inulin yield has not been investigated, and this The soil chemical and physical properties were slightly trait is also important for Jerusalem artichoke breeding for different among experimental years (Table 4). The soil in the drought resistance. Water regime contributed to small second experiment (2011/12) was higher in pH, available portions of total variations in WUEb (1.1%) and WUEt phosphorus (P), exchangeable potassium and exchangeable (1.4%). The results suggested that any water regime can be calcium (Ca) than in the first experiment (2010/11). The used for evaluation of water use efficiency with similar results. Therefore, mimicking of drought conditions may not chemical properties indicated that soil fertility was lower than be necessary. In general, the cultivars with high yield optimum conditions for production of Jerusalem artichoke. potential under optimum conditions had acceptable yield EC values in both years were lower than 0.03 dS/m, under stressed environments, but, under a particular indicating that the soil was not saline (Geng-mao et al., environmental stress, cultivars with high potential had lower 2008), and P values were higher than 15 mg/kg which should yield than certain cultivars with lower yield potential (Blum, be sufficient for normal growth of Jerusalem artichoke 2005). Therefore, high yield potential and low yield reduction (Lebot, 2009). Potassium values were intermediate and under water stressed conditions are important for sustaining nitrogen values were low. As the nutrient values fell into the yield under drought. In some cases, drought stress reduced same ranges and basal dose was also applied, the difference water use efficiency such as in peanut (Jongrungklang et al., in nutrients among years would not cause significant 2008) and dry bean (Phaseolus vulgaris L.) (Muñoz-perea et differences in water use efficiency. Differences were al., 2007). In Jerusalem artichoke, water application of 50% found among the experiments in the ranking of the of ET caused yield reductions of lower than 50% (Losavio et genotypes, showing the significance of genotypes by al., 1997), and, therefore, drought caused higher water use environmental interactions. The differences between years efficiency. Drought also increased water use efficiency in were likely due to higher rain fall and air temperature in peanut (Aranyanak et al., 2008), cassava (Olanrewaju et al., 2011/12 that enhanced performance of genotypes. In the first 2009), common bean and green gram (Webber et al., 2006). year, maximum and minimum air temperatures ranged from Differences in the results from different studies are due to 18.4–30.3 oC, which was lower than the second year which difference in crop species, times of drought imposition to the ranged from 19.5–30.5 oC. Because Jerusalem artichoke in crops and drought intensity. As mentioned earlier, this study was grown in the tropics, the growing temperatures genotypic variations accounted for 49.0% for WUEb and were much higher than optimum temperatures for this 43.7% for WUEt. Genotypes with high water use efficiency species. Most Jerusalem artichoke cultivars require an could be readily identified. HEL 231, HEL 65 and average annual temperature between 18–26 oC under JA102×JA89(8) had high WUEb across water regimes and temperate conditions (Cosgrove et al., 1991). However, years, whereas HEL 65 had high WUEt. As water use Jerusalem artichoke grown under temperate conditions and efficiency is closely related to yield, these Jerusalem tropical conditions requires a similar number of heat units. In artichoke genotypes also showed high yield under and well- tropical regions, heat units between 2245 and 4242 were irrigated and drought conditions (Data not reported). reported (Ruttanaprasert et al., 2013), while heat units Relationships between data for WUEb and WUEt of two between 2106 and 4123 were reported in temperate regions years were consistent as indicated by significant correlation (Kocsis et al., 2007). The difference is that the crop in coefficients. The results indicated that selection for high temperate regions takes nine months to accumulate these heat water use efficiency in these Jerusalem artichoke collections units but it takes only three months in the tropics. The rainfall of genotypes is possible. In previous investigation, Yang et did not cause significant differences among water treatments al. (2010) found that JA 6 had high water use efficiency for because all treatments received uniform water during the crop biomass. It is interesting to note here that JA 6 was establishment period, but rainfall during the early growing commonly used in these studies. However, JA 6 has high season in 2011/12 promoted better establishment of the crop water use efficiency for biomass and tuber yield across water and subsequent crop performance than in 2010/11. regimes in 2011/12 only. JA 70, JA 1, JA 60 and JA 36 had Differences in WU were largely due to the differences in low WUEb, whereas JA 70 and JA 36 had low WUEt. amount of water applied to the crop, which accounted for Genotypic variations in water use efficiency are mainly due 88.4% of total variation for water use. Genotype and to genetic variation in WU. Reduction in WU should increase genotype by year interaction gave small contribution to total water use efficiency and ultimately improve yield under variation for WU (1.5% for both). Improvement of WU in drought conditions (Blum, 2005; Hamlyn, 2004). So, water this population was not expected to yield significant results as use efficiency values depend on the WU and day to harvest in the genetic variation for this trait was rather low. Genotypes each genotype (Lasovio et al., 1997; Matthews et al., 1988). contributed significant proportions of the total variations in Cluster analysis based on WUEb and WUEt under drought WUEb (49.0%) and WUEt (43.7%). The contributions were conditions could reasonably well separate groups of generally 1- to- 4 fold larger than those for variation by years, Jerusalem artichoke genotypes with high or low WUEb and water regimes and other interactions. Water use efficiency is WUEt. However, the classification of Jerusalem artichoke important for crop improvement for drought resistance. In genotypes based on the dendrogram was slightly different peanut, genotype contributed a large portion to the variations from that based on the data of three water regimes. The in water use efficiency (Jongrungklang et al., 2008; Mattews difference could be due to the differential response of et al., 1988). Similar results were also reported in cassava Jerusalem artichoke genotypes to drought conditions. The (Manickasundaram et al., 2002). Therefore, improvement of genotypes with high DTI were relatively low-yielding these traits in this Jerusalem artichoke population is genotypes in well- watered conditions. Genotypes with high promising. Other agronomic traits are also important for water use efficiency were not high DTI genotypes because improvement of Jerusalem artichoke for drought resistance. high DTI genotypes were not the best for yield in drought Variations in fresh tuber yield, biomass and inulin content conditions but rather had low yield reductions under drought have also been reported (Puttha et al., 2012), and the conditions. The genotypes identified through this study genotypic variation in inulin content was consistent across 1677 Table 5. Forty genotypes of Jerusalem artichoke used in the experiment, their characteristics and sources of origin Genotypes Characteristics Sources of origin JA 1 , JA 4, JA 6, JA 36, JA 70, JA 92, JA 114 Early and low biomass varieties PGRC1, Canada JA3, JA 16, JA 21, JA 37, JA 38, JA 97, JA 132 Early and high biomass varieties PGRC, Canada JA 5, JA 122 Early, tall plant and low biomass varieties PGRC, Canada HEL 324 Early, tall plant and low biomass varieties IPK2, Germany HEL 53, HEL 61, HEL 231, HEL 335 Early, tall plant and high biomass varieties IPK, Germany CN 52867 Early, tall plant and high biomass varieties PGRC, Canada KKUAc001 Early, tall plant and high biomass varieties Khajarern3 JA 61 Early, tall plant and high biomass varieties PGRC, Canada JA 46, JA 60, JA 109 Late, short plant and low biomass varieties PGRC, Canada JA 76, JA 77 Late, short plant and high biomass varieties PGRC, Canada HEL 62 Late, short plant and high biomass varieties IPK, Germany HEL 246, HEL 257 Late, tall plant and low biomass varieties IPK, Germany JA 15, JA 67, JA 125 Late, tall plant and high biomass varieties PGRC, Canada JA 89 Late, tall plant and high biomass varieties PGRC, Canada HEL 65, HEL 253, HEL 256 Late, tall plant and high biomass varieties IPK, Germany JA102×JA89(8) Late, tall plant and high biomass varieties Jerusalem artichoke Research Project4 1 The Plant Gene Resource of Canada (PGRC). 2 The Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) of Germany, 3 Department of Animal Science Faculty Agriculture, Khon Kaen University, Thailand. 4 Jerusalem artichoke Research Project, Thailand Fig 5. Dendrogram of 40 Jerusalem artichoke genotypes based on water use efficiency for biomass and water use efficiency for tubers under drought conditions for two years should be useful in future breeding programs for improving newly-released variety from the Jerusalem artichoke research drought tolerance. project of Thailand and one accession was the first introduced clone in Thailand of unknown origin. The details of Materials and methods Jerusalem artichoke accessions used in the experiment are available in Table 5. A line source sprinkler system was Plant materials and experimental design installed to provide three water gradients, which hereafter are referred to as W1, W2 and W3, respectively, and the water Field experiments were conducted at the Khon Kaen gradients were dependent on the distances for the line source, University’s agronomy farm, Khon Kaen, Thailand (16O 28´ which was installed at the center of the field. The water N, 102 O 48´ E, 200 msl) in the dry season for two years supplied to W1 was expected to be equivalent to the crop water during October to February in 2010/2011 and 2011/2012. The requirement (ET crop). Water supplied to W2 was estimated as soil type was Yasothon series (loamy sand, Oxic Paleustults). 75% of that supplied to W1, and water supplied to W2 was Three irrigation levels were assigned in strip plots, 40 45% of that supplied to W1. Jerusalem artichoke accessions were arranged randomly in subplots, and the treatments were replicated four times. Crop management Twenty-seven accessions were introduced from Plant Gene Resource of Canada (PGRC), 11 accessions were kindly Healthy tubers were used as planting materials. The tubers donated from the Leibniz Institute of Plant Genetics and Crop were cut into small pieces with 2 to 3 buds each, and the Plant Research (IPK) of Germany, one accession was a tuber pieces were immersed into water containing a fungicide 1678 (caboximide) at the rate of 10 g per 20 l of water for 40 min. Data collection The tuber pieces were then incubated in burnt rice husk mixed (1:1) with a commercial preparation of Trichoderma Meteorological conditions (T9) in plastic boxes for 5 to 7 days to stimulate germination. Trichoderma was incorporated into the soil to control stem Weather data for both seasons were obtained from nearby rot disease caused by Sclerotium rolfsii. After germination, meteorological station, Khon Kaen University, Khon Kaen, the seedlings were transferred into plug trays containing Thailand. Evaporation (E ), rainfall, maximum and minimum 0 mixed medium of soil, burnt rice husk and Trichoderma at temperature and relative humidity (RH) were recorded daily the ratio of 3:3:2 V/V. Water was supplied regularly to the form transplanting until harvest. nursery to avoid water stress until the seedlings had 2–3 leaves, or about 7–10 days after transferring. The seedlings Soil data and soil moisture content were then suitable for transplanting into the field. Conventional tillage was practiced for soil preparation. A line The field experiment in both years was conducted in the same source sprinkler system consisting of two modules was field. Soil samples were collected before planting in each installed at the centre of the experimental field, and PVC replication from 8 positions per replication, and the soil tubes with 3 inches in diameter were used to supply water to samples were air dried. After mixing and bulking, the soil the system. Module 1 supplied water to replications 1 and 2, samples were analyzed to determine the physical and and module 2 supplied water to replications 3 and 4. A chemical properties. The soil chemical and physical separate control valve was installed for each module, The properties were slightly different among experimental years. system was not operated until the crop was well established. The soil in 2010/11 was loamy sand and in 2011/12 was sand, Prior to transplanting of Jerusalem artichoke, a subsurface and clay particle in 2010/11 was slightly higher than in drip irrigation system (Super Typhoon®, Netafim Irrigation 2011/12 (Table 4). The differences in soil properties could be Equipment & Drip System, Israel) was installed with a due to tillage to break hard pan. Soil moisture content was spacing of 50 cm between drip lines and 20 cm between measured by gravimetric methods at transplanting, 14 DAT emitters. The drip lines were installed at 10 cm below the soil and harvest at the depths of 30, 60 and 90 cm. Soil moisture surface between the rows, and pressure values and water content was also measured with a neutron probe (Type I.H. II meters were fitted separately for all replications to ensure SER. No NO152, Ambe Didcot Instruments Co., Ltd., uniform supply of water. The insecticide carbofuran (2,3– England), and neutron probe readings were conducted at the dihydro–2,2–dimethyl benzofuran–7–ylmethylcarbamate 3% depths of 30, 60 and 90 cm (30 cm intervals) at 7–day G granular) at the rate 62.5 kg ha-1 was applied along the drip intervals throughout the course of the experiment. lines and then the drip lines were covered with soil. An aluminum access tube was installed at the middle of each Crop Data water level of the plot border to measure soil moisture content. Prior to planting, water was supplied to the soil Relative water content through drip irrigation at field capacity level. The healthy seedlings were then transplanted to the soil and inoculum of To evaluate plant water status, the relative water content was Trichoderma was applied to each hill before planting. Plot measured at 40, 60 and 70 DAT using the second or third size was 2 × 4 m in both years with a spacing of 50 cm expanded leaves from the top of the main stem of five plants between rows and 30 cm between plants within row. Manual from each plot. The leaves were cut with a disc borer 1 cm in weeding was done at 14 days after transplanting (DAT) and diameter, and leaf fresh weight was determined. The leaf mixed fertilizer of N – P2O5 –K 2O (15–15–15) at the rate of discs were placed in distilled water until the leaf was 156.25 kg ha-1 was applied at 30 DAT. moisture saturated. The turgid weight was determined after keeping the leaf sample in distilled water for 8 hours. The Water regimes leaf discs were oven-dried at 80 oC for 48 hours and leaf dry weight was determined. Water content was calculated based Water was supplied to the crop through drip irrigation system on the formula suggested by Kramer (1980) as follows; at field capacity level from transplanting to 10 DAT, and then RWC =[(FW – DW)/ (TW – DW)] × 100, drip irrigation system was no longer used. After 14 DAT, Where, FW: sample field weight, TW: sample turgid weight water was supplied through a line source sprinkler irrigation and DW: sample dry weight. system until harvest. Total crop water use for W1 was crop water requirement described by Doorenbos and Pruitt (1992), Biomass and tuber yield Where, ETcrop = ETo × Kc ETcrop = crop water requirement (mm/day) At harvest, the plants at two ends of the rows were discarded, ETo = evapotranspiration of a reference plant under all plants in an area of 2.1 m2 were harvested discarding the specified conditions calculated by pan evaporation method border rows, cut at the soil surface and separated into shoots Kc = the crop water requirement coefficient for sunflower, and tubers. Tubers were washed in tap water to remove the which varies depending on varieties and growth stages. As potting medium. Fresh shoot weight and tuber fresh weight crop coefficient for Jerusalem artichoke is not available in the were determined in the field (Ohaus model PA 413, USA) literature, the crop coefficient for sun flower (Monti et al., and then the weights were converted to fresh weights per 2005) is used because sunflower and Jerusalem artichoke are area. A random shoot fresh weight and tuber fresh weight closely related species and their morphological characters are from 10% of plants in each plot was taken, oven-dried at 80 similar. The amounts of water that were supplied to the crop °C for 72 hours or until constant weight, and weighed. at all moisture levels were monitored by catch can, which Biomass was calculated from shoot dry weight and tuber dry were installed in all replications of water treatments (6 cans weight. for each water treatment for a replication). 1679