تأثیر کمبود آب برمحتوای نسبی آب برگ، شاخص‌های فلورسانس کلروفیل و عملکرد دانه چهار رقم لوبیا چیتی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه محقق اردبیلی

2 دانشیار دانشگاه علوم کشاورزی و منابع طبیعی ساری

3 استادیار دانشگاه زنجان

4 استادیار دانشگاه فردوسی مشهد

5 کارشناس ارشد اصلاح نباتات دانشگاه آزاد اسلامی واحد اردبیل

چکیده

سابقه و هدف: لوبیا چیتی گیاهی حساس به تنش خشکی است، در عین حال در این گیاه از لحاظ مقاومت به خشکی، تنوع ژنتیکی مشاهده می‌شود. پژوهش حاضر با هدف بررسی اثر تنش خشکی بر محتوای نسبی آب برگ، شاخص‌های فلورسانس کلروفیل و عملکرد دانه‌ی ارقام لوبیا چیتیL.) vulgaris (Phaseolus کشت شده در استان زنجان اجرا گردید.
مواد و روش‌ها: این پژوهش به‌صورت کرت‌های خرد شده بر پایه‌ی بلوک های کامل تصادفی در چهار تکرار، در مزرعه‌ی تحقیقاتی دانشگاه زنجان انجام شد. سطوح آبیاری شامل شاهد و تنش خشکی در کرت‌های اصلی و ارقام لوبیا چیتی شامل محلی خمین، صدری، Ks21193 و Ks21189 در کرت‌های فرعی قرار داده شدند. در این آزمایش محتوای نسبی آب برگ، فلورسانس کمینه، فلورسانس بیشینه، فلورسانس متغیر، عملکرد کوانتومی فتوسیستم II و عملکرد دانه اندازه‌گیری شدند.
یافته‌ها: بر اساس نتایج به‌دست آمده اثر تنش خشکی در تمام صفات به‌جز فلورسانس بیشینه و بر‌هم‌کنش تنش خشکی در رقم برای تمام صفات به‌جز فلورسانس کمینه و فلورسانس بیشینه معنی‌دار بود. در این آزمایش مشاهده شد که میزان محتوای نسبی آب برگ، فلورسانس متغیر، عملکرد کوانتومی فتوسیستم II و عملکرد دانه‌ در ارقام در شرایط تنش خشفکی به‌طور معنی‌داری کمتر از شاهد بود. محدودیت آبی عملکرد کوانتومی فتوسیستم II را به‌دلیل افزایش F0 (فلورسانس حداقل یا کمینه در شرایط سازگار شده با تاریکی) و کاهش Fm (فلورسانس حداکثر یا بیشینه در شرایط سازگار شده با تاریکی) کاهش داد. نتایج به‌دست آمده نشان داد که رقم Ks21189 از بیشترین محتوای نسبی آب برگ (24/74 درصد)، فلورسانس متغیر (2046) و عملکرد کوانتومی فتوسیستم II (70/0) در شرایط تنش خشکی برخوردار بود. در ضمن میزان کاهش محتوای نسبی آب برگ و عملکرد کوانتومی فتوسیستم II در رقم Ks21189 در شرایط تنش خشکی نسبت به شاهد کمتر بود. همین رقم حداکثر عملکرد دانه (6/741 کیلوگرم در هکتار) را در شرایط تنش داشت. این مسئله نشاندهنده‌ی مقاومت رقم Ks21189به تنش خشکی و تحریک این رقم به افت کمتر عملکرد کوانتومی فتوسیستم II در شرایط محدودیت آب می‌باشد. کمترین محتوای نسبی آب (8/51 درصد)، فلورسانس متغیر (5/1245)، عملکرد کوانتومی فتوسیستم II (63/0) و عملکرد دانه (1/503 کیلوگرم در هکتار) در کرت‌هایی برآورد گردید که رقم صدری تحت شرایط تنش رطوبتی به‌کار برده شد. ژنوتیپ صدری با کاهش عملکرد 18/80 % حساس‌ترین ژنوتیپ به کمبود آب بود.
نتیجه‌گیری: بررسی ضرایب همبستگی، نشان‌گر همبستگی مثبت و معنی‌دار، محتوای نسبی آب برگ، فلورسانس بیشینه، فلورسانس متغیر و عملکرد کوانتومی فتوسیستم II با عملکرد دانه می‌باشد. لذا چنین به‌نظر می‌رسد ارقامی که بتوانند در شرایط تنش خشکی پایداری محتوای نسبی آب برگ و عملکرد کوانتومی فتوسیستم II را حفظ کنند، به‌دلیل برخورداری از سرعت فتوسنتز بالاتر، از عملکرد دانه بیشتری برخودار خواهند بود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Effects of water deficit on Relative Water Content, Chlorophyll Fluorescence indices and seed yield in four pinto bean genotypes

نویسندگان [English]

  • somayyeh soheili movahhed 1
  • mohammadali esmaeili 2
  • farhad jabbari 3
  • sorour khorramdel 4
  • aghil fouladi 5
1
2
3
4
5
چکیده [English]

Background and objectives: Pinto bean is a susceptible plant to drought stress. However, there is genotype variation for the trait in this plant. The aim of this study was to investigate the effect of drought stress on leaf relative water content, chlorophyll fluorescence indices and grain yield of pinto bean genotypes (Phaseolus vulgaris L.) cultivated in Zanjan province.
Materials and methods: an experiment was conducted as spilt plot based on a completely randomized block design with four replications at Zanjan university research farm. Irrigation levels (control and drought stress) and genotypes (Local khomein, Sadri, Ks21193 and Ks21189) were set in the main and subplot, respectively. In this experiment leaf relative water content, minimum fluorescence, maximum fluorescence, variable fluorescence, quantum yield of photosystem II and grain yield were measured.
Results: Results showed that the drought stress effects for all traits, except for maximum fluorescence and the interaction of drought stress and cultivar for all traits, except for minimum fluorescence and maximum fluorescence were significant. In this experiment, it was also observed that on leaf relative water content, variable fluorescence, quantum yield of photosystem II and grain yield of genotypes were significantly lower under drought stress compared to the control. The results showed that water deficit caused quantum yield of photosystem II declined significantly due to increasing of minimum fluorescence and decreasing of maximum fluorescence. Results indicated that Ks21189 genotype showed maximum leaf relative water content (74/24%), variable fluorescence (2046) and quantum yield of photosystem II (0/70) under drought stress. Also, Ks21189 genotype exhibited the least reduction for leaf relative water content and quantum yield of photosystem II under drought stress in comparison to control. In addition, this genotype had maximum seed yield (741/6 Kg.Ha-1) under drought stress. These findings confirm the resistance of Ks21189 genotype to drought stress and stimulating this genotype to least reduction for quantum yield of photosystem II under water limitation conditions. Minimum leaf relative water content (51/8%), variable fluorescence (1245/5), quantum yield of photosystem II (0/63) and grain yield (503/1 Kg.Ha-1) was obtained in the plots which sadri genotype under drought condition was applied. Sadri genotype was identified as water deficit stress sensitive genotypes with the reduction of yield 80/18%.
Conclusion: Correlation analysis indicated significant and positive correlation between leaf relative water content, maximum fluorescence, variable fluorescence and quantum yield of photosystem II with grain yield. Thus, it seems that under drought stress, genotypes with stable quantum yield of photosystem II and leaf relative water content produce higher grain yield because of higher photosynthesis rate.

کلیدواژه‌ها [English]

  • Drought stress
  • Quantum yield of photosystem II
  • Variable fluorescence
  • Ks21189
Adibifard, N., Esfandiari, M., Hassanpour Avanji, S.R., and Baniabbass, Z.
2014. Zoning of Canola Cultivation Based on Climatic Temperature Needs
Using of GIS in Golestan Province. Int. J. Adv. Biol. Biom. Res. 2(4): 1226-
1231. (In Persian)
2. Araya, A., Keesstra, S.D., and Stroosnijder, L. 2010. A new agro-climatic
classification for crop suitability zoning in northern semi-arid Ethiopia. Agr.
Forest. Meteorol., 150: 1057–1064.
3. Bagli, S., Terres, J.M., Gallego, J., Annoni, A., and Dallemand, J.F. 2003.
Agro-Pedo Climatological Zoning of Italy, European Commission Directorate
General Joint Research Center (ISPRA).
4. Bidadi, M., Kamkar, B., and Abadi, O. 2014. Zoning of Suitable Areas for
Soybean Cropping in Qaresoo Basin Using Geospatial Information Systems
(GIS). EJCP., 7(2): 175-187. (In Persian)
5. Bishnoi, O.P. 2010. Applied Agroclimetology. Oxford book company. Jaipur,
India. 540p.
6. Caldiz, D.O., Haverkort, A.J., and Struik, P.C. 2002. Analysis of a complex
crop production system in interdependent agro-ecological zones: a
methodological approach for potatoes in Argentina. Agr. Syst., 73: 297–311.
7. Cheraghi, H. 2013. Agro climatic suitability of rain fed Chick pea (Cicer
ariegtinum) using growth length index and geographical information system in
Kurdistan province. A Thesis Submitted for the Degree of MSc. Department of
Agriculture. University of Zabol. Iran. 150p. (In Persian)
8. Cheraghi, R. 2013. Agro climatic suitability of rain fed Canola using growth
length index and geographical information system in Khuzestan province. A
Thesis Submitted for the Degree of MSc. Department of Agriculture. University
of Zabol. Iran. 120p. (In Persian)
9. Darini, A., Fathi, G., Gharineh, M.H., Alami-Saeid, K., Khodadadi, M., and
Siadat, S.A. 2013. Effect of planting date and application of anti-freeze on tuber
yield and some physiological traits of potato cultivars in autumn planting in
jiroft region of Iran. Seed. Plant Prod. J., 29(4): 443-459. (In Persian)
10. DePauw, E., Mirghasemi, Ghaffari, A., and Nseir, B. 2008. Agro ecological
zones of Karkheh River Basin: A reconnaissance assessment of climatic and
edaphic patterns and their similarity to areas inside and outside the basin.
Technical Report, ICARDA. 96p.
11. Ewing, E.E. 1981. Heat stress and the tuberization stimulus. Amer. Potato.,
1(58): 31-49.
12. FAO. 1996. Guidelines: Agro ecological zoning. FAO. Soils Bultin 73. FAO.
Rome. 89p.
13. Ghaffari, A. 2008. Agroclimatic zoning of Iran, Rainfed crop production areas
with particular emphasis to agro ecological characterization. Report,
Agricultural Extension, Education and Research Organization (AEERO), Dry
land Agricultural Research Institute (DARI). ICARDA Technical Report. 214p.
14. Haverkort A.J., and MacKerron D.K.L. 1995. Potato Ecology and Modelling of
Crops under Conditions Limiting Growth. Springer-Science Business Media,
B.V. 371p.
15. Hollinger, S.E. 2003. "Chapter 1. Agricultural climatology." In Illinois
Agronomy Handbook: 23rd edition. Champaign, IL: University of Illinois
Agricultural Extension Service, Pp: 1-21.
16. Kazemi Poshtmazari, H., Tahmasebi Sarvestani, Z., Kamkar, B., Shataee, Sh.,
and Sadeghi, S. 2012. Agroecological zoning of agricultural lands in Golestan
province for canola cultivation by Geographic Information System (GIS) and
Analytical Hierarchy Process (AHP). EJCP., 5(1): 123-139. (In Persian)
17. Kazemi, H. 2014. Agro ecological zoning of Gorgan agricultural lands for
hulless barley cropping base on Boolean logic. EJCP., 6(4): 165-185. (In
Persian)
18. Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F. 2006. World map of
the Koppen-Geiger climate classification updated, Meteorol. Z. 15(3): 259–263.
19. Marinoni, O. 2004. Implementation of the analytical hierarchy process with
VBA in ArcGIS, Comput. Geosci., 30(6): 637-646.
20. McCoy, J., Johnston, K., Kopp, S., Borup, B., Willison, J., and Payne, B. 2002.
Using ArcGIS Spatial Analyst. ESRI, New York. 238p.
21. Nadler, A.J. 2007. An agro climatic risk assessment of crop production on the
Canada Prairies. A Thesis Submitted for the Degree of MSc. Department of Soil
Science. University of Manitoba. Winnipeg, Manitoba., 251p.
22. Neamatollahi, E., Bannayan, M., Jahansuz, M.R., Struik, P., and Farid, A.R.
2012. Agro ecological zoning for wheat (Triticum aestivum), sugar beet (Beta
vulgaris) and corn (Zea mays) on the Mashhad plain, Khorasan Razavi
province. Egypt. J. Remote Sens. Space Sci., 15: 99–112.
23. Ngai, E.W.T., and Chan, E.W.C. 2005. Evaluation of knowledge management
tools using AHP. Expert Syst. Appl., 29(4): 889-899.
24. Nikzad, M. 2015. Agro ecological zoning of potato for autumn cropping system
using WOFOST model and GIS in Kerman province. MSc dissertation, Faculty
of Agriculture, University of Jiroft, Iran. (In Persian)
25. Prentice, I.C., Cramer, W., Harrison, S.P., Leemans, R., Monserud, R.A., and
Solomon, A.M. 1992. A global biome model based on plant physiology and
dominance, Soil properties and climate, J. Biogeo., 19: 117-134.
26. Rasco, E.T.J., Plaisted, R.L., and Ewing, E.E. 1980. Photoperiod response and
earliness of S. tuberosum spp. Andigena after six cycles of recurrent selection
for adaptation to long days. Am. J. Potato. Res. 1.57: 435-448.
27. Saaty, T.L. 1980. The Analytical Hierarchy Process, Pinning Priority, Resource
Allocation”, RWS Publication, USA.
28. Saaty, T.L. 1986. Axiomatic foundation of analytical hierarchy process. Manag.
Sci. 32(7): 841-855.
29. Saaty, T.L. 1994. Highlights and critical points in the theory and application of
the analytical hierarchy process. Eur. J. Oper. Res. 74: 426-447.
30. Salmeron, J.L. 2005. An AHP based methodology to rank critical success
factors of executive information systems. Comput. Stand. Inter., 28(1): 1-12.
31. Sands, P.J., Hackett, C., and Nix, H.A. 1979. A model of the development and
bulking of potato (Solanum tuberosum) derivation from well managed crop.
Field Crop Res., 2: 309-331.
32. Sarparast, R., and Mashayekhi, K. 2014. Heat unit evaluation of potato
genotypes for determining different maturity groups in Gorgan region. EJCP.,
7(3): 123-143. (In Persian)
33. Seppänen, M.M. 2000. Characterization of freezing tolerance in Solanum
commersonii (Dun.)With special reference to the relationship between freezing
and oxidative stress. Appendices. A Thesis Submitted for the Degree of MSc.
Department of Plant Production. University of Helsinki Finland, 55p.
34. Snyder, R.G., and Ewing, E.E. 1989. Interactive effects of temperature,
photoperiod, and cultivar on tuberization of potato cuttings. Hort. Sci., 24: 336-
338.
35. Solaimani, N., Ashori, Z., Moalemi, M., Karimzadeh, S., Azimzade, S. 2015.
The Role of Climate and climatic factors on crop zoning agroclimatic sunflower
3cultivation in Hamedan province. Int. J. Adv. Biol. Biom. Res., 2(4): 248-255.
(In Persian)
36. Soltani, A., Hammer, G.L., Torabi, M.J., Robertson, B., and Zeinali, E. 2006.
Modeling chickpea growth and development: phenological development. Field
Crops Res., 99: 1-13.
37. Sun, W., and Huang, Y. 2011. Global warming over the period 1961–2008 did
not increase high-temperature stress but did reduce low-temperature stress in
irrigated rice across China Agr. Forest Meteorol., 151(9): 1193–1201.
38. Supit, I., Van Diepen, C.A., De Wit, A.J.W., Wolf, J., Kabat, P., Baruth, B., and
Ludwig, F. 2012. Assessing climate change effects on European crop yields
using the Crop Growth Monitoring system and a weather generator. Agr. Forest.
Meteorol., 164: 96–111.
39. Taati, A., Sarmadian, F., Mousavi, A., and Rahmani, A. 2015. Agro-ecological
zoning for cultivation of Alfalfa (Medicago sativa L.) using RS and GIS. Sci.
Agri., 9(2): 93-100.
40. UNESCO. 1979. Map of the World Distribution of Arid Regions, Map at Scale
1:25,000,000 with Explanatory Note. UNESCO, Paris, ISBN: 92-3-101484-6,
54p.
41. Van Bussel, L.G.J., Wolf, J., Licker, R., Grassini, P., Nelson, A., Boogaard, H.,
Gerber, J., Mueller, N.D., Claessens, L., Van Ittersumb, M., and Cassman, K.G.
2013. Use of agro-climatic zones to upscale simulated crop yield potential.
Field Crops Res., 143: 44–55.
42. Van Wart, J., Kersebaum, K.C., Peng, S., Milnera, M., and Cassman, K.G.
2013b. Estimating crop yield potential at regional to national scales. Field Crops
Res., 143: 34–43.
43. Wheeler, R.M., and Tibbetts, T.W. 1986. Utilization of potatoes for life support
systems in space: I-Cultivar-photoperiod interactions. Am. Potato. J., (63): 315-
323.
44. Wolf, J., and Van Oijen, M. 2002. Modelling the dependence of European
potato yields on changes in climate and CO2. Agr. Forest Meteorol., 112 (3-4):
217–231.
45. Yasari, T., Khoshhal, J., and Shahsavari, M.R. 2013. Planting dates zoning of
safflower varieties in Esfahan province. G.E.P., 49(1): 171-182. (In Persian)