پیش‌بینی ظهور گیاهچه علف‌های هرز هفت‌بند پیچکی (Polygonum convolvulus L.)، شاهتره (Fumaria vaillantii Lois) و پیچک صحرایی (Convolvulus arvensis L.) با استفاده از مدل‌های دمایی در شرایط کرج
محورهای موضوعی : زراعت
سجاد ایلانلو
1
(دانشجوی کارشناسی ارشد، دانشکده کشاورزی و صنایع غذایی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران)
مرجان دیانت
2
(استادیار دانشکده کشاورزی و صنایع غذایی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران)
مصطفی اویس
3
(3- دانشیار دانشگاه تهران)
فریدون قاسم خان قاجار
4
(استادیار دانشکده کشاورزی و صنایع غذایی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران)
کلید واژه: درجه روز رشد, بانک بذر, مدل لجستیک,
چکیده مقاله :
پیش‌بینی زمان رویش علف‌های هرز از طریق بهینه سازی زمان کنترل می‌تواند در کاهش مصرف علف‌کش‌ها موثر باشد. جهت پیش‌بینی زمان ظهور گیاهچه‌های هفت‌بند پیچکی، شاهتره و پیچک صحرایی با استفاده از مدل‌های دمایی، آزمایشی در فصل زراعی 92-1391 در مزرعه تحقیقاتی پردیس کشاورزی دانشگاه تهران اجرا گردید. بر اساس نتایج بدست آمده از تابع لجستیک سه پارامتره50 درصد رویش نهایی هفت‌بند پیچکی در حاشیه داخلی، مرکز و حاشیه خارجی به ترتیب با دریافت 21/75 و 48/71 و 21/75 درجه روز رشد حاصل شد. رویش شاهتره در حاشیه داخلی مزرعه در متوسط درجه روز رشد بالاتری اتفاق افتاد. البته شاهتره در حاشیه خارجی مزرعه نرخ رویش پایین‌تری را به ازاء درجه روز رشد دریافتی نسبت به سایر مناطق از خود نشان داد، یعنی با افزایش هر واحد درجه روز رشد تعداد گیاهچه کمتری نسبت به سایر مناطق مزرعه به سطح خاک آمدند. اگرچه در این منطقه به ازاء هر واحد درجه روز شیب کندتری از خود نشان داد اما با دریافت کمترین درجه روز رشد زودتر به 50 درصد رویش نهایی رسید. این در حالی بود که 50 درصد رویش نهایی شاهتره در مرکز و حاشیه داخلی مزرعه به ترتیب با دریافت 90/45 و 11/49 درجه روز رشد حاصل شد. پیچک صحرایی در حاشیه داخلی و مرکز مزرعه با دریافت 98/158 و60/150 درجه روز رشد به50 درصد رویش نهایی رسید. رابطه بین پیچک صحرایی موجود در بانک بذر با تعداد گیاهچه‌های رویش یافته مثبت بود اما رابطه‌ای بین تعداد بانک بذر هفت‌بند پیچکی و گیاهچه‌های رویش یافته مشاهده نشد.
Prediction of weed emergence timing would help reduce herbicide use through the optimization of the timing of weed control. In order to predict the emergence of wild buckwheat (Polygonum convolyulus L.), alkafaun (Fumaria vaillantii Lois) and Field bindweed (Convolvulus arvensis L.) by using the temperature model, an experiment was conducted at wheat field research of university of Tehran, Karaj during 2012-13. Based on the results, 50 percent of cumulative emergence of wild buckwheat were obtained in 75.21, 71.48 and 75.21 growing degree day at inner margin, center and outer margin of wheat field, respectively. The presence of wheat was not impressed the emergence of wild buckwheat. It was for that this weed was not required light for germination. Alkafaun emergence was happened at higher growing degree day at inner margin of field. Of course alkafaun had lower emergence per received GDD at outer margin in comparison with other parts of the field. Although emergence had lower slope per growing degree day at this part, but it was achieved to 50 percent cumulative emergence with lower received GDD. It was this time that 50 percent cumulative emergence of alkafaun achieved with 49.11 and 45.90 GDD at center and outer margin of field, respectively. Field bindweed was achieved to 50 percent of cumulative emergence with 158.98 and 150.60 growing degree day at inner margin and center of field. but there was no direct correlation between the number of weeds in the wild buckwheat seed bank and the number of seedlings were emerged.
منابع
1. Alm, D.M., Stoller, E.W., and Wax, L.M. 1993. An index model for predicting
seed germination and emergence rates. Weed Technology, 7: 560–569.
2. Anderson, R.L., and Nielsen D.C. 1996. Emergence pattern of five weeds in the
central great platns. Weed Technology, 10: 744–749.
3. Baskin, C.C., and Baskin, J.M. 1998. Seeds: Ecology, Biogeography, and
Evolution of Dormancy and Germination. San Diego, CA: Academic. 27–124.
4. Benech-Arnold, R.L., Ghersa, C.M., Sanchez, R.A., and Insausti, P. 1990. A
mathematical model to predict Sorghum halepense (L.) Pers. seedling emergence
in relation to soil temperature. Weed Research, 30: 91–99.
5. Blackshow, R.E. 1991. Soil temperature and moisture effects on downy brome Vs.
winter canola, wheat, and rye emergence. Crop Science, 31: 1034-1040.
6. Bostrom, U., Milberg, P., and Fogelfors, H. 2003. Yield loss in spring-sown cereals
related to the weed flora in the spring. Weed Science, 51:418–424.
7. Brown, R.F., and Mayer, D.G. 1988. Representing cumulative germination. The
use of the Weibull function and other empirically derived curves. Annual Botany,
61: 127-138.
8. Buhler, D.D., Liebman, M. and Obrycki, J.J. 2000. Theoretical and practice
challenges to an IPM approach to weed management. Weed Science, 48: 274-280.
9. Chantre, G.R., Blanco A.M., Forcella, F., Van Acker, R.C., Sabbatini, M.R., and
Gonzalez-Andujar, J.L. 2013. A comparative study between non-linear regression
and artificial neural network approaches for modeling wild oat (Avena fatua) field
emergence. Journal of Agricultural Science, 152: 1-9.
10. Donald, W.W. 2000. A degree-day model of Cirsium arvense shoot emergence
from adventitious root buds in spring. Weed Science, 48: 333-341.
11. Dorado, J., Sousa, E., Calha, I.M., Gonzalez-Andujar, J.L., and Fernandez-
Quintanilla, C. 2009. Predicting weed emergence in maize crops under two
contrasting climatic conditions. Weed Research, 49: 251-260.
12. du Croix Sissons, M.J., Van Acker, R.C., Derksen, D.A., and Thomas A.G. 2000.
Depth of seedling recruitment of five weed species measured in situ in
conventional- and zero-tillage fields. Weed Science, 48: 327–332.
13. Forcella, F. 1998. Real-time assessment of seed dormancy and seedling growth for
weed management. Seed Science Research, 8: 201–209.
14. Forozesh, S., Rahimmian Mashhadi, H., Alizade, H., Oveisi, M., and Tasob
Shirazi, M. 2015. Predicting seedling emergence of different wild oat (Avena
ludoviciana). Iranian Journal of Weed Science, 11: 91-104.
15. Forsberg, D.E., and Best, K.F. 1963. The emergence and plant development of wild
buckwheat (Polygonum convolvolus) Experimental Farm, Canada Department of
Agriculture, Scott, Saskatchewan, and Swift Current, Saskatchewan, respectively
Received May 2,
16. Friesen, G., and Shebeski, L.H. 1960. Economic losses caused by weed
competition in Manitoba grain fields. I. Weed species, their relative abundance and
their effect on crop yields. Canadian Journal of Plant Science, 40: 457–467.
17. Gan, Y., Stobbe E.H., and Moes, J. 1992. Relative date of wheat seedling
emergence and its impact on grain yield. Crop Science, 32: 1275-1281.
18. Gruenhagen, R.D., and Nalewaja, J. D. 1969. Competition between flax and wild
buckwheat. Weed Science, 17: 380–384.
19. Gubanov, I.A., Kiseleva K.V., Novikov, V.S., and Tihomirov, V.N. 2004. An
Illustrated identification book of the plants of Middle Russia, Vol. 3: Angiosperms
(dicots: archichlamydeans). Moscow: Institute of Technological Researches. 3. p.
520.
20. Harvey, S.J., and Forcella, F. 1993. Thermal seedling emergence model for
common lambsquarters (Chenopodium album). Weed Science, 41: 309-316.
21. Holm, L.G. Plucknett, D.L, Pancho J.V., and Herberger, J.P. 1991. The world‘s
worst weeds: distribution and biology. Malabar: Krieer.The University Press of
Hawaii, Honolulu. p. 98-104.
22. Hume, L., Martinez, J., and Best, K. 1983. The biology of Canadian weeds. 60.
Polygonum convolvulus L. Canadian Journal of Plant Science, 63: 959–971.
23. Jafari, S., Yousefi, A.R., and Mansorifar, C. 2018. Prediction of weed seedling
emergence under different nitrogen levels in Pisum sativum L. Iranian Journal of
Weed Science, 14: 9-18.
24. Keshtkar, E., Kordbachehm, F. Mesgaran, M.B., Mashhadi, H.R., and Alizadeh,
H.M. 2009. Effects of the sowing depth and temperature on the seedling emergence
and early growth of wild barley (Hordeum spontaneum) and wheat. Weed Biology
and Management, 9: 10–19.
25. Khakzad, R., Alebrahim, M.T., and Oveisi, M. Effect of management operations
on spotted spurge (Euphorbia maculata L.) emergence time in soybean. 2020.
Iranian Journal of Weed Science, 16: 27-43.
26. Klein, H. 2011. Black bindweed Fallopia convolvulus (Linnaeus) Á. Löve or
Polygonum convolvulus L. Alaska Natural Heritage Program.
http://aknhp.uaa.alaska.edu.
27. Kruk, B., Insausti, P., Razul, A., and Benech-Arnold, R. 2006. Light and thermal
environments as modified by a wheat crop: effects on weed seed germination.
Journal of Applied Ecolology, 43: 227–236.
28. Leblanc, M.L., Cloutier, D.C. Stewart, K.A., and Hamel, C. 2003. The use of
thermal time to model common lambsquarters (Chenopodium album) seedling
emergence in corn. Weed Science, 51: 718–724.
29. Leguizamon, E.S., Rodriguez, N., Rainero, H., Perez, M., Perez, L., Zorza, E., and
fernandez-Quintanilla, C. 2009. Modeling the emergence pattern of six summer
annual weed grasses under no tillage systems in Argentina. Weed Research, 49:
98-106.
30. Leguizamon, E.S., Fernandez-Quintanilla, C., Barros, J., and Gonzalez-Andujar,
J.L. 2005. Using thermal and hydrothermal time to model seedling emergence of
Avena sterilis ssp ludoviciana in Spain. Weed Research, 45: 149–156.
31. Lyons, K. E. Element stewardship abstract for Convolvulus arvensis L. 1998. In:
Field bindweed. Arlington: The Nature Conservancy. 1-21
32. Mennan, H., and M. Ngouajio. 2006. Seasonal cycles in germination and seedling
emergence of summer and winter populations of catchweed bedstraw (Galium
aparine) and wild mustard (Brassica kaber). Weed Science, 54: 114–120.
33. Mohler C. L., and Calloway M. B. 1992. Effects of tillage and mulch on the
emergence and survival of weeds in corn. Journal of Applied Ecology, 29: 21–34.
34. Myers, M.W., Curran, W.S., VanGessel, M. J., Calvin, D.D., Mortensen, D.A.,
Majek, B.A., Karsten, H.D., and Roth, G.W. 2004. Predicting weed emergence for
eight annual species in the Northeastern United States. Weed Science, 52: 913-919.
35. Norsworthy, J.K., and Oliveira, M.J. 2007. A model predicting common cocklebur
(Xanthium strumarium) emergence in soybean. Weed Science, 55: 341–345.
36. Norton, G. 2003. Understanding the success of fumitory as a weed in Australia,
PhD thesis, Charles Sturt University.
37. Roman, E.S., Murphy, S.D., and Swanton, C.J. 2000. Simulation of Chenopodium
album emergence. Weed Science, 48: 217–224.
38. Roman, E.S., Murphy S.D., and Swanton C.J. 1999. Effect of tillage and Zea mays
on Chenopodium album seedling emergence and density. Weed Science, 47: 551–
556.
39. Royo-Esnal, A., Torra, J., Conesa, J.A., Forcella, F., and Recasens, J. 2010.
Modeling the emergence of three arable bedstraw (Galium) species. Weed Science,
58: 10–15.
40. Smutny, V., and Kren, J. 2002. Improvement of an elutriation method for
estimation of weed seedbank in the soil. Rostlinna Vyroba, 48: 271–278.
41. Tanveer, A., Taseem, M., Khaliq, A., Javaid, M.M., and Chaudhry, M.N. 2013.
Influence of seed size and ecological factors on the germination and emergence
of field bindweed (Convolvulus arvensis). Planta Daninha, 31: 39-51
42. Yousefi, A.R., Oveisi, M., and Gonzalez-Andujar, J.L. 2014. Prediction of annual
weed seed emergence in garlic (Allium sativum L.) using soil thermal time. Scientia
Horticulture, 168: 189–192.
43. White, S.N., Boyd, N.S., and Van Acker, R.C. 2015.Temperature Thresholds and
Growing-Degree-Day Models for Red Sorrel (Rumex acetosella) Ramet Sprouting,
Emergence, and Flowering in Wild Blueberry. Weed Science, 63: 254-263