پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,504 |
| تعداد مشاهده مقاله | 124,123,522 |
| تعداد دریافت فایل اصل مقاله | 97,231,690 |
ارزیابی قابلیت شاخصهای طیفی در بررسی تنش آبی درخت زیتون | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 13، دوره 51، شماره 1، فروردین 1399، صفحه 179-190 اصل مقاله (774.94 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2019.285004.668254 | ||
| نویسندگان | ||
| عظیمه عسگری1؛ عبدالرحیم هوشمند** 2؛ سعید برومندنسب3؛ شهره زیودار4 | ||
| 1دانشجوی دکتری، گروه آبیاری و زهکشی، دانشکده علوم آب، دانشگاه شهید چمران اهواز، اهواز، ایران | ||
| 2دانشیار، گروه آبیاری و زهکشی، دانشکده علوم آب، دانشگاه شهید چمران اهواز، اهواز، ایران | ||
| 3استاد، گروه آبیاری و زهکشی، دانشکده علوم آب، دانشگاه شهید چمران، اهواز، ایران | ||
| 4استادیار، گروه علوم باغبانی، دانشکده کشاورزی، دانشگاه شهید چمران، اهواز، ایران | ||
| چکیده | ||
| طیفسنجی، امکان بررسی سریع و غیرمخرب وضعیت تنش آبی گیاه را فراهم مینماید. هدف از این مطالعه ارزیابی قابلیت چندین شاخص طیفی از جمله شاخص آب ()، شاخص نرمال آب 1-5 () و شاخص نرمال آب بر اساس انعکاس در طول موجهای 960 و 940 نانومتر ()، در بررسی وضعیت تنش آبی درخت زیتون بود. تیمارهای آزمایشی شامل دو رقم زیتون (کرونیکی و ) و چهار رژیم آبیاری (آبیاری برای تأمین 100، 85، 70 و 55 درصد از نیاز آبی گیاه) بود. نتایج نشان داد که درختان زیتون در تیمارهای متفاوت آبیاری برای تأمین 85، 70 و 55 درصد از نیاز آبی گیاه بهطور متوسط نسبت به تیمار شاهد، به ترتیب در معرض حدود 11، 15 و 20 درصد کمبود آب خاک، قرار داشتند. به دلیل مقاومت بالای درخت زیتون در برابر تنش آبی، کم آبیاری در سطح 15، 30 و 45 درصد، تأثیر معنیداری در مقدار شاخصهای طیفی مورد مطالعه نداشت. با این حال شاخصهای طیفی با شاخص محتوای نسبی آب برگ گیاه، ارتباط خطی نزدیک و معنیدار داشت (**76/0*26/0). بهطور کلی شاخص طیفی نرمال آب کمترین ضریب تبیین را با شاخص محتوای نسبی آب برگ در طول اندازهگیریها نشان داد (23-1 درصد کمتر از سایر شاخصهای مورد مطالعه). بر اساس مقدار متوسط شاخصهای طیفی و شاخص رطوبت نسبی آب برگ در طول دورهی تحقیق، شاخصهای طیفی ، ، ، ، ، و ، به ترتیب رابطهی بهتری با شاخص محتوای نسبی آب برگ زیتون نشان دادند. در نهایت میتوان بیان کرد که شاخصهای طیفی ، و میتوانند جهت بررسی سریع و غیر مخرب وضعیت تنش آبی درخت زیتون، مورد استفاده قرار گیرند. | ||
| کلیدواژه‌ها | ||
| طیف سنجی؛ شاخص طیفی؛ تنش آبی گیاه؛ محتوای نسبی آب برگ؛ درخت زیتون | ||
| عنوان مقاله [English] | ||
| Evaluation of the Capability of Spectral Water Indices for Assessing Water stress in Olive Tree | ||
| نویسندگان [English] | ||
| Azimeh Asgari1؛ Abdolrahim Hooshmand2؛ Saeed BoroomandNasab3؛ Shohre Zivdar4 | ||
| 1Ph. D. student, Irrigation and drainage department, Water science faculty, Shahid Chamran University, Ahwaz, Iran | ||
| 2Associate Professor, Irrigation and drainage department, Water science faculty, Shahid Chamran University, Ahwaz, Iran | ||
| 3Full Professor, irrigation and drainage department, Water science faculty, Shahid Chamran University, Ahwaz, Iran | ||
| 4Assistant professor, Horticulture science department, Agriculture College, Shahid Chamran University, Ahwaz, Iran | ||
| چکیده [English] | ||
| Spectrometric measurements have the potential for fast and non-destructive measurements of plant water stress. The aim of this work was to investigate the ability of several spectral water indices, including water index (WI), normalized spectral water indices 1-5 (NWI 1-5), and normalized water index based on wavelengths in 960 and 940 nm (NWI 960-940) for detection of water stress in olive trees. The experimental treatments involved two olive cultivars (Koroneiki and T2) and four water regimes (100%, 85%, 70%, and 55% of crop water requirement). Results showed that the olive trees in different water supplies 85%, 70%, and 55% of ETc were subjected to soil moisture deficit equal to 11, 15, and 20%, respectively, as compared to soil moisture of control treatment. Because of the high resistance of olive trees to water stress, water reduction at levels of 15, 30, and 45 percent did not have significant effects on spectral indices. However, spectral indices were closely and significantly linear associated with relative water content of the crop leaf (). Among all tested water spectral indices, NWI-2 showed the least consistent associations with relative water content of the leaf (ranging from 1–23% less than the ones in other tested indices). Based on the average amount of spectral indices and relative water content during the study period, NWI4, NWI5, NWI1, WI, NWI960-940, NWI3, and NWI2 showed a stronger relationship with the relative water content of olive leaves, respectively. In conclusion, spectral reflectance indices, WI, NWI 1-5, and NWI 960-940, could be useful for fast and non-destructive estimating of plant water stress. | ||
| کلیدواژه‌ها [English] | ||
| Spectrometry, Spectral Index, Plant Water Stress, relative water content, Olive Tree | ||
| مراجع | ||
|
Agam, N., Cohen, Y., Berni, J.A.J., Alchanatis, V., Cool, D., Dag, A., Yermiyahu, U. and Ben-Gal, A. (2013). An insight to the performance of crop water stress index for olive trees. Agricultural Water Management, 118, 79-86. Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998). Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage. Paper No. 56, FAO, Rome, Italy, pp. 300. Babar, M. A., Reynolds, M. P, van Ginkel, M., Klatt, A. R., Raun, W. R. and Stone, M. L. (2006). Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Science. 46, 578-588. Bacelar, E. A., Santos, D. L., Moutinho-Pereira, J. M., Goncalves, B. C., Ferreira, H. F. and Correia, C. M. (2006). Immediate responses and adaptative strategies of three olive cultivars under contrasting water availability regimes, Changes on structure and chemical composition of foliage and oxidative damage. Plant Science, 170, 596-605. Becker, E. and Schmidhalter, U. (2017). Evaluation of yield and drought using active and passive spectral sensing systems at the reproductive stage in wheat. Frontiers in Plant Science, 8, 1–15. Berni, J. A. J, Zarco-Tejada, P. J., Sepulcre-Canto, G., Fereres, E. and Villalobos, F. (2009). Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery. Remote Sensing of Environment, 113, 2380-2388. Cohen, Y., Alchanatis, V., Meron, M., Saranga, Y. and Tsipris, J. (2005). Estimation of leaf water potential by thermal imagery and spatial analysis. Journal of Experimental Botany, 56 (417), 1843–1852. DeJonge, K. C, Taghvaeian, S., Trout, T. J. and Comas, L. H. (2015). Comparison of canopy temperature-based water stress indices for maize. Agricultural Water Management, 156, 51–62. Eitel, J. U. H., Gessler, P. E., Smith, A. M. S and Robberecht, R. (2006). Suitability of existing and novel spectral indices to remotely detect water stress in Populus spp. Forest Ecology and Management, 229, 170–182. Elsayed, S. and Darwish, W. (2017). Hyperspectral remote sensing to assess the water status, biomass, and yield of maize cultivars under salinity and water stress. Bragantia, 76, 62–72. Elsayed, S., Elhoweity, M., Ibrahim, H.H., Dewir, Y.H., Migdadi, H.M. and Schmidhalter, U. (2017). Thermal imaging and passive reflectance sensing to estimate the water status and grain yield of wheat under different irrigation regimes. Agricultural Water Management, 189, 98-110. Elsayed, S., Elhoweity, M. and Schmidhalter, U. (2015). Normalized difference spectral indices and partial least squares regression to assess the yield and yield components of peanut. Australian Journal of Crop Science, 9, 976-986. Elsayed. S., Mistele, B. and Schmidhalter, U. (2011). Can changes in leaf water potential be assessed spectrally? Functional Plant Biology, 38, 523–533. Fereres, E., Orgaz, F. and Gonzalez-Dugo, V. (2011). Reflections on food security under water scarcity. Journal of Experimental Botany, 62, 4079–4086. Garces-Restrepo, C., Vermillion, D. and Munoz, G. (2007). Irrigation management transfer. Worldwide efforts and results. FAO, Rome, pp. 62. Garcia-Tejero, I. F., Hernandez , A., Padilla-Diaz, C. M., Diaz-Espejo, A. and Fernandez, J. . (2017). Assessing plant water status in a hedgerow olive orchard from thermography at plant level. Agricultural Water Management, 188, 50-60. Geerts, S. and Raes, D. (2009). Deficit irrigation as an on farm strategy to maximize crop water productivity in dry areas. Agricultural Water Management, 96, 1275–1284. Gutierrez, M., Reynolds, M. P., Raun, W. R., Stone, M. L. and Klatt, A. R. (2010). Spectral water indices for assessing yield in elite bread wheat genotypes in well irrigated, water stressed, and high temperature conditions. Crop Science, 50, 197–214. Kim, Y., Glenn, D. M., Park, J., Ngugi, H. K. and Lehman, B. L. )2011(. Hyperspectral image analysis for water stress detection of apple trees. Computers and Electronics in Agriculture, 77, 155-160. Maki, M., Ishiahra, M. and Tamura, M. (2004) Estimation of leaf water status to monitor the risk of forest fires by using remotely sensed data. Remote Sensing of Environment, 90, 441-450. Mangus, D. L, Sharda, A. and Zhang, N. (2016). Development and evaluation of thermal infrared imaging system for high spatial and temporal resolution crop water stress monitoring of corn within a greenhouse. Computers and Electronics in Agriculture, 121, 149-159. Marino, G., Pallozzi, E., Cocozza, C., Tognetti, R., Alessio, G., Cantini, C. and Centritto, M. (2014). Assessing gas exchange, sap flow and water relations using tree canopy spectral reflectance indices in irrigated and rainfed Olea europaea L. Environmental and Experimental Botany, 99, 43-52. Penuelas, J., Pinol, J., Ogaya, R. and Filella, I. (1997). Estimation of plant water concentration by the reflectance water index (R900/R970). International Journal of Remote Sensing, 18, 2869–2875. Penuelas, J., Filella, I., Biel, C., Serrano, L. and Save, R. (1993). The reflectance at the 950–970 mm region as an indicator of plant water status. International Journal of Remote Sensing, 14,1887-1905. Pinter, P. J., Hatfield, J. L., Schepers, J. S., Barnes, E. M., Moran, M. S, Daughtry, C. S and Upchurch, D. R. (2003). Remote sensing for crop management. Photogrammetric Engineering and Remote Sensing, 69(6), 647-664. Prasad, B., Carver, B. F., Stone, M. L., Babar, M. A., Raun, W.R. and Klatt, A. R. (2007). Potential use of spectral reflectance indices as a selection tool for grain yield in winter wheat under Great Plains conditions. Crop Science, 47, 1426–1440. Pu, R., Ge, S., Kelly, N. and Gong, P. (2003). Spectral absorption features as indicators of water status in coast live oak (Quercus Agrifolia) leaves. International Journal of Remote Sensing. 24, 1799-1810. Richards, R. A., Rebetzke, G. J, Watt, M., Condon, A., Spielmeyer, W. and Dolferus, R. (2010). Breeding for improved water productivity in temperate cereals, phenotyping, quantitative trait loci, markers and the selection environment. Functional Plant Biology, 37, 85–97. Sims, D. and Gamon, J. (2003). Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance, a comparison of indices based on liquid water and chlorophyll absorption features. Remote Sensing of Environment, 84, 526–537. Schlemmer, M. R., Francis, D. D., Shanahan, J. F. and Schepers, J. S (2005). Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agronomy Journal, 97,106–112. | ||
|
آمار تعداد مشاهده مقاله: 546 تعداد دریافت فایل اصل مقاله: 454 |
||