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Ekmeklik Buğdayda Biyokütle Verimi: Ekim Sıklığının Etkisi ve NDVI Kullanılarak Tahmini

Yıl 2024, , 1148 - 1158, 17.09.2024

Ali Cevat Sönmez

https://doi.org/10.18016/ksutarimdoga.vi.1226330

Öz

Bu çalışmanın amacı, İç Anadolu Bölgesi'nde ekim sıklığı(ES) uygulamalarının BV'ye etkisini ve BV'nin kolayca tahmin edilmesinde normalize edilmiş bitki indeksi (NDVI) değerlerinin kullanımını belirlemektir. Tarla denemeleri 2012-2015 yılları arasında arka arkaya üç yıl süreyle yağmura bağımlı ve sulu koşullarda Eskişehir'de yapılmıştır. Altı adet kışlık buğday çeşidine dört farklı ekim sıklığı (Seyrek, Sıradan, Yüksek ve Çok Yüksek) uygulanmıştır. Biyokütle örnekleri çiçeklenme ve hasat dönemlerinde alınmıştır. NDVI değerleri çiçeklenme döneminde Green Seeker Handhold Sensor (GSHS) cihazı kullanılarak ölçülmüştür. Her iki koşulda da çiçeklenme dönemindeki NDVI değerleri ile hasat döneminde elde edilen BV’leri arasındaki korelasyon pozitif ve istatistiksel olarak önemli bulunmuştur (yağmura bağımlı koşullarda (R = 0,837), sulu koşullarda (R = 0,786)). Yüksek BV elde etmek için çeşitlerin yağışlı koşullarda Yüksek ES uygulamasıyla, sulu koşullarda Normal ES uygulamasıyla ekilmesi önerilir. Çeşitler arasında Alpu 2001 ve Harmankaya-99 çeşitlerinden her iki koşulda da yüksek verim alınmıştır. Ayrıca GSHS'nin BV tahmini için kullanılabilecek güvenilir bir araç olduğu belirlenmiştir.

Anahtar Kelimeler

Vejetasyon indeksi Korelasyon Triticum aestivum L. Biyokütle Tahmini Tohum sıklığı

Kaynakça

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  • Aisawi, K. A. B., Reynolds, M. P., Singh, R. P., & Foulkes, M. J. (2015). The physiological basis of the genetic progress in yield potential of CIMMYT spring wheat cultivars from 1966 to 2009. Crop Science, 55(4), 1749-1764. doi:10.2135/ cropsci2014.09.0601
  • Amanullah, Khan, A., Hussain, & Z., Jan, D. (2010). Performance of wheat cultivars sown at different seeding rates under drought-stress conditions. Archives of Agronomy and Soil Science, 56(1), 99-105. doi:10.1080/03650340.902897641
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  • Babar, M. A., Reynolds, M. P., Van Ginkel, M., Klatt, A. R., Raun, W. R., & Stone, M. L. (2006). Spectral reflectance to estimate genetic variation for in‐season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Science, 46(3), 1046-1057. doi:10.2135/cropsci2005.0211
  • Bhatta, M., Eskridge, K. M., Rose, D. J., Santra, D. K., Baenziger, P. S., & Regassa, T. (2017). Seeding rate, genotype, and topdressed nitrogen effects on yield and agronomic characteristics of winter wheat. Crop Science, 57(2), 951-963. doi:10.2135/cropsci2016.02.0103
  • Cabrera-Bosquet, L., Molero, G., Stellacci, A., Bort, J., Nogués, S., & Araus, J. (2011). NDVI is a potential tool for predicting biomass, plant nitrogen content, and growth in wheat genotypes subjected to different water and nitrogen conditions. Cereal Research Communications, 39(1), 147-159.
  • Carr, P. M., Horsley, R. D., & Poland, W. W. (2003). Tillage and seeding rate effects on wheat cultivars: I. Grain production. Crop Science, 43(1), 202-209.
  • Chandel, N. S., Tiwari, P. S., Singh, K. P., Jat, D., Gaikwad, B. B., Tripathi, H., & Golhani, K. (2019). Yield prediction in wheat (Triticum aestivum L.) using spectral reflectance indices. Curr. Sci, 116(2), 272.
  • Dai, J., Bean, B., Brown, B., Bruening, W., Edwards, J., Flowers, M., …& Wiersma, J. (2016). Harvest index and straw yield of five classes of wheat. Biomass and Bioenergy, 85, 223-227. doi:10.1016/j.biombioe.2015.12.023
  • Foulkes, M. J., Snape, J. W., Shearman, V. J., Reynolds, M. P., Gaju, O., & Sylvester-Bradley, R. (2007). Genetic progress in yield potential in wheat: recent advances and prospects. The Journal of Agricultural Science, 145(1), 17-29. doi:10.1017/S0021859607006740
  • Foulkes, M. J., Slafer, G. A., Davies, W. J., Berry, P. M., Sylvester-Bradley, R., Martre, P., ... & Reynolds, M. P. (2011). Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. Journal of Experimental Botany, 62(2), 469-486. doi:10.1093/jxb/erq300
  • Gündoğdu, K. S. (2018). Buğday ekili parsellerde NDVI değerlerinin konumsal ve zamana bağlı değişiminin belirlenmesi. Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi, 21(4), 492-499.
  • Gutiérrez-Rodríguez, M., Reynolds, M. P., Escalante-Estrada, J. A., & Rodríguez-González, M. T. (2004). Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions. Australian Journal of Agricultural Research, 55(11), 1139-1147. doi:10.1071/AR04214
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Biomass Yield in Bread Wheat: The Effect of Sowing Density and Predicting Using NDVI

Yıl 2024, , 1148 - 1158, 17.09.2024

Ali Cevat Sönmez

https://doi.org/10.18016/ksutarimdoga.vi.1226330

Öz

This is due to approaching the upper limits of the harvest index. The study aimed to determine the effect of sowing density (SD) practices on BY in the Central Anatolian Region and the use of normalized vegetation index (NDVI) values in estimating BY easily. Field trials were carried out for three consecutive years in rainfed and irrigated conditions in Eskişehir between 2012 and 2015. Four different SDs (Sparse, Ordinary, High, and Very High) were applied to six winter wheat cultivars. Biomass samples were taken during flowering and harvesting periods. NDVI values were measured using the Green Seeker Handhold Sensor (GSHS) tool during the flowering period. In both conditions, the correlation between the NDVI values during the flowering period and the biomass yields obtained during the harvesting period was found to be positive and significant (in rainfed conditions (R = 0.837), in irrigated conditions (R = 0.786)). To obtain high BY, it is recommended that to be sowed with High SD in rainfed conditions, and Ordinary SD practices in irrigated conditions. Considering the varieties, Alpu 2001 and Harmankaya-99 stand out from the others in terms of getting high biomass yield in both conditions. In addition, it was determined that the GSHS is a reliable tool that can be used for the estimation of BY.

Anahtar Kelimeler

Triticum aestivum L. Biomass estimation Seeding rate Vegetation Index Correlation

Destekleyen Kurum

The Republic of Türkiye Ministry of Agriculture and Forestry, General Directorate of Agricultural Research and Policy, Transitional Zone Agricultural Research Institute,

Kaynakça

  • Aharon, S., Fadida-Myers, A., Nashef, K., Ben-David, R., Lati, R. N., & Peleg, Z. (2021). Genetic improvement of wheat early vigor promotes weed competitiveness under the Mediterranean climate. Plant Science, 303, 110785. doi:10.1016/j.plantsci.2020.110785
  • Aisawi, K. A. B., Reynolds, M. P., Singh, R. P., & Foulkes, M. J. (2015). The physiological basis of the genetic progress in yield potential of CIMMYT spring wheat cultivars from 1966 to 2009. Crop Science, 55(4), 1749-1764. doi:10.2135/ cropsci2014.09.0601
  • Amanullah, Khan, A., Hussain, & Z., Jan, D. (2010). Performance of wheat cultivars sown at different seeding rates under drought-stress conditions. Archives of Agronomy and Soil Science, 56(1), 99-105. doi:10.1080/03650340.902897641
  • Anonymous. (2022). The world population is projected to reach 9.8 billion in 2050, and 11.2 billion in 2100. Retrieved from https://www.un.org/en/desa/ world population-projected-reach-98-billion-2050-and-112 billion-2100
  • Atkinson Amorim, J. G., Schreiber, L. V., de Souza, M. R. Q., Negreiros, M., Susin, A., Bredemeier, C., ... & Parraga, A. (2022). Biomass estimation of spring wheat with machine learning methods using UAV-based multispectral imaging. International Journal of Remote Sensing, 43(13), 4758-4773.
  • Babar, M. A., Reynolds, M. P., Van Ginkel, M., Klatt, A. R., Raun, W. R., & Stone, M. L. (2006). Spectral reflectance to estimate genetic variation for in‐season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Science, 46(3), 1046-1057. doi:10.2135/cropsci2005.0211
  • Bhatta, M., Eskridge, K. M., Rose, D. J., Santra, D. K., Baenziger, P. S., & Regassa, T. (2017). Seeding rate, genotype, and topdressed nitrogen effects on yield and agronomic characteristics of winter wheat. Crop Science, 57(2), 951-963. doi:10.2135/cropsci2016.02.0103
  • Cabrera-Bosquet, L., Molero, G., Stellacci, A., Bort, J., Nogués, S., & Araus, J. (2011). NDVI is a potential tool for predicting biomass, plant nitrogen content, and growth in wheat genotypes subjected to different water and nitrogen conditions. Cereal Research Communications, 39(1), 147-159.
  • Carr, P. M., Horsley, R. D., & Poland, W. W. (2003). Tillage and seeding rate effects on wheat cultivars: I. Grain production. Crop Science, 43(1), 202-209.
  • Chandel, N. S., Tiwari, P. S., Singh, K. P., Jat, D., Gaikwad, B. B., Tripathi, H., & Golhani, K. (2019). Yield prediction in wheat (Triticum aestivum L.) using spectral reflectance indices. Curr. Sci, 116(2), 272.
  • Dai, J., Bean, B., Brown, B., Bruening, W., Edwards, J., Flowers, M., …& Wiersma, J. (2016). Harvest index and straw yield of five classes of wheat. Biomass and Bioenergy, 85, 223-227. doi:10.1016/j.biombioe.2015.12.023
  • Foulkes, M. J., Snape, J. W., Shearman, V. J., Reynolds, M. P., Gaju, O., & Sylvester-Bradley, R. (2007). Genetic progress in yield potential in wheat: recent advances and prospects. The Journal of Agricultural Science, 145(1), 17-29. doi:10.1017/S0021859607006740
  • Foulkes, M. J., Slafer, G. A., Davies, W. J., Berry, P. M., Sylvester-Bradley, R., Martre, P., ... & Reynolds, M. P. (2011). Raising yield potential of wheat. III. Optimizing partitioning to grain while maintaining lodging resistance. Journal of Experimental Botany, 62(2), 469-486. doi:10.1093/jxb/erq300
  • Gündoğdu, K. S. (2018). Buğday ekili parsellerde NDVI değerlerinin konumsal ve zamana bağlı değişiminin belirlenmesi. Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi, 21(4), 492-499.
  • Gutiérrez-Rodríguez, M., Reynolds, M. P., Escalante-Estrada, J. A., & Rodríguez-González, M. T. (2004). Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions. Australian Journal of Agricultural Research, 55(11), 1139-1147. doi:10.1071/AR04214
  • Hu, C., Zheng, C., Sadras, V. O., Ding, M., Yang, X., & Zhang, S. (2018). Effect of straw mulch and seeding rate on the harvest index, yield, and water use efficiency of winter wheat. Scientific reports, 8(1), 1-8. doi:10.1038/s41598-018-26615-x
  • JMP. (2016). JMP Users Guide, Version 13.0.0, SAS Institute Inc., Cary, NC, USA.
  • Kara, R., & Akkaya, A. (2009). Kahramanmaraş yöresine ait yerel ekmeklik buğday genotiplerinin verim ve fizyolojik özellikler yönünden incelenmesi. Türk Tarım ve Doğa Bilimleri Dergisi, 7(4), 1186-1204.
  • Khan, A., Ahmad, A., Ali, W., Hussain, S., Ajayo, B. S., Raza, M. A., ...& Yang, W. (2020). Optimization of plant density and nitrogen regimes to mitigate lodging risk in wheat. Agronomy Journal, 112(4), 2535-2551. doi:10.1002/agj2.20211
  • Khan, T. S., & Mubeen, U. (2012). Wheat straw: A pragmatic overview. Curr. Res. J. Biol. Sci, 4(6), 673-675.
  • Lapidus, D., Salem, M. E., Beach, R. H., Zayed, S., & Ortiz-Monasterio, I. (2022). Greenhouse gas mitigation benefits and profitability of the GreenSeeker Handheld NDVI sensor: evidence from Mexico. Precision Agriculture, 23(6), 2388-2406.
  • Lovegrove, A., Pellny, T. K., Hassall, K. L., Plummer, A., Wood, A., Bellisai, A., ... & Shewry, P. R. (2020). Historical changes in the contents and compositions of fiber components and polar metabolites in white wheat flour. Scientific reports, 10(1), 1-9. doi:10.1038/s41598-020-62777-3
  • Ma, S. C., Wang, T. C., Guan, X. K., & Zhang, X. (2018). Effect of sowing time and seeding rate on yield components and water use efficiency of winter wheat by regulating the growth redundancy and physiological traits of root and shoot. Field Crops Research, 221, 166-174. doi:10.1016/j.fcr.2018.02.028
  • Menegat, A., & Nilsson, A. T. (2019). Interaction of preventive, cultural, and direct methods for integrated weed management in winter wheat. Agronomy, 9(9), 564.
  • Meng, J., Du, X., & Wu, B. (2013). Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation. International Journal of Digital Earth, 6(3), 203-218. doi:10.1080/17538947.2011.623189
  • Mitchell, P. L., & Sheehy, J. E. (2018). Potential yield of wheat in the United Kingdom: How to reach 20 t ha-1. Field crops research, 224, 115-125. doi:10.1016/j.fcr.2018.05.008
  • Molero, G., Joynson, R., Pinera‐Chavez, F. J., Gardiner, L. J., Rivera‐Amado, C., Hall, A., & Reynolds, M. P. (2019). Elucidating the genetic basis of biomass accumulation and radiation use efficiency in spring wheat and its role in yield potential. Plant biotechnology journal, 17(7), 1276-1288. doi:10.1111/pbi.13052
  • Morgounov, A., Gummadov, N., Belen, S., Kaya, Y., Keser, M., & Mursalova, J. (2014). Association of digital photo parameters and NDVI with winter wheat grain yield in variable environments. Turkish journal of agriculture and forestry, 38(5), 624-632. doi:10.3906/tar-1312-90
  • Morgounov, A. I., Ozdemir, F., Keser, M., Akin, B., Payne, T. S., & Braun, H. J. (2019). International Winter Wheat Improvement Program: history, activities, impact, and future. Front. Agr. Sci. Eng. 2019, 6(3), 240–250. doi:10.15302/J-FASE-2019261
  • Önder, O. (2007). Orta Anadolu kuru şartlarında yetiştirilen bazı ekmeklik buğday çeşitlerinin kardeşlenme dinamiğinin araştırılması (Tez No 179009). [Yüksek Lisans Tezi, Eskişehir Osmangazi Üniversitesi, Fen Bilimleri Enstitüsü Tarla Bitkileri Ana Bilim Dalı] Yükseköğretim Kurulu Ulusal Tez Merkezi
  • Özkan, M. (2020). Bingöl şartlarında farklı ekim sıklıklarında bazı ekmeklik buğday (Triticum aestivum. L) çeşitlerinin verim ve verim komponentlerinin belirlenmesi (Tez No 629037). [Yüksek Lisans Tezi, Bingöl Universitesi Fen Bilimleri Enstitüsü Tarla Bitkileri Ana Bilim Dalı] Yükseköğretim Kurulu Ulusal Tez Merkezi
  • Öztürk, İ. (2011). Ekmeklik buğday (Triticum aestivum L.) genotiplerinde kurağa dayanıklılığın karakterizasyonu ve kalite ile ilişkileri (Tez No 297713). [Doktora Tezi, Namık Kemal Üniversitesi Fen Bilimleri Enstitüsü Tarla Bitkileri Ana Bilim Dalı] Yükseköğretim Kurulu Ulusal Tez Merkezi
  • Ravindran, R., & Jaiswal, A. K. (2016). A comprehensive review on pre-treatment strategy for lignocellulosic food industry waste: challenges and opportunities. Bioresource Technology, 199, 92-102. doi:10.1016/j.biortech.2015.07.106
  • Reynolds, M., Foulkes, J., Furbank, R., Griffiths, S., King, J., Murchie, E., ...& Slafer, G. (2012). Achieving yield gains in wheat. Plant, cell & environment, 35(10), 1799-1823. doi:10.1111/j.1365-3040.2012.02588.x
  • Reynolds, M. P., Pask, A. J., Hoppitt, W. J., Sonder, K., Sukumaran, S., Molero, G., ... & Joshi, A. K. (2017). Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat. Euphytica, 213(11), 1-23. doi:10.1007/s10681-017-2040-z
  • Reynolds, M., Chapman, S., Crespo-Herrera, L., Molero, G., Mondal, S., Pequeno, D. N., ... & Sukumaran, S. (2020). Breeder-friendly phenotyping. Plant Science, 295, 110396. doi:10.1016/j.plantsci.2019.110396
  • Reynolds, M. P., Slafer, G. A., Foulkes, J. M., Griffiths, S., Murchie, E. H., Carmo-Silva, E., ... & Flavell, R. B. (2022). A wiring diagram to integrate physiological traits of wheat yield potential. Nature Food, 3(5), 318-324.
  • Sajjad, M. R., Rashid, M., Akram, M., Ahmad, M. J., Hussain, R., & Razzaq, A. (2009). Optimum seed rate of wheat in available soil moisture under rainfed conditions. Journal of Agricultural Research (03681157), 47(2), 143-151.
  • Savaşlı, E., Çekiç, C., Önder, O., Dayıoğlu, R., Kalaycı, & H. M. (2012). Evaluation of Some Bread Wheat Cultivars and Advanced Breeding Lines for Yield, Biomass and Vegetation Index International Journal of Agricultural and Natural Sciences, 5(2), 33-37.
  • Savaşlı, E., Önder, O., Cekic, C., Kalaycı, H. M., Dayıoğlu, R., Karaduman, Y., ... & Gezgin, S. (2021a). Orta Anadolu Kuru Şartlarında Ekmeklik Buğdayda Optik Sensöre Dayalı Mevsim İçi Azotlu Gübre Kalibrasyon Optimizasyonu. Kahramanmaraş Sütçü İmam Üniversitesi Tarım ve Doğa Dergisi, 24(1), 130-140.
  • Savaşlı, E., Önder, O., Dayıoğlu, R., Özen, D., Karaduman Y., Özdemir, S., ... & Özsayın, M. (2021b). Ekmeklik Buğdayda Optik Sensör ile Azotlu Gübre Tavsiyesi. Yuzuncu Yıl University Journal of Agricultural Sciences, 31(2), 453-465.
  • Savaşlı, E., Önder, O., Dayıoğlu, R., Belen, S., Çakmak, M., Çekiç, C., ... & Erşahin, S. (2023). Estimating grain and biomass yield of bread wheat genotypes by optical sensors. European Journal of Agronomy, 150, 126923.
  • Shah, F., Coulter, J. A., Ye, C., & Wu, W. (2020). Yield penalty due to delayed sowing of winter wheat and the mitigatory role of increased seeding rate. European Journal of Agronomy, 119, 126120.
  • Shewry, P. R. (2009). Wheat. Journal of experimental botany, 60(6), 1537-1553.
  • Soomro, U. A., Rahman, M. U., Odhano, E. A., Gul, S., & Tareen, A. Q. (2009). Effects of sowing method and seed rate on growth and yield of wheat (Triticum aestivum). World Journal of Agricultural Sciences, 5(2), 159-162. Student, (1908). The probable error of a mean. Biometrika, 1-25.
  • Townsend, T. J., Sparkes, D. L., Ramsden, J., Glithero N. J., & Wilson, P. (2018). Wheat straw availability for bioenergy in England. Energy policy, 122, 349-357. doi:10.1016/j.enpol.2018.07.053
  • Trentin, C., Bredemeier, C., Vian, A. L., Drum, M. A., & Santos, F. L. D. (2021). Biomass production and wheat grain yield and its relationship with NDVI as a function of nitrogen availability. Revista Brasileira de Ciências Agrárias (Agrária), 16(4), e34, 1-7 p.
  • Walsh, O. S., Marshall, J., Jackson, C., Nambi, E., Shafian, S., Jayawardena, D. M., ... & McClintick‐Chess, J. R. (2022). Wheat yield and protein estimation with handheld and UAV‐based reflectance measurements. Agrosystems, Geosciences & Environment, 5(4), e20309.
  • Walter, J. D., Edwards, J., McDonald, G., & Kuchel, H. (2019). Estimating biomass and canopy height with LiDAR for field crop breeding. Frontiers in plant science, 10, 1145.
  • Wu, Yue, Nianxun Xi, Jacob Weiner, and Da-Yong Zhang. (2021). Differences in weed suppression between two modern and two old wheat cultivars at different sowing densities. Agronomy 2021, 11(2), 253. doi:10.3390/agronomy11020253
  • Zadoks, J. C., Chang, T. T., & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed Research, 14(6), 415-421.
  • Zecha, C. W., Peteinatos, G. G., Link, J., & Claupein, W. (2018). Utilization of ground and airborne optical sensors for nitrogen level identification and yield prediction in wheat. Agriculture, 8(6), 79.
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ziraat, Veterinerlik ve Gıda Bilimleri
Bölüm ARAŞTIRMA MAKALESİ (Research Article)
Yazarlar

Ali Cevat Sönmez 0000-0002-9818-2660

Erken Görünüm Tarihi 2 Temmuz 2024
Yayımlanma Tarihi 17 Eylül 2024
Gönderilme Tarihi 29 Aralık 2022
Kabul Tarihi 12 Aralık 2023
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Sönmez, A. C. (2024). Biomass Yield in Bread Wheat: The Effect of Sowing Density and Predicting Using NDVI. Kahramanmaraş Sütçü İmam Üniversitesi Tarım Ve Doğa Dergisi, 27(5), 1148-1158. https://doi.org/10.18016/ksutarimdoga.vi.1226330

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2022-JCI = 0.170

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