Research Article
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Year 2025, Volume: 9 Issue: 1, 115 - 122, 17.03.2025
https://doi.org/10.31015/2025.1.14

Abstract

References

  • Aparicio, N., Villegas, D., Araus, J. L., Casadesus, J., Royo, C. (2002). Relationship between growth traits and spectral vegetation indices in durum wheat. Crop science, 42 (5), 1547-1555. https://doi.org/10.2135/cropsci2002.1547
  • Ashourloo, D., Mobasheri, M. R., Huete, A. (2014). Evaluating the effect of different wheat rust disease symptoms on vegetation indices using hyperspectral measurements. Remote Sensing, 6 (6), 5107-5123. https://doi.org/10.3390/rs6065107
  • Cooper, M., Messina, C. D., Podlich, D., Totir, L. R., Baumgarten, A., Hausmann, N. J., Graham, G. (2014). Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction. Crop and Pasture Science, 65 (4), 311-336. https://doi.org/10.1071/CP14007
  • Giunta, F., Motzo, R., Deidda, M. (2002). SPAD readings and associated leaf traits in durum wheat, barley and triticale cultivars. Euphytica, 125, 197-205. https://doi.org/10.1071/CP14007
  • Grosse-Heilmann, M., Cristiano, E., Deidda, R., Viola, F. (2024). Durum wheat productivity today and tomorrow: A review of influencing factors and climate change effects. Resources Environment and Sustainability, 17, 100170. https://doi.org/10.1016/j.resenv.2024.100170
  • Hassan, M. A., Yang, M., Rasheed, A., Yang, G., Reynolds, M., Xia, X., He, Z. (2019). A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform. Plant science, 282, 95-103. https://doi.org/10.1016/j.plantsci.2018.10.022
  • Jackson, P., Robertson, M., Cooper, M., Hammer, G. (1996). The role of physiological understanding in plant breeding; from a breeding perspective. Field Crops Research, 49 (1), 11-37. https://doi.org/10.1016/S0378-4290(96)01012-X
  • Kızılgeçi, F., Yıldırım, M., Akıncı, C., Albayrak, Ö., Sesiz, U., Tazebay, N. (2018). Evaluation of relationships between yield and yield components with physiological parameters in barley. DUFED, 7(2), 61-66.
  • Kizilgeci, F., Akıncı, C., Yıldırım, M. (2019). Improving grain yield, protein ratio and nitrogen use efficiency of durum wheat (Triticum durum Desf.) hybrids using spad meter as a selection criterion. International Journal of Agriculture Environment and Food Sciences, 3 (3), 112-120. https://doi.org/10.31015/jaefs.2019.3.1
  • Kizilgeci, F. (2020). Diallel analysis of spad, yield component and nitrogen use efficiency of some bread wheat genotypes under low and high nitrogen levels. Fresenius Environmental Bulletin, 29 (8), 7071-7080. https://doi.org/10.5601/jelem.2022.27.3.2241
  • Kizilgeci, F., Yıldırım, M., Islam, M. S., Ratnasekera, D., Iqbal, M. A., Sabagh, A. E. (2021). Normalized difference vegetation index and chlorophyll content for precision nitrogen management in durum wheat cultivars under semi-arid conditions. Sustainability, 13 (7), 3725. https://doi.org/10.3390/su13073725
  • Kızılgeçi, F., Cebeli, Z. (2024). Proximal canopy sensing of twenty-two bread wheat genotypes for nutritional quality, yield attributes and grain yield under Mediterranean climate. International Journal of Agriculture Environment and Food Sciences, 8 (2), 347-358. https://doi.org/10.31015/jaefs.2024.2.10
  • Le Bail, M., Jeuffroy, M. H., Bouchard, C., Barbottin, A. (2005). Is it possible to forecast the grain quality and yield of different varieties of winter wheat from Minolta SPAD meter measurements? European Journal of Agronomy, 23 (4), 379-391. https://doi.org/10.1016/j.eja.2005.02.003
  • Martins, T., Barros, A. N., Rosa, E., Antunes, L. (2023). Enhancing health benefits through chlorophylls and chlorophyll-rich agro-food: A comprehensive review. Molecules, 28 (14), 5344. https://doi.org/10.3390/molecules28145344
  • Mekliche, A., Hanifi-Mekliche, L., Aidaoui, A., Gate, P., Bouthier, A., Monneveux, P. H. (2015). Grain yield and its components study and their association with normalized difference vegetation index (NDVI) under terminal water deficit and well-irrigated conditions in wheat (Triticum durum Desf. and Triticum aestivum L.). African Journal of Biotechnology, 14 (26), 2142-2148. https://doi.org/10.5897/AJB2015.14535
  • Mohammadi, R., Cheghamirza, K., Geravandi, M., Abbasi, S. (2022). Assessment of genetic and agro-physiological diversity in a global durum wheat germplasm. Cereal Research Communications, 50 (1), 117-126. https://doi.org/10.1007/s42976-021-00143-3
  • Reynolds, M., Langridge, P. (2016). Physiological breeding. Current opinion in plant biology, 31, 162-171. https://doi.org/10.1016/j.pbi.2016.04.005
  • Sinha, S. K., Swaminathan, M. S. (1984). New parameters and selection criteria in plant breeding. Crop Breeding. A Contemporary Basis, 1-31. https://doi.org/10.1016/B978-0-08-025505-7.50004-X
  • Sun, H., Li, M., Zhang, Q. (2022). Crop Sensing in Precision Agriculture. In Soil and Crop Sensing for Precision Crop Production Cham: Springer International Publishing, 251-293. https://doi.org/10.1007/978-3-030-70432-2_8
  • Yakushev, V. P., Kanash, E. V., Rusakov, D. V., Yakushev, V. V., Blokhina, S. Y., Petrushin, A. F., Mitrofanov, E. P. (2022). Correlation dependences between crop reflection indices, grain yield and optical characteristics of wheat leaves at different nitrogen level and seeding density. Sel’skokhozyaistvennaya biologiya, 57(1), 98-112. https://doi.org/10.15389/agrobiology.2022.1.98eng
  • Yıldırım, M., Kılıç, H., Kendal, E., Karahan, T. (2011). Applicability of chlorophyll meter readings as yield predictor in durum wheat. Journal of Plant Nutrition, 34 (2), 151-164. https://doi.org/10.1080/01904167.2011.533319
  • Yıldırım, M., Koç, M., Akıncı, C., Barutçular, C., (2013). Variations in morphological and physiological traits of bread wheat diallel crosses under timely and late sowing conditions. Field Crops Research, 140: 9–17. https://doi.org/10.1016/j.fcr.2012.10.001

Non-Destructive chlorophyll meters: a comparison of three types of meters for grain yield estimation of durum wheat under semi-arid environments

Year 2025, Volume: 9 Issue: 1, 115 - 122, 17.03.2025
https://doi.org/10.31015/2025.1.14

Abstract

Optimizing management practices to maximize crop yield and efficiency necessitates real-time monitoring of plant growth throughout the growing season. Utilizing spectral indices, such as normalized difference vegetation index, SPAD chlorophyll meter readings, and the CM-1000 chlorophyll meter, can provide quantitative data to aid in making informed management decisions. This study investigated the relationships between spectral indices (NDVI, SPAD, CM-1000) and grain yield in five durum wheat genotypes under semi-arid conditions. Spectral indices were taken at three growth stages: heading, anthesis, and maturity. Our findings revealed significant variations in spectral reflectance values among the genotypes and across growth stages. NDVI values were highest during the early growth stages and declined towards maturity. SPAD values also exhibited a similar trend, peaking at heading and anthesis. Chlorophyll content, as measured by SPAD readings, varied across growth stages, with different genotypes exhibiting peak chlorophyll content at different times. CM-1000 measurements showed significant differences among genotypes at all stages, with 'Fırat 93' and 'Hasanbey' generally exhibiting higher chlorophyll content. Correlation analysis revealed significant positive relationships between NDVI values at different stages, as well as between CM-1000 measurements and grain yield. Conversely, SPAD values showed a negative correlation with grain yield. These findings suggest that CM-1000 measurements could be a valuable tool for selecting high-yielding durum wheat genotypes under semi-arid conditions.

References

  • Aparicio, N., Villegas, D., Araus, J. L., Casadesus, J., Royo, C. (2002). Relationship between growth traits and spectral vegetation indices in durum wheat. Crop science, 42 (5), 1547-1555. https://doi.org/10.2135/cropsci2002.1547
  • Ashourloo, D., Mobasheri, M. R., Huete, A. (2014). Evaluating the effect of different wheat rust disease symptoms on vegetation indices using hyperspectral measurements. Remote Sensing, 6 (6), 5107-5123. https://doi.org/10.3390/rs6065107
  • Cooper, M., Messina, C. D., Podlich, D., Totir, L. R., Baumgarten, A., Hausmann, N. J., Graham, G. (2014). Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction. Crop and Pasture Science, 65 (4), 311-336. https://doi.org/10.1071/CP14007
  • Giunta, F., Motzo, R., Deidda, M. (2002). SPAD readings and associated leaf traits in durum wheat, barley and triticale cultivars. Euphytica, 125, 197-205. https://doi.org/10.1071/CP14007
  • Grosse-Heilmann, M., Cristiano, E., Deidda, R., Viola, F. (2024). Durum wheat productivity today and tomorrow: A review of influencing factors and climate change effects. Resources Environment and Sustainability, 17, 100170. https://doi.org/10.1016/j.resenv.2024.100170
  • Hassan, M. A., Yang, M., Rasheed, A., Yang, G., Reynolds, M., Xia, X., He, Z. (2019). A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform. Plant science, 282, 95-103. https://doi.org/10.1016/j.plantsci.2018.10.022
  • Jackson, P., Robertson, M., Cooper, M., Hammer, G. (1996). The role of physiological understanding in plant breeding; from a breeding perspective. Field Crops Research, 49 (1), 11-37. https://doi.org/10.1016/S0378-4290(96)01012-X
  • Kızılgeçi, F., Yıldırım, M., Akıncı, C., Albayrak, Ö., Sesiz, U., Tazebay, N. (2018). Evaluation of relationships between yield and yield components with physiological parameters in barley. DUFED, 7(2), 61-66.
  • Kizilgeci, F., Akıncı, C., Yıldırım, M. (2019). Improving grain yield, protein ratio and nitrogen use efficiency of durum wheat (Triticum durum Desf.) hybrids using spad meter as a selection criterion. International Journal of Agriculture Environment and Food Sciences, 3 (3), 112-120. https://doi.org/10.31015/jaefs.2019.3.1
  • Kizilgeci, F. (2020). Diallel analysis of spad, yield component and nitrogen use efficiency of some bread wheat genotypes under low and high nitrogen levels. Fresenius Environmental Bulletin, 29 (8), 7071-7080. https://doi.org/10.5601/jelem.2022.27.3.2241
  • Kizilgeci, F., Yıldırım, M., Islam, M. S., Ratnasekera, D., Iqbal, M. A., Sabagh, A. E. (2021). Normalized difference vegetation index and chlorophyll content for precision nitrogen management in durum wheat cultivars under semi-arid conditions. Sustainability, 13 (7), 3725. https://doi.org/10.3390/su13073725
  • Kızılgeçi, F., Cebeli, Z. (2024). Proximal canopy sensing of twenty-two bread wheat genotypes for nutritional quality, yield attributes and grain yield under Mediterranean climate. International Journal of Agriculture Environment and Food Sciences, 8 (2), 347-358. https://doi.org/10.31015/jaefs.2024.2.10
  • Le Bail, M., Jeuffroy, M. H., Bouchard, C., Barbottin, A. (2005). Is it possible to forecast the grain quality and yield of different varieties of winter wheat from Minolta SPAD meter measurements? European Journal of Agronomy, 23 (4), 379-391. https://doi.org/10.1016/j.eja.2005.02.003
  • Martins, T., Barros, A. N., Rosa, E., Antunes, L. (2023). Enhancing health benefits through chlorophylls and chlorophyll-rich agro-food: A comprehensive review. Molecules, 28 (14), 5344. https://doi.org/10.3390/molecules28145344
  • Mekliche, A., Hanifi-Mekliche, L., Aidaoui, A., Gate, P., Bouthier, A., Monneveux, P. H. (2015). Grain yield and its components study and their association with normalized difference vegetation index (NDVI) under terminal water deficit and well-irrigated conditions in wheat (Triticum durum Desf. and Triticum aestivum L.). African Journal of Biotechnology, 14 (26), 2142-2148. https://doi.org/10.5897/AJB2015.14535
  • Mohammadi, R., Cheghamirza, K., Geravandi, M., Abbasi, S. (2022). Assessment of genetic and agro-physiological diversity in a global durum wheat germplasm. Cereal Research Communications, 50 (1), 117-126. https://doi.org/10.1007/s42976-021-00143-3
  • Reynolds, M., Langridge, P. (2016). Physiological breeding. Current opinion in plant biology, 31, 162-171. https://doi.org/10.1016/j.pbi.2016.04.005
  • Sinha, S. K., Swaminathan, M. S. (1984). New parameters and selection criteria in plant breeding. Crop Breeding. A Contemporary Basis, 1-31. https://doi.org/10.1016/B978-0-08-025505-7.50004-X
  • Sun, H., Li, M., Zhang, Q. (2022). Crop Sensing in Precision Agriculture. In Soil and Crop Sensing for Precision Crop Production Cham: Springer International Publishing, 251-293. https://doi.org/10.1007/978-3-030-70432-2_8
  • Yakushev, V. P., Kanash, E. V., Rusakov, D. V., Yakushev, V. V., Blokhina, S. Y., Petrushin, A. F., Mitrofanov, E. P. (2022). Correlation dependences between crop reflection indices, grain yield and optical characteristics of wheat leaves at different nitrogen level and seeding density. Sel’skokhozyaistvennaya biologiya, 57(1), 98-112. https://doi.org/10.15389/agrobiology.2022.1.98eng
  • Yıldırım, M., Kılıç, H., Kendal, E., Karahan, T. (2011). Applicability of chlorophyll meter readings as yield predictor in durum wheat. Journal of Plant Nutrition, 34 (2), 151-164. https://doi.org/10.1080/01904167.2011.533319
  • Yıldırım, M., Koç, M., Akıncı, C., Barutçular, C., (2013). Variations in morphological and physiological traits of bread wheat diallel crosses under timely and late sowing conditions. Field Crops Research, 140: 9–17. https://doi.org/10.1016/j.fcr.2012.10.001
There are 22 citations in total.

Details

Primary Language English
Subjects Cereals and Legumes
Journal Section Research Articles
Authors

Ferhat Kızılgeçi 0000-0002-7884-5463

Negar Ebrahim Pour Mokhtari 0000-0002-2307-5756

Seval Eliş 0000-0001-6708-5238

Remzi Özkan 0000-0002-6457-5802

Merve Bayhan 0000-0002-3220-4548

Mehmet Yıldırım 0000-0003-2421-4399

Publication Date March 17, 2025
Submission Date January 27, 2025
Acceptance Date March 5, 2025
Published in Issue Year 2025 Volume: 9 Issue: 1

Cite

APA Kızılgeçi, F., Ebrahim Pour Mokhtari, N., Eliş, S., Özkan, R., et al. (2025). Non-Destructive chlorophyll meters: a comparison of three types of meters for grain yield estimation of durum wheat under semi-arid environments. International Journal of Agriculture Environment and Food Sciences, 9(1), 115-122. https://doi.org/10.31015/2025.1.14


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