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Journals / Anadolu Tarım Bilimleri Dergisi / 2026 / Cilt: 41

Distribution of Black Point Infection on Wheat in Relation to Precipitation and Topographic Features Using Geographic Information Systems

Coğrafi Bilgi Sistemleri Kullanılarak Buğdayda Embriyo Kararması Enfeksiyonunun Yağış ve Topoğrafik Özelliklere Göre Dağılımı

Ömer Faruk Karaca(Yozgat Bozok Üniversitesi)0000-0002-6302-9738
Ali Endes(YOZGAT BOZOK UNIVERSITY)0000-0003-4815-5864
Bekir Aktaş(YOZGAT BOZOK UNIVERSITY)0000-0002-8431-4554
Pages
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Publication Date
2026-06-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Regarding the black point incidence, it was found that the north, east, and west directions from the major directions differed statistically significantly from the south directions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Environmental factors and geographical features are of great importance in the disease incidence and severity of black point.
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Key Findings & Data:It was defined that there were statistically significant differences between aspect, soil groups, lithology, precipitation and black point.
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Conclusion & Impact:Regarding the black point incidence, it was found that the north, east, and west directions from the major directions differed statistically significantly from the south directions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:CBS · Çevresel Koşullar · Sayısal Yükseklik Modeli

Abstract

Environmental factors and geographical features are of great importance in the disease incidence and severity of black point. Geographic Information System (GIS), Expert System and Artificial Neural Network are among the techniques recently used to guide producers in preventing wheat diseases and harmful insects. In this study, it was aimed to determine the effect of precipitation and topographic features such as aspect, slope, digital elevation model (DEM), lithology classes and soil groups on the black point incidence formation in wheat production areas in Yerköy (Yozgat) and Çiçekdağı (Kırşehir) districts with the help of GIS. It was defined that there were statistically significant differences between aspect, soil groups, lithology, precipitation and black point. In contrast, no significant difference was found in DEM and slope degree. A statistically significant difference was found between lithosol type soils and black point among soil groups, and an increase in the incidence of infection occurred in these types of soils. In terms of precipitation amount, 201-300 mm and 301-400 mm precipitation ranges had a statistically significant difference from the 401-500 mm precipitation range. Regarding the black point incidence, it was found that the north, east, and west directions from the major directions differed statistically significantly from the south directions. More attention should be paid to cultivation techniques against black point in wheat cultivation, especially in areas with such geographical features.

Özet

Çevresel faktörler ve coğrafi özellikler, embriyo kararması hastalığının görülme sıklığı ve şiddetinde büyük öneme sahiptir. Coğrafi Bilgi Sistemi (CBS), Uzman Sistem ve Yapay Sinir Ağı, son zamanlarda üreticilere buğday hastalıkları ve zararlı böcekleri önlemede rehberlik etmek için kullanılan teknikler arasındadır. Bu çalışmada, Yerköy (Yozgat) ve Çiçekdağı (Kırşehir) ilçelerindeki buğday üretim alanlarında kara nokta görülme sıklığı oluşumu üzerine yağış ve bakı, eğim, sayısal yükseklik modeli (DEM), litoloji sınıfları ve toprak grupları gibi topoğrafik özelliklerin etkisinin CBS yardımıyla belirlenmesi amaçlanmıştır. Bakı, toprak grupları, litoloji, yağış ve embriyo kararması arasında istatistiksel olarak anlamlı farklılıklar olduğu belirlenmiştir. Buna karşılık, DEM ve eğim derecesinde anlamlı bir fark bulunamamıştır. Litosol tipi topraklar ile toprak grupları arasında embriyo kararması arasında istatistiksel olarak anlamlı bir fark bulunmuş ve bu tip topraklarda enfeksiyon görülme sıklığında artış meydana gelmiştir. Yağış miktarı açısından, 201-300 mm ve 301-400 mm yağış aralıkları, 401-500 mm yağış aralığından istatistiksel olarak anlamlı bir fark göstermiştir. Embriyo kararması görülme sıklığı açısından ise, ana yönlerden kuzey, doğu ve batı yönlerinin güney yönlerinden istatistiksel olarak anlamlı bir şekilde farklı olduğu bulunmuştur. Özellikle bu tür coğrafi özelliklere sahip alanlarda buğday yetiştiriciliğinde embriyo kararmasına karşı yetiştirme tekniklerine daha fazla dikkat edilmelidir.

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Cite This Article

Karaca, Ö. F., Endes, A., Aktaş, B. (2026). Distribution of Black Point Infection on Wheat in Relation to Precipitation and Topographic Features Using Geographic Information Systems. Anadolu Tarım Bilimleri Dergisi, Cilt: 41. https://doi.org/10.7161/omuanajas.1761061

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References (93)

  1. Agrios,G.N. (2005). Plant pathology. Elsevier Academic Press, 5th ed, UK, London
  2. Aktaş, B., & Endes, A., 2025. Reaction of bread wheat cultivars to black point and its inheritance in segregating F4 and F5 progenies. Journal of Crop Health, 77:1-12. https://doi.org/10.1007/s10343-024-01105-5.
  3. Anonymous, 2025. Climate. Available at https://tr.climate-data.org/asya/tuerkiye/yozgat/yerkoey-8564/ (Accessed Date:15 April 2025)
  4. Baker, R.H.A., Sansford, C.E., Jarvis, C.H., Cannon, R.J.C., MacLeod, A., Walters, K.F.A., 2000. The role of climatic mapping in predicting the potential geographical distribution of non-indigenous pests under current and future climates. Agric. Ecosyst. Environ., 82:57-71. https://doi.org/10.1016/S0167-8809(00)00216-4.
  5. Başayiğit, L., Şenol, H., 2008. The Determinability of high fruit growing potential areas in geographic information systems environment and control with remote sensing method. Süleyman Demirel University Journal of the Faculty of Agriculture 3(1):1-8.
  6. Bebber, D.P., 2015. Range-expanding pests and pathogens in a warming world. Annu. Rev. Phytopathol. 53:335-356. https://doi.org/10.1146/annurev-phyto-080614-120207.
  7. Bestelmeyer, B.T., Marcillo, G., McCord, S.E., Mirsky, S.B., Boglen, G.E., Neven, L.G., Peters, D.C., Sohoulande, Djebou, D.C., Wakie, T., 2020. Scaling up agricultural research with artifcial intelligence. IEEE IT Profess., 22:32-38. https://doi.org/10.1109/MITP.2020.2986062.
  8. Bolstad, P., 2005. GIS fundamentals, a first text on geographic information systems. White Bear Lake, 2nd edition, MN: Eider Press,
  9. Bhunia, G., Shit, P., Chattopadhyay, R., 2018. Assessment of spatial variability of soil properties using geostatistical approach of lateritc soil (West Bengal, India). Annals of Agrarian Science, 16:436-443.
  10. Chen, W., Modi, D., Picot, A., 2023. Soil and phytomicrobiome for plant disease suppression and management under climate change: A review. Plants, 12:2736. https://doi.org/10.3390/plants12142736.
  11. Conner, R., Thomas, J., 1985. Genetic variation and screening techniques for resistance to black point in soft white spring wheat. Can. J. Plant Pathol., 7:402-407. http://dx.doi.org/10.1080/07060668509501669.
  12. Conner, R., Carefoot, J., Bole, J., Kozub, G., 1992. The effect of nitrogen fertilizer and irrigation on black point incidence in soft white spring wheat. Plant Soil, 140:41-47. https://doi.org/10.1007/BF00012805.
  13. CORINE, 2025. Coordination of Information on the Environment. Available at https://land.copernicus.eu/en/products/corine-land-cover/clc2018 (Accessed Date: 24 April 2025)
  14. Cotuna, O., Paraschivu, M., Sărăţeanu, V., Carmen, D., & Rechitean, I., 2020. Research regarding the identification of the fungi associated with “black point” disease in some winter wheat varieties from Banatului Plain (Western Romania). Life Science and Sustainable Development, 1:25-31. https://doi.org/10.58509/LSSD.V1I2.29.
  15. Cromey, M., Mulholland, R., 1988. Black point of wheat: fungal associations, cultivar susceptibility and effects on grain weight and germination. N.Z.J. Agric. Res., 31:51-55. https://doi.org/10.1080/00288233.1988.10421363.
  16. Delgado, J.A., Short, N.M.Jr, Roberts, D.P., Vandenberg, B., 2019. Big data analysis for sustainable agriculture on a geospatial cloud framework. Front Sustain Food Syst., 3:54. https://doi. org/10.3389/fsufs.2019.00054.
  17. Delgado-Baquerizo, M., Guerra, C.A., Cano-Díaz, C., Egidi, E., Wang, J.T., Eisenhauer, N., Singh, B.K., Maestre, F.T., 2020. The proportion of soil-borne pathogens increases with warming at the global scale. Nat. Clim. Change, 10:550-554. https://doi.org/10.1038/s41558-020-0759-3.
  18. Demirci, A., 2008. GIS for teachers: Geographic information systems. Fatih University Publications, No: 41, İstanbul.
  19. Desclaux, D., 2000. Environmental conditions inducing black-point symptoms in durum wheat. In: Royo, C., Nachit, M., Di Fonzo, N., Araus, J.L. (Eds.). Durum Wheat Improvement in the Mediterranean Region: New Challenges; CIHEAM, Zaragoza, p 501-503.
  20. Donatelli, M., Magarey, R.D., Bregaglio, S., Willocquet, L., Whish, J.P.M., Savary, S., 2017. Modelling the impacts of pests and diseases on agricultural systems. Agric Syst., 155:213-224. doi: 10.1016/j.agsy.2017.01.019. PMID: 28701814; PMCID: PMC5485649.
  21. Dong, Y., Xu, F., Liu, L., Du, X., Ye, H., Zhu, Y., Huang, W., 2019. Monitoring and forecasting for disease and pest in crop based on WebGIS system. In Proceeding of 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) 1-5, Istanbul, Turkey.
  22. EarthExplorer (2025). US Geology Survey. Available at https://earthexplorer.usgs.gov (Accessed Date: 06 May 2025)
  23. El-Gremi, S., Draz, I., Youssef, W., 2017. Biological control of pathogens associated with kernel black point disease of wheat. Crop Protect., 91:13-19. https://doi.org/10.1016/j.cropro.2016.08.034.
  24. Etterson, J.R., Shaw, R.G., 2001. Constraint to adaptive evolution in response to global warming. Science, 294:151-154.
  25. Eymen, U., 2007. Data Analysis with SPSS 15.0, Statistical Center Publication House.
  26. FAO/UNESCO, 1974. FAO - Unesco Soil Map of the World. Unesco, Paris.
  27. FAO/UNESCO, 2025. Soil Map of the World. Available at https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/faounesco-soil-map-of-the-world/en/ (Accessed Date: 28 April 2025)
  28. Fernandez, M.R., Clarke, J.M., Depauw, R.M., Irvine, R.B., Knox, R.E., 2000. Black point reaction of durum and common wheat cultivars grown under irrigation in southern Saskatchewan. Plant Dis., 84(8):892-894. doi: 10.1094/PDIS.2000.84.8.892. PMID: 30832144.
  29. Fernandez, M., Conner, R.L., 2011. Black point and smudge in wheat. Prairie Soils & Crops Journal, 4:158-164.
  30. Fietz, T.E., Miller, B.C., Pan, W.L., 1994. Winter wheat yield and grain protein across varied landscape positions. Agronomy Journal, 86:1026e1032. https://doi.org/10.2134/agronj1994.00021962008600060018x.
  31. Fitzpatrick, C., Maguire, D., 2000. GIS in schools: Infrastructure, methodology and role - GIS: A Source book for schools. Taylor & Francis.
  32. Garrett, K.A., Nita, M., De Wolf E.D., Esker, P.D., Gomez-Montano, L., Sparks, A.H., 2021. Plant pathogens as indicators of climate change In: Letcher, T.M. (Ed.), Climate Change. Elsevier, p. 499-513, Amsterdam, Netherlands. Gebbers, R., Adamchuk, V.I., 2010. Precision agriculture and food security. Science, 327:828-831. https://doi.org/10.1126/science.1183899.
  33. George, D., Mallery, M., 2010. SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update:Pearson. 10th ed. Boston.
  34. GLIM, 2025. Global Lithological Map. Available at https://www.geo.uni-hamburg.de/en/geologie/forschung/aquatische-geochemie/glim.html (Accessed Date: 02 May 2025)
  35. Godwin, R.J., Miller, P.C.H., 2003. A review of the technologies for mapping within-field variability. Biosystems Engineering, 84:393e407. https://doi.org/10.1016/S1537-5110(02)00283-0.
  36. Guo, W., Maas, S.J., Bronson, K.F., 2012. Relationship between cotton yield and soil electrical conductivity, topography, and Landsat imagery. Precision Agriculture, 13:678e692. https://doi.org/10.1007/s11119-012-9277-2.
  37. Haggag, W., Ali, R., Al-Ansary, N., 2023. Geographic information systems and remote sensing: Innovativetools for plant health. International Journal of Agricultural Technology, 19:2449-2464.
  38. Halliday, F.W., Jalo, M., Laine, A.L., 2021. The effect of host community functional traits on plant disease risk varies along an elevational gradient. eLife, 10:e67340. doi: 10.7554/eLife.67340. PMID: 33983120; PMCID: PMC8208817.
  39. HGM, 2025. Turkish Administrative Border. Available at https://www.harita.gov.tr/urun/turkiye-mulki-idare-sinirlari/232, (Accessed Date: 29 April 2025)
  40. Huber, L., Gillespie, T.J., 1992. Modeling leaf wetness in relation to plant disease epidemiology. Annu. Rev. Phytopathology, 30:553-577. https://doi.org/10.1146/annurev.py.30.090192.003005.
  41. Iqbal, J., Read, J.J., Thomasson, A.J., Jenkins, J.N., 2005. Relationships between soilelandscape and dryland cotton lint yield. Soil Science Society of America Journal, 69(3):872e882. https://doi.org/10.2136/sssaj2004.0178.
  42. Janssen, S.J.C., Porter, C.H., Moore, A.D., Athanasiadis, I.N., Foster, I., Jones, J.W., Antle, J.M., 2017. Towards a new generation of agricultural system data, models, and knowledge products: information and communication technology. Agric Sys., 155:200-212. https://doi.org/10.1016/j.agsy.2016.09.017.
  43. Jowkin, V., Schoenau, J.J., 1998. Impact of tillage and landscape position on nitrogen availability and yield of spring wheat in the Brown soil zone in southwestern Saskatchewan. Canadian Journal of Soil Science, 78(3):563e572. https://doi.org/10.4141/s97-065.
  44. Karaca, Ö.F., 2024. Determination of topographic wetness index (TWI) of Yozgat province using geographic information systems. Bozok Journal of Engineering and Architecture (BJEA), 3(2):87-98. https://doi.org/10.70700/bjea.1576651.
  45. Khani, M., Cheong, J., Mrva, K., Mares, D., 2018. Wheat black point: Role of environment and genotype. Journal of Cereal Science, 82:25-33. https://doi.org/10.1016/j.jcs.2018.04.012.
  46. Kosmas, C.S., Danalatos, N.G., Moustakas, N., Tsatiris, B., Kallianou, C., Yassoglou, N., 1993. The impacts of parent material and landscape position on drought and biomass production of wheat under semi-arid conditions. Soil Technology, 6(4):337e349. https://doi.org/10.1016/0933-3630(93)90024-9.
  47. Kravchenko, A.N., Bullock, D.G., 2000. Correlation of corn and soybean grain yield with topography and soil properties. Agronomy Journal, 92(1):75e83. https://doi.org/10.2134/agronj2000.92175x.
  48. Lalic, B., Jankovic, D., Dekic, L.J., Eitzinger, J., Sremac, A.F., Pacher, B., 2017. Testing the effectiveness of monthly forecasting in agricultural meteorology: Winter wheat phenology dynamics. IOP Conf. Ser.: Earth Environ. Sci., 57:12002. doi: 10.1088/1755-1315/57/1/012002.
  49. Lamichhane, J.R., Barbetti, M.J., Chilvers, M.I., Pandey, A.K., Steinberg, C., 2023. Exploiting root exudates to manage soil-borne disease complexes in a changing climate. Trends Microbiol., 32:27-37. https://doi.org/10.1016/j.tim.2023.07.011.
  50. Li, Q.Y., Wang, S.Y., Chang, S.W., Xu, K.G., Li, M.Y., Xu, Q.Q., Jiang, Y.M., Niu, J.S., 2008. Key periods and effects of meteorological factors affecting incidence of wheat black point in the Yellow and Huai wheat area of China. Crop Protect, 125:104882. https://doi.org/10.1016/j.cropro.2019a.104882.
  51. Li, B., Cao, X., Chen, L., Zhou, Y., Duan, X., Luo, Y., Fitt, B.D.L., Xu, X., Song, Y., Wang, B., Shiqin, C., 2013. Application of geographic information systems to identify the oversummering regions of Blumeria graminis f. sp. tritici in China. Plant Disease, 97:1168-1174. doi: 10.1094/PDIS-10-12-0957-RE. PMID: 30722407.
  52. Li, Q.Y., Xu, Q.Q., Jiang, Y.M., Niu, J.S., Xu, K.G., He, R.S., 2019. The correlation between wheat black point and agronomic traits in the North China Plain. Crop Protection, 119:17-23. https://doi.org/10.1016/j.cropro.2019.01.004.
  53. Li, Q., Li, M., Jiang, Y., Wang, S., Xu, K., Liang, X., Niu, J., Wang, C., 2020. Assessing genetic resistance in wheat to black point caused by six fungal species in the yellow and huai wheat area of China. Plant Disease, 104:3131-3134. doi: 10.1094/PDIS-01-20-0018-RE. Epub 2020 Oct 16. PMID: 33066722.
  54. Lim, J.A., Yaacob, J.S., Mohd-Rasli, S.R.A., Eyahmalay, J.E., El-Enshasy, H.A., Zakaria, M.R.S., 2023. Mitigating the repercussions of climate change on diseases affecting important crop commodities in Southeast Asia, for food security and environmental sustainability-A review. Front. Sustain. Food Syst., 6:1030540. https://doi.org/10.3389/fsufs.2022.1030540.
  55. Lin, Z., Zhang, P., Halliday, F., Wang, X., Chen, F., Shi, A., Shi, J., Xiao, Y., Liu, X., 2021. Data from: Contrasting effects of elevation on above and below ground plant pathogens. Dryad, https://doi.org/10.5061/dryad.gqnk98spf.
  56. Lin, Z., Halliday, F.W., Zhang, P., Wang, X., Chen, F., Shi, A., Shi, J., Xiao, Y., Liu, X., 2025. Above and belowground plant pathogens along elevational gradients: patterns and potential mechanisms. Oikos, e10455. doi: 10.1111/oik.10455. Lithosols, 2025. Orthent. Available at https://en.wikipedia.org/wiki/Orthent (Accessed Date: 05 May 2025)
  57. Liu, X., Ma, Z.Y., Cadotte, M.W., Chen, F., He, J.S., Zhou, S.R., 2019. Warming affects foliar fungal diseases more than precipitation in a Tibetan alpine meadow. New Phytol., 221:1574-1584. https://doi.org/10.1111/nph.15460.
  58. Lomolino, M.V., 2001. Elevation gradients of species‐density: historical and prospective views. Global Ecology and Biogeography, 10(1):3-13. https://doi.org/10.1046/j.1466-822x.2001.00229.x.
  59. Lorestani, E., Kamkar, B., Razavi, S., Teixeira da Silva, J., 2013. Modeling and mapping diversity of pathogenic fungi of wheat fields using geographic information systems. Crop Protection, 54:74-83. https://doi.org/10.1016/j.cropro.2013.07.002.
  60. Mahler, R.L., Benzdicek, D.F., Witters, R.E., 1979. Influence of slope position on nitrogen fixation and yield of dry peas. Agronomy Journal 71(2):348e354. https://doi.org/10.2134/agronj1979.00021962007100020029x.
  61. Mahlein, A.K., 2016. Plant disease detection by imaging sensors-parallels and specifc demands for precision agriculture and plant phenotyping. Plant Dis., 100:241-251. https://doi.org/10.1094/pdis-03-15-0340-fe.
  62. Masiello, M., Somma, S., Susca, A., 2020. Molecular identification and mycotoxin production by alternaria species occurring on durum wheat, showing black point symptoms. Toxins (Basel), 12(4):275. doi: 10.3390/toxins12040275. PMID: 32340279; PMCID: PMC7232423.
  63. MEVBIS, 2025. Meteorological Data Information Presentation and Sales System. Available at https://mevbis.mgm.gov.tr/mevbis/ui/index.html#/Workspace (Accessed Date: 25 April 2025)
  64. Moschini, R., Sisterna, M., Carmona, M., 2006. Modelling of wheat black point incidence based on meteorological variables in the southern Argentinean Pampas region. Australian Journal of Agricultural Research, 57:1151-1156. doi:10.1071/ar05275.
  65. Oerke, E.C., 2006. Crop losses to pests. J. Agric. Sci., 144:31-43. doi:10.1017/S0021859605005708.
  66. Oerke, E.C., 2020. Remote sensing of diseases. Annu Rev Phytopathol., 58:225-252. https://doi.org/10.1146/annurev-phyto-010820-012832.
  67. Roberts, D.P., Kobayashi, D.Y., 2011. Impact of spatial heterogeneity within spermosphere and rhizosphere environments on performance of bacterial biological control agents. Bacteria in agrobiology: Crop ecosystems, 111-130. https://doi.org/10.1007/978-3-642-18357-7_5.
  68. Romero, F., Cazzato, S., Walder, F., Vogelgsang, S., Bender, S.F., van der Heijden, M.G.A., 2021. Humidity and high temperature are important for predicting fungal disease outbreaks worldwide. New Phytol., 234:1553-1556. https://doi.org/10.1111/nph.17340.
  69. Rowe, R.J., 2009. Environmental and geometric drivers of small mammal diversity along elevational gradients in Utah. Ecography, 32:411-422. https://doi.org/10.1111/j.1600-0587.2008.05538.x.
  70. Roy, B.A., Güsewell, S., Harte, J., 2004. Response of plant pathogens and herbivores to a warming experiment. Ecology, 85:2570-2581. https://doi.org/10.1890/03-0182.
  71. RTMAF, 2025. Land Usage Land Cover Classes. Available at https://corine.tarimorman.gov.tr/corineportal/araziortususiniflari.html. (Accessed Date: 01 May 2025)
  72. Sesiz, U., 2023. The Screening of black point in commercial bread wheat cultivars grown in Turkey and the effect of black point on thousand grain weight. Yuzuncu Yil University Journal of the Institute of Natural and Applied Sciences, 28:230-238. https://doi.org/10.53433/yyufbed.1170102.
  73. Shen, H., Liu, G., Ge, Y., 2005. Research on wheat diseases and insect pests geographic information system. The International Federation for Information Processing. Boston, M.A. Springer,
  74. Siebold, M., Tiedemann, A., 2013. Effects of experimental warming on fungal disease progress in oilseed rape. Global Change Biol., 19:1736-1747. https://doi.org/10.1111/gcb.12180.
  75. Sinai, G., Zaslavsky, D.Z., Golany, P., 1981. The effect of soil surface curvature on moisture and yielddBeer Sheba observation. Soil Science Society of America Journal, 132(5):367e375. https://ui.adsabs.harvard.edu/link_gateway/1981SoilS.132.367S/doi:10.1097/00010694-198111000-00007.
  76. Sisterna, M., Sarandon, S., 2005. Preliminary studies on the natural incidence of wheat black point under different fertilization levels and tillage systems in Argentina. Plant Pathol. J., 4:26-28. https://doi.org/10.3923/ppj.2005.26.28.
  77. Skendzic, S., Zovko, M., Zivkovic, I.P., Lesic, V., Lemic, D., 2021. The impact of climate change on agricultural insect pests. Insects, 12:440. https://doi.org/10.3390/insects12050440.
  78. Stone, J.R., Gilliam, J.W., Cassel, D.K., Danies, R.B., Nelson, L.A., Kleiss, H.J., 1985. Effect of erosion and landscape position on the productivity of Piedmont soils. Soil Science Society of America Journal, 49(4):987e991. https://doi.org/10.2136/sssaj1985.03615995004900040039x.
  79. Toklu, F., Akgul, D., Bicici, M., Karakoy, T., 2008. The relationship between black point and fungi species and effects of black point on seed germination properties in bread wheat. Turk. J. Agric. For., 32:267-272. https://journals.tubitak.gov.tr/agriculture/vol32/iss4/4.
  80. USGS, 2025. What are sedimentary rocks? Available at https://www.usgs.gov/faqs/what-are-sedimentary-rocks, (Accessed Date: 02 May 2025)
  81. Waldron, L.R., 1934. Increase of kernel weight in common wheat due to black point disease. J. Agric. Res., 48:1017-1024.
  82. Walker, K.R., 2011. Regulation of Candidate Genes in Black Poimt Formation in Barley. PhD Thesis. The University of Adelaide (Faculty of Science). Adelaide(Australia): p. 52-63.
  83. Walters, D.R., Bingham, I.J., 2007. Infuence of nutrition on disease development cause by fungal pathogens: implications for plant disease control. Ann Appl Biol., 151:307-324. https://doi.org/10.1111/j.1744-7348.2007.00176.x.
  84. Wang, H.W., 2006. The Development of wheat black point warning and control decision-making expert system for henan province. MSc Thesis. Henan Agricultural University, Zhengzhou (China): p. 47-48.
  85. Weiss, M.V., 1987. Compendium of wheat diseases. APS Press, 2nd ed., St. Paul, MN.
  86. WHEAT, 2013. Wheat: vital grain of civilization and food security. Mexico, D.F.; CGIAR Res. Program Wheat 2013 Annu. Rep., CGIAR.
  87. Wiese, M., 1987. Compendium of wheat diseases. The American Phytopathological Society (APS) Press, MABEE Library, Mid-America Nazarene College, Olathe.
  88. Xu, K.G., Jiang, Y.M., Li, Y.K., Xu, Q.Q., Niu, J.S., Zhu, X.X., Li, Q.Y., 2018. Identification and pathogenicity of fungal pathogens causing black point in wheat on the North China Plain. Indian J. Microbiol., 58(2):159-164. doi: 10.1007/s12088-018-0709-1. Epub 2018 Jan 24. PMID: 29651174; PMCID: PMC5891473.
  89. Yomralıoğlu, T., 2000. Geographic information systems basic concepts and applications. İber Ofset, Trabzon.
  90. Yoshino, K., Zou, T., Nyamsambuu, K., Pham, D., Okabe, H., 2015. Spatial dependency of soil line coeffıcıents derived from Landsat ETM+ and MODIS imagery in Kyrgyzstan. The 36th Asian Conference on Remote Sensing; Quezon city, Metro Manila, Philippines.
  91. Zhang, Z.X., 2016. Rock Fracture and Blasting - Theory and Applications - Chapter 3 - Rock Fracture and Rock Strength. Butterworth (Heinemann): Copyright © Elsevier. https://doi.org/10.1016/C2014-0-01408-6. https://www.sciencedirect.com/book/9780128026885/rock-fracture-and-blasting
  92. Agrios,G.N. (2005). Plant pathology. Elsevier Academic Press, 5th ed, UK, London
  93. Sinai, G., Zaslavsky, D.Z., Golany, P., 1981. The effect of soil surface curvature on moisture and yielddBeer Sheba observation. Soil Science Society of America Journal, 132(5):367e375. https://ui.adsabs.harvard.edu/link_gateway/1981SoilS.132.367S/doi:10.1097/00010694-198111000-00007.