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BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI

Yıl 2024, Cilt: 4 Sayı: 2, 107 - 117, 31.12.2024

Öz

Bağcılık tarımsal üretimde en yoğun kültürel uygulama ve bakım işleminin yapıldığı yetiştiricilik şekillerinden birisidir. Hastalık ve zararlı takibi, sulama, gübreleme vb. uygulamaların zamanında ve en uygun yöntemle yapılması verim ve kalite açısından büyük önem taşımaktadır. Bu uygulamaların etkili şekilde gerçekleştirilebilmesi için yenilikçi teknolojilerden faydalanılması günümüz koşullarında bir zorunluluk haline gelmeye başlamıştır. Özellikle hassas tarım gibi yaklaşımların uygulanabilmesi ise sensör teknolojisi gibi araçların kullanılmasıyla mümkün olabilmektedir. Bu araçlar hem mevcut durumun belirlenmesine hem de uygulama aşamasında karar destek sisteminin sağlanmasına olanak tanımaktadır. Bu tarz teknolojilerin kullanımı aynı zamanda sürdürülebilir tarım yaklaşımı içerisinde değişen iklim koşulları ve üretim zorlukları ile mücadelede önemli bir araç olma potansiyeline sahiptir. Bu makale kapsamında gerek verim-kalite özelliklerinin izlenmesinde ve gerekse yetiştirme tekniğine yönelik uygulamalarda kullanılan sensör tiplerinin ve bunların üretime sağlayabileceği katkıların tanıtılması hedeflenmektedir. Bu kapsamda toprak ve iklim değerlerinin izlenmesi, bitki gelişimine yönelik parametrelerin takibi, üzüme özgü kalite değerlerinin ortaya konulmasında mevcut durum ve ileriye dönük uygulama olanakları incelenmiştir. Özellikle son yıllarda yapılan spesifik çalışmalar kapsamlı şekilde taranarak bunların üretici ve sektör paydaşlarına önerilerle birlikte özetlenmesi hedeflenmiştir.

Kaynakça

  • Abdelghafour F, Rosu R, Keresztes B, Germain C, Da Costa J P (2019). A Bayesian framework for joint structure and colour based pixel-wise classification of grapevine proximal images. Computers and Electronics in Agriculture. 158: 345-357
  • Ammoniaci M, Kartsiotis S.-P, Perria R, Storchi P (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture 11, 201
  • Catania P, Vallone M, Re G L, Ortolani M (2013). A wireless sensor network for vineyard management in Sicily (Italy). Agric Eng Int: CIGR Journal 15(4): 139-146
  • Cogato A, Meggio F, Collins C, Marinello F (2020). Medium-resolution multispectral data from sentinel-2 to assess the damage and the recovery time of late frost on vineyards. Remote Sensing 12, 1896
  • Cogato A, Pagay V, Marinello F, Meggio F, Grace P, Migliorati D A M (2019). Assessing the feasibility of using sentinel-2 ımagery to quantify the ımpact of heatwaves on ırrigated vineyards. Remote Sensing 11, 2869
  • Daglio G, Cesaro P, Todeschini V, Lingua G, Lazzari M, Berta G, Massa N (2022). Potential field detection of Flavescence dorée and Esca diseases using a ground sensing optical system. Biosystems Engineering 215(2022): 203-214
  • Diago M P, Rey-Carames C, Moigne M L, Fadaili E M, Tardaguila J, Cerovic Z G (2016). Calibration of non-invasive fluorescence-based sensors for the manual and on-the-go assessment of grapevine vegetative status in the field. Australian Journal of Grape and Wine Research 22(3): 438-449
  • Ferro M V, Catania P (2023). Technologies and innovative methods for precision viticulture: a comprehensive review. Horticulturae 2023, 9, 399.
  • Ghozlen N B, Cerovic Z G, Germain C, Toutain S, Latouche G (2010). Non-destructive optical monitoring of grape maturation by proximal sensing. Sensors 10(11): 10040-10068
  • Gutiérrez S, Fernández‑Novales J, Diago M, Iñiguez R, Tardaguila J (2021). Assessing and mapping vineyard water status using a ground mobile thermal imaging platform. Irrigation Science 39:457–468
  • Kartsiotis S P, Ammoniaci M, Perria R, Storchi P (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture 2021, 11, 201
  • Keskin M (2007). Spektroradyometreler ve tarımda kullanım alanları. Tarımsal Mekanizasyon 24. Ulusal Kongresi, 5-6 Eylül, Kahramanmaraş, 326-332
  • Matese A, Di Gennaro S F (2015). Technology in precision viticulture: a state of the art review. International Journal of Wine Research 2015(7): 69-81
  • Meyers J M, Dokoozlian N, Ryan C, Bioni C (2020). A new, satellite ndvı-based sampling protocol for grape maturation monitoring. Remote Sensing 12, 1159
  • Mizik T (2023). How can proximal sensors help decision-making in grape production?. Heliyon 9(2023) e16322 Njoroge B M, Fei T K, Thiruchelvam V (2018). A research review of precision farming techniques and technology. Journal of Applied Technology and Innovation 2(1): 22-30
  • Oberti R, Marchi M, Tirelli P, Calcante A, Iriti M, Borghese A N (2014). Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity. Computers and Electronics in Agriculture 104(2014): 1-8
  • Pérez-Roncal C, López-Maestresalas A, Lopez-Molina C, Jarén C, Urrestarazu J, Santesteban L G, Arazuri S (2020). Hyperspectral imaging to assess the presence of powdery mildew (erysiphe necator) in cv. carignan noir grapevine bunches. Agronomy 10, 88
  • Sapaev J, Fayziev J, Sapaev I, Abdullaev D, Nazaraliev D, Sapaev B (2023). Viticulture and wine production: challenges, opportunities and possible implications. E3S Web of Conferences, 452, 01037
  • Shanmuganthan S, Ghobakhlou A, Sallis P (2008). Sensors for modeling the effects of climate change on grapevine growth and wine quality. 12th WSEAS International Conference on CIRCUITS, 22-24 July, pp. 315-320
  • Sun Q, Ebersole C, Wong D P, Curtis K (2022). The impact of vineyard mechanization on grape and wine phenolics, aroma compounds, and sensory properties. Fermentation 2022, 8, 318
  • Torres R, Ferrara G, Soto F, López J A, Saanchez F, Mazzeo A, Pérez-Pastor A, Domingo R (2017). Effects of soil and climate in a table grape vineyard with cover crops. irrigation management usıng sensors networks. Ciência Téc. Vitiv. 32(1): 72-81
  • Trought M C T, Bramley R G V (2011). Vineyard variability in Marlborough, New Zealand: Characterising spatial and temporal changes in fruit composition and juice quality in the vineyard. Aust. J. Grape Wine R., 17, 79–89
  • Yazar Coşkun E, Karacabey E (2023). Current approaches in viticulture mechanization. Viticulture Studies (VIS) 3(2): 65 – 71

Use of Sensor Technology and Proximal Sensing Applications in Viticulture

Yıl 2024, Cilt: 4 Sayı: 2, 107 - 117, 31.12.2024

Öz

Viticulture is one of cultivation types in which the most intense cultural practices and maintenance are carried out in agricultural production. It is of great importance in terms of efficiency and quality that the applications such as disease and pest monitoring, irrigation, fertilization, etc. are carried out on time and with the most appropriate method. In order to carry out these applications effectively, using innovative technologies has become a necessity in today's conditions. Especially the implementation of approaches such as precision agriculture is possible by using tools such as sensor technology. These tools allow both to determine the current situation and to provide a decision support system during the implementation phase. The use of such technologies also has the potential to be an important tool in struggling with changing climate conditions and production challenges within the sustainable agriculture approach. Within the scope of this article, it is aimed to introduce the sensor types used both in monitoring yield-quality characteristics and in applications related to cultivation techniques and to introduce the contributions which can make to production. In this context, the current situation and future application possibilities in monitoring soil and climate values, monitoring parameters for plant development and determining grape-specific quality values were examined. It is aimed to comprehensively review specific studies, especially in recent years, and summarize them with recommendations for growers and sector stakeholders.

Kaynakça

  • Abdelghafour F, Rosu R, Keresztes B, Germain C, Da Costa J P (2019). A Bayesian framework for joint structure and colour based pixel-wise classification of grapevine proximal images. Computers and Electronics in Agriculture. 158: 345-357
  • Ammoniaci M, Kartsiotis S.-P, Perria R, Storchi P (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture 11, 201
  • Catania P, Vallone M, Re G L, Ortolani M (2013). A wireless sensor network for vineyard management in Sicily (Italy). Agric Eng Int: CIGR Journal 15(4): 139-146
  • Cogato A, Meggio F, Collins C, Marinello F (2020). Medium-resolution multispectral data from sentinel-2 to assess the damage and the recovery time of late frost on vineyards. Remote Sensing 12, 1896
  • Cogato A, Pagay V, Marinello F, Meggio F, Grace P, Migliorati D A M (2019). Assessing the feasibility of using sentinel-2 ımagery to quantify the ımpact of heatwaves on ırrigated vineyards. Remote Sensing 11, 2869
  • Daglio G, Cesaro P, Todeschini V, Lingua G, Lazzari M, Berta G, Massa N (2022). Potential field detection of Flavescence dorée and Esca diseases using a ground sensing optical system. Biosystems Engineering 215(2022): 203-214
  • Diago M P, Rey-Carames C, Moigne M L, Fadaili E M, Tardaguila J, Cerovic Z G (2016). Calibration of non-invasive fluorescence-based sensors for the manual and on-the-go assessment of grapevine vegetative status in the field. Australian Journal of Grape and Wine Research 22(3): 438-449
  • Ferro M V, Catania P (2023). Technologies and innovative methods for precision viticulture: a comprehensive review. Horticulturae 2023, 9, 399.
  • Ghozlen N B, Cerovic Z G, Germain C, Toutain S, Latouche G (2010). Non-destructive optical monitoring of grape maturation by proximal sensing. Sensors 10(11): 10040-10068
  • Gutiérrez S, Fernández‑Novales J, Diago M, Iñiguez R, Tardaguila J (2021). Assessing and mapping vineyard water status using a ground mobile thermal imaging platform. Irrigation Science 39:457–468
  • Kartsiotis S P, Ammoniaci M, Perria R, Storchi P (2021). State of the art of monitoring technologies and data processing for precision viticulture. Agriculture 2021, 11, 201
  • Keskin M (2007). Spektroradyometreler ve tarımda kullanım alanları. Tarımsal Mekanizasyon 24. Ulusal Kongresi, 5-6 Eylül, Kahramanmaraş, 326-332
  • Matese A, Di Gennaro S F (2015). Technology in precision viticulture: a state of the art review. International Journal of Wine Research 2015(7): 69-81
  • Meyers J M, Dokoozlian N, Ryan C, Bioni C (2020). A new, satellite ndvı-based sampling protocol for grape maturation monitoring. Remote Sensing 12, 1159
  • Mizik T (2023). How can proximal sensors help decision-making in grape production?. Heliyon 9(2023) e16322 Njoroge B M, Fei T K, Thiruchelvam V (2018). A research review of precision farming techniques and technology. Journal of Applied Technology and Innovation 2(1): 22-30
  • Oberti R, Marchi M, Tirelli P, Calcante A, Iriti M, Borghese A N (2014). Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity. Computers and Electronics in Agriculture 104(2014): 1-8
  • Pérez-Roncal C, López-Maestresalas A, Lopez-Molina C, Jarén C, Urrestarazu J, Santesteban L G, Arazuri S (2020). Hyperspectral imaging to assess the presence of powdery mildew (erysiphe necator) in cv. carignan noir grapevine bunches. Agronomy 10, 88
  • Sapaev J, Fayziev J, Sapaev I, Abdullaev D, Nazaraliev D, Sapaev B (2023). Viticulture and wine production: challenges, opportunities and possible implications. E3S Web of Conferences, 452, 01037
  • Shanmuganthan S, Ghobakhlou A, Sallis P (2008). Sensors for modeling the effects of climate change on grapevine growth and wine quality. 12th WSEAS International Conference on CIRCUITS, 22-24 July, pp. 315-320
  • Sun Q, Ebersole C, Wong D P, Curtis K (2022). The impact of vineyard mechanization on grape and wine phenolics, aroma compounds, and sensory properties. Fermentation 2022, 8, 318
  • Torres R, Ferrara G, Soto F, López J A, Saanchez F, Mazzeo A, Pérez-Pastor A, Domingo R (2017). Effects of soil and climate in a table grape vineyard with cover crops. irrigation management usıng sensors networks. Ciência Téc. Vitiv. 32(1): 72-81
  • Trought M C T, Bramley R G V (2011). Vineyard variability in Marlborough, New Zealand: Characterising spatial and temporal changes in fruit composition and juice quality in the vineyard. Aust. J. Grape Wine R., 17, 79–89
  • Yazar Coşkun E, Karacabey E (2023). Current approaches in viticulture mechanization. Viticulture Studies (VIS) 3(2): 65 – 71
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ziraat Mühendisliği (Diğer)
Bölüm Derlemeler
Yazarlar

Nilay Taşdelen Ok 0009-0000-2430-2853

Ersin Karacabey 0000-0003-4166-1553

Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 9 Temmuz 2024
Kabul Tarihi 27 Ağustos 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 4 Sayı: 2

Kaynak Göster

APA Taşdelen Ok, N., & Karacabey, E. (2024). BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI. Kırşehir Ahi Evran Üniversitesi Ziraat Fakültesi Dergisi, 4(2), 107-117.
AMA Taşdelen Ok N, Karacabey E. BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI. KUZFAD. Aralık 2024;4(2):107-117.
Chicago Taşdelen Ok, Nilay, ve Ersin Karacabey. “BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI”. Kırşehir Ahi Evran Üniversitesi Ziraat Fakültesi Dergisi 4, sy. 2 (Aralık 2024): 107-17.
EndNote Taşdelen Ok N, Karacabey E (01 Aralık 2024) BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI. Kırşehir Ahi Evran Üniversitesi Ziraat Fakültesi Dergisi 4 2 107–117.
IEEE N. Taşdelen Ok ve E. Karacabey, “BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI”, KUZFAD, c. 4, sy. 2, ss. 107–117, 2024.
ISNAD Taşdelen Ok, Nilay - Karacabey, Ersin. “BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI”. Kırşehir Ahi Evran Üniversitesi Ziraat Fakültesi Dergisi 4/2 (Aralık 2024), 107-117.
JAMA Taşdelen Ok N, Karacabey E. BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI. KUZFAD. 2024;4:107–117.
MLA Taşdelen Ok, Nilay ve Ersin Karacabey. “BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI”. Kırşehir Ahi Evran Üniversitesi Ziraat Fakültesi Dergisi, c. 4, sy. 2, 2024, ss. 107-1.
Vancouver Taşdelen Ok N, Karacabey E. BAĞCILIKTA SENSÖR TEKNOLOJİSİ KULLANIMI VE YAKINSAL ALGILAMA UYGULAMALARI. KUZFAD. 2024;4(2):107-1.