Iranian Journal of Irrigation & Drainage

Iranian Journal of Irrigation & Drainage

Investigation the placement refinement of male trees in pistachio orchard to increase water productivity

Document Type : Original Article

Authors
1 Graduated M.Sc. student of Irr. & Dra. Eng., Water Sci. & Eng. Dept., Faculty of Agri. & Natural Res. Imam Khomeini International University, Iran, Qazvin
2 Assistant Professor, Water Science. & Eng. Dept., Faculty of Agri. & Natural Res. Imam Khomeini International University, Iran, Qazvin
3 Professor Water Sci. & Eng. Dept., Faculty of Agri. & Natural Res. Imam Khomeini International University, Iran, Qazvin
Abstract
Pistachios are considered as an economic crop in horticulture and, compared to other crops, they will gain more income by consuming less water, which is a major advantage for the global agricultural market. One of the factors affecting the yield and quality of pistachios is proper pollination in the orchard, which is directly related to the number of male trees in the orchard. Typically, 5 to 7 percent of the trees in the orchard are male rootstocks, which need to be properly distributed throughout the orchard based on the climatic conditions of the region. This research was conducted in the pistachio orchards of Popli Farm in Qazvin, covering an area of 193 hectares. 20 drone flights were conducted and 2722 aerial images were taken from a height of 30 meters above the orchard. After image processing and determining the location of male trees in the orchard, a modified layout map was prepared for a sample orchard, and based on the orchard's water consumption data over 10 years, water productivity values were evaluated under two modified scenarios. In the first scenario, minimal changes were made to the position of male trees, and in the second scenario, placement was done regardless of the current situation and based on the suggestions of previous studies. The results obtained for water productivity values in both scenarios showed that modifying the placement of male trees in the sample orchard improved total productivity, and its amount increased from about 1 kg m-3 to 12% in the first scenario and about 24% in the second scenario. As a result, with less water consumption or increasing the yield with the same amount of water consumption, the orchardist will have more income.
Keywords

احمدی، م. و رمضانی اعتدالی، ه. 1401. کاربردپذیری پایگاه‌ بارشی GLDAS در برآورد ردپای آب سبز و آبی گندم و ذرت در دشت قزوین با استفاده از مدل Aqua Crop', هیدروژئولوژی. 7(2): 42-30.
سلطانی، م. 1403. برآورد درصد پوشش گیاهی ذرت با استفاده از الگوریتم‏های پردازش تصویر.مدیریت آب و آبیاری. 14(1): 122-111.
شریفانی،م.، اسماعیلی، م.، ترابی، ب.، دهقانی، ا.ا.، عوض آبادیان، ع.ا.، و حکم‏آبادی، ح. 1402. بررسی دینامیک حرکت دانه‌گرده و ارتباط آن با بارآوری درختان پسته. پژوهش‌های تولید -گیاهی. 30(4): 57-77 .
عبداله‏نژاد باروق، ع.، عادلی نیا، م. و محمدی، م. 1395. کلاس‌بندی پسته با استفاده از تکنیک‌های پردازش تصویر و شبکه نروفازی تطبیق‌پذیر. ماشین های کشاورزی. 6 (1): 68-60.
فرهادی، ح.، شریفانی، م. م. و حکم آبادی، ن. 1399. بررسی اثرات گرده‌افشانی آزاد و کنترل شده دانه گرده گونه‌های اهلی و اینتگریما بر برخی ویژگی‌های کمی و کیفی میوه پسته (Pistachio vera L.) رقم فندقی، مجله علوم و فناوری پسته. 5 (10): 45-65.
قاسمی، م.، کاشانی‏زاده، س.، گلمحمدی، م.، قاسمی، ش.، هاشمی‏نسب، ح. و حکم‏آبادی، ح. 1399. بررسی الگوی گلدهی و کمیت دانه گرده برخی ژنوتیپ‌های نر پسته (Pistacia  vera L.) در شرایط آب و هوایی قزوین، مجله علوم و فناوری پسته. 5 (9): 176-187
کاشانی‏زاده، س. 1384. بررسی، شناسایی و جمع آوری ارقام نر پسته در منطقه قزوین. گزارش پژوهشی موسسه تحقیقات پسته کشور، رفسنجان.
گوینده نجف‏آبادی، م.، میرلطیفی، س.م. و اکبری، م. 1397. برآورد شاخص سطح برگ ذرت با استفاده دوربین دیجیتال اصلاح شده، نشریه آبیاری و زهکشی ایران. 12(6): 1406-1396.
Mehdi-Tounsi, H, Chelli-Chaabouni, A, Mahjoub-Boujnah, D. and Boukhris, M. 2017. Long term field response of pistachio to irrigation water salinity. Journal of agricultural water management. 185: 1-12.
Inoue, Y. 2020 Satellite- and drone-based remote sensing of crops and soils for smart farming – a review. Soil Science and Plant Nutrition. 66(6): 798–810. https://doi.org/10.1080/00380768.2020.1738899
Soltani, M. 2024. Estimating maize canopy cover percent by means of image processing algorithms. Water and Irrigation Management. 14(1): 111-122. doi: 10.22059/jwim.2023.364331.1098
Riehle, D., Reiser, D. and Griepentrog, H. W. 2020. Robust index-based semantic plant/background segmentation for RGB- images. Computers and Electronics in Agriculture. 169: 105201. https://doi.org/10.1016/j.compag.2019.105201.
Abdullah, S. L. S., Hambali, H. and Jamil, N. 2012. Segmentation of natural images using an improved ‎thresholding-based technique. Procedia Engineering. 41(Iris): 938–944. ‎https://doi.org/10.1016/j.proeng.2012.07.266‎.
Panday, U. S., Pratihast, A. K., Aryal, J. and Kayastha, R. B. 2020. A review on drone-based data solutions for cereal crops. Drones. 4(3): 1–29. https://doi.org/10.3390/drones4030041
Zhang, C. and Kovacs, J. M. 2012. The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture 2012 13:6. 13(6): 693–712. https://doi.org/10.1007/S11119-012-9274-5
Miraki, M., Sohrabi, H., Fatehi, P. 2022. Citrus trees identification and trees stress detection based on spectral data derived from UAVs. Research in Horticultural Sciences. 1(1): 27-40. doi: 10.22092/rhsj.2022.127815
Vaknin, Y, Gan-Mor, S, Bechar, A, Ronen B, & Eisikowitch, D. 2002. Electrostatic pollination of pistachio, a novel technique of pollen supplementation in agriculture. United States Agricultural Research and Development Funding. 1511-1516.