Forecasting rainfed sorghum yield using satellite-derived vegetation indices with limited ground-based information in Gadarif region, eastern Sudan

  • admin
  • M.A. Bashir Gezira Research Station, Agricultural Research Corporation, Wad Medani, Sudan
  • H. Tanakamaru Graduate School of Agricultural Science, Kobe University, Japan
  • A. Tada Graduate School of Agricultural Science, Kobe University, Japan
  • A.E. Hassan Gedarif Research Station, Agricultural Research Corporation, Gedarif, Sudan.
  • A.E. Khalid Dongla Research Station, Agricultural Research Corporation, Dongola, Sudan.
  • H.A. Sirelkhatim Gezira Research Station, Agricultural Research Corporation, Wad Medani, Sudan.

Abstract

A practical crop growth and yield monitoring system based on satellite data is required and fundamental not only for precision farming, but also very useful for global food security enhancement. This study was performed to determine the optimal vegetation index and also to identify the best time for making a reliable crop yield forecast in one of the major sorghum-growing region (Gedarif State, Sudan). The study was also aimed to develop a simple yield prediction model which was later validated using an official yield data acquired during 2013 and 2014 cropping seasons from the Department of Information System and Statistical Analysis of the State Ministry of Agriculture, Gedarif State. The study used NASA’s multi-temporal MODerate resolution Imaging Spectroradiometer (MODIS) land products with limited ground information. Relationship between sorghum yield and crop reflectance indicated that normalized difference vegetation index (NDVI) at the third dekad of September (Sep.III) is the most appropriate to develop sorghum yield prediction model with higher R2 value of 0.77 (p<0.05) compared to other vegetation indices (normalized ratio vegetation index, NRVI and soil-adjusted vegetation index, SAVI). The plotting of estimated yield against actual yield during 2013 and 2014 cropping seasons revealed strong positive and linear correlations (R2 = 0.64 (p=0.06) and 0.74 (p<0.05), respectively with average R2 = 0.71 (p<0.001) for both seasons. This study concluded that a good prediction of rainfed sorghum yield could be achieved more than 30 days before harvesting with quick, accurate and cost-effective method compared to traditional field surveys.


 


 


تقدير انتاجية الذرة المطري باستخدام المؤشرات الخضرية المستخلصة من صور الأقمار الصناعية وبعض المعلومات الأرضية في منطقة القضارف, شرق السودان


 


بشير محمد أحمد1 و تناكامارو هاريو2 وتادا أكيو2  و علي التوم حسن3 و خالد علي الطيب4 و سرالختم  حسن أحمد1


 


1محطة بحوث الجزيرة، هيئة البحوث الزراعية، واد مدني، السودان.


2جامعة كوبي، مدرسة دراسات العلوم الزراعية، كوبي، اليابان.


3محطة بحوث القضارف، هيئة البحوث الزراعية، القضارف، السودان.


4محطة بحوث دنقلا، هيئة البحوث الزراعية، دنقلا، السودان.


 


الخلاصة


      إنّ مراقبة نمو المحصول والانتاجية عن طريق نظام عملي يعتمد على معلومات مستخلصة من صور الأقمار الصناعية يعتبر ضروري وأساسي ليس فقط لأغراض الزراعة الدقيقة وإنّما هو مفيد جداً لتعزيز الأمن الغذائي العالمي. اجريت هذه الدراسة لتحديد المؤشر الخضري الأمثل وأيضاً لتحديد أفضل وقت لعمل تقديرات موثوق بها لإنتاجية المحصول في واحدة من المناطق الرئيسية لزراعة الذرة الرفيعة (ولاية القضارف، السودان). كما تهدف هذه الدراسة أيضاً إلى تطوير نموذج بسيط للتنبؤ بإنتاجية المحصول والذي تم التحقق منه لاحقاً باستخدام بيانات رسمية للإنتاجية تم جمعها من شعبة نظم المعلومات والتحليل الاحصائي التابعة لوزارة الزراعة الولائية، ولاية القضارف. استخدمت في هذه الدراسة منتجات أرضية من وكالة الفضاء الأمريكية (ناسا) المستخلصة من مستشعر متعدد الزمنية – معتدل دقة التصوير الطيفي (MODIS) اضافةً إلى بعض المعلومات الأرضية. أوضحت العلاقة بين انتاجية الذرة والانعكاس الطيفي للمحصول أن  NDVI في الفترة الثالثة من سبتمبر (Sep. III) هو الأنسب لتطوير نموذج تقدير الانتاجية (R2 = 0.77, P<0.05) مقارنةً مع المؤشرات الخضرية الأخرى (NRVI و SAVI). كشف مخطط الرسم البياني للإنتاجية المقدرة مقابل الانتاجية الفعلية خلال موسمي 2013 و 2014 أن هناك علاقة ايجابية وخطية قوية (R2 = 0.64, P<0.06) و (R2 = 0.74, P<0.05) علي التوالي بمتوسط (R2 = 0.71, P<0.001) للموسمين. خلصت هذه الدراسة الى أنه يمكن تحقيق تقدير جيد لإنتاجية الذرة المطري قبل حوالي 30 يوماً من الحصاد بطريقة سريعة ودقيقة وفعالة من حيث التكلفة مقارنةً مع المسوحات الميدانية التقليدية.

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Published
2019-12-31
How to Cite
, admin et al. Forecasting rainfed sorghum yield using satellite-derived vegetation indices with limited ground-based information in Gadarif region, eastern Sudan. Gezira Journal of Agricultural Science, [S.l.], v. 17, n. 2, dec. 2019. ISSN 1728-9556. Available at: <http://journals.uofg.edu.sd/index.php/gjas/article/view/1374>. Date accessed: 01 oct. 2020.
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Articles