کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6539889 | 1421104 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using ground-based spectral reflectance sensors and photography to estimate shoot N concentration and dry matter of potato
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
NIRRVIRRERatio Vegetation IndexDrip irrigation - آبیاری قطرهایNear-infrared reflectance - انعکاس نزدیک مادون قرمزnormalized difference vegetation index - شاخص تنوع گیاه شناسی نرمال شدهLeaf area index - شاخص سطح برگNDVI - شاخص نرمالشده تفاوت پوشش گیاهی Vegetation index - شاخص گیاهیLAI - شبیهShoot - شلیکCorrelation coefficient - ضریب همبستگیChlorophyll concentration - غلظت کلروفیلNup - قدم زدن
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Using ground-based spectral reflectance sensors and photography to estimate shoot N concentration and dry matter of potato Using ground-based spectral reflectance sensors and photography to estimate shoot N concentration and dry matter of potato](/preview/png/6539889.png)
چکیده انگلیسی
Two years experiments were set up to evaluate the performance of different vegetation indices (VI) to estimate shoot N concentration (Nc) and shoot dry matter (DM) for a potato crop grown under different nitrogen (N) treatments. Possibilities to improve the performance of VI using normalization by leaf area index (LAI) or camera-derived ground cover fraction (GC) were also investigated. Results indicated that Nc was significantly correlated to RRE (Near-infrared divided by red edge reflectance) and RRE/GC with a coefficient of determination (R2) of 0.62 and 0.78, respectively, indicating that inclusion of auxiliary parameter GC together with RRE substantially improved the correlation as compared to using only RRE. However, no significant correlation between Nc and RVI (Ratio Vegetation Index, near-infrared divided by red reflectance) or NDVI (Normalized Difference Vegetation Index) was found. However, DM was highly correlated to RVI and NDVI. Moreover, DM showed significant relationship (R2â¯=â¯0.86) with GC, highlighting its versatile usefulness in estimating agronomic variables DM and Nc, which are the core variables to assess N status of crops for a better N application.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 144, January 2018, Pages 154-163
Journal: Computers and Electronics in Agriculture - Volume 144, January 2018, Pages 154-163
نویسندگان
Zhenjiang Zhou, Mohamed Jabloun, Finn Plauborg, Mathias Neumann Andersen,