کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8487400 1552022 2016 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Characterising the within-field scale spatial variation of nitrogen in a grassland soil to inform the efficient design of in-situ nitrogen sensor networks for precision agriculture
ترجمه فارسی عنوان
مشخص نمودن تنوع فضایی موجود در مقیاس درون زمین در خاک روستایی به منظور اطلاع رسانی به طراحی کارایی شبکه های حسگر نیتروژن در محیط کشت دقیق
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
چکیده انگلیسی
The use of in-situ sensors capable of real-time monitoring of soil nitrogen (N) may facilitate improvements in agricultural N-use efficiency (NUE) through better fertiliser management. The optimal design of such sensor networks, consisting of clusters of sensors each attached to a data logger, depends upon the spatial variation of soil N and the relative cost of the data loggers and sensors. The primary objective of this study was to demonstrate how in-situ networks of N sensors could be optimally designed to enable the cost-efficient monitoring of soil N within a grassland field (1.9 ha). In the summer of 2014, two nested sampling campaigns (June & July) were undertaken to assess spatial variation in soil amino acids, ammonium (NH4+) and nitrate (NO3−) at a range of scales that represented the within (less than 2 m) and between (greater than 2 m) data logger/sensor cluster variability. Variance at short range (less than 2 m) was found to be dominant for all N forms. Variation at larger scales (greater than 2 m) was not as large but was still considered an important spatial component for all N forms, especially NO3−. The variance components derived from the nested sampling were used to inform the efficient design of theoretical in-situ networks of NH4+ and NO3− sensors based on the costs of a commercially available data logger and ion-selective electrodes (ISEs). Based on the spatial variance observed in the June nested sampling, and given a budget of £5000, the NO3− field mean could be estimated with a 95% confidence interval width of 1.70 μg N g−1 using 2 randomly positioned data loggers each with 5 sensors. Further investigation into “aggregate-scale” (less than 1 cm) spatial variance revealed further large variation at the sub 1-cm scale for all N forms. Sensors, for which the measurement represents an integration over a sensor-soil contact area of diameter less than 1 cm, would be subject to this aggregate-scale variability. As such, local replication at scales less than 1 cm would be needed to maintain the precision of the resulting field mean estimation. Adoption of in-situ sensor networks will depend upon the development of suitable low‐cost sensors, demonstration of the cost-benefit and the construction of a decision support system that utilises the generated data to improve the NUE of fertiliser N management.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agriculture, Ecosystems & Environment - Volume 230, 16 August 2016, Pages 294-306
نویسندگان
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