Sampling Strategies for Mapping ‘Within-field’ Variability in the Dry Matter Yield and Mineral Nutrient Status of Forage Grass Crops in Cool Temperate Climes

Sampling Strategies for Mapping ‘Within-field’ Variability in the Dry Matter Yield and... In the absence of suitable technology to measure and map the dry matter (DM) yield distributions of forage grass crops within individual fields, a ‘manual’ procedure of yield mapping has been developed. Samples of herbage are collected just prior to each silage harvest from known grid points within a field, and sward DM yields at each point are predicted from the mineral composition of the herbage, using empirical mathematical models. Yield maps (and maps of sward nutrient status) are then produced by kriging interpolation between the point data. To make the most efficient use of time and resources, however, sampling intensity needs to be kept to the absolute minimum necessary for interpolation purposes. The aim of the present study was to examine the spatial variability in sward DM yield and mineral nutrient status in a large grass silage field under a three-cut system, and devise ‘optimal’ sampling strategies for mapping the distributions of these parameters at each cut. Herbage samples were collected from the field, prior to each harvest, at 25 m intervals in a regular rectangular grid to provide databases of herbage nutrient contents and DM yields. Different data combinations were abstracted from these databases for comparison purposes, and ordinary kriging used to produce interpolated maps of DM yield and sward N, P, K and S statuses. The results suggested that a sampling density of just seven samples per hectare was adequate for estimating the ‘true’ population means of sward DM yield and sward N, P, K, and S statuses. For mapping purposes, it was found that the best compromise between interpolation accuracy and sampling efficiency was to collect herbage samples in a 35.4 m×35.4 m equilateral triangular sampling pattern. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Sampling Strategies for Mapping ‘Within-field’ Variability in the Dry Matter Yield and Mineral Nutrient Status of Forage Grass Crops in Cool Temperate Climes

Loading next page...
1
 
/lp/springer_journal/sampling-strategies-for-mapping-within-field-variability-in-the-dry-RRJV6pzeAG
Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1023/A:1021815122216
Publisher site
See Article on Publisher Site

Abstract

In the absence of suitable technology to measure and map the dry matter (DM) yield distributions of forage grass crops within individual fields, a ‘manual’ procedure of yield mapping has been developed. Samples of herbage are collected just prior to each silage harvest from known grid points within a field, and sward DM yields at each point are predicted from the mineral composition of the herbage, using empirical mathematical models. Yield maps (and maps of sward nutrient status) are then produced by kriging interpolation between the point data. To make the most efficient use of time and resources, however, sampling intensity needs to be kept to the absolute minimum necessary for interpolation purposes. The aim of the present study was to examine the spatial variability in sward DM yield and mineral nutrient status in a large grass silage field under a three-cut system, and devise ‘optimal’ sampling strategies for mapping the distributions of these parameters at each cut. Herbage samples were collected from the field, prior to each harvest, at 25 m intervals in a regular rectangular grid to provide databases of herbage nutrient contents and DM yields. Different data combinations were abstracted from these databases for comparison purposes, and ordinary kriging used to produce interpolated maps of DM yield and sward N, P, K and S statuses. The results suggested that a sampling density of just seven samples per hectare was adequate for estimating the ‘true’ population means of sward DM yield and sward N, P, K, and S statuses. For mapping purposes, it was found that the best compromise between interpolation accuracy and sampling efficiency was to collect herbage samples in a 35.4 m×35.4 m equilateral triangular sampling pattern.

Journal

Precision AgricultureSpringer Journals

Published: Oct 3, 2004

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off