Investigating temporal and spatial patterns of cranberry yield in New Jersey fields

Investigating temporal and spatial patterns of cranberry yield in New Jersey fields Cranberries are grown in sensitive wetland ecosystems and precision farming could be beneficial to reduce agro-chemical pollution and increase production without expanding area. Precision farming requires knowledge of the variation of yield within-fields but cranberry harvesting methods produce only one yield value per field unless an expensive pre-harvest berry count is done. Co-operatives and extension services have an important role in precision farming to: (1) determine important factors affecting yield patterns within a growing region and (2) identify fields that would benefit most from future intensive survey. This paper reports a study to investigate temporal and spatial patterns in useable and poor quality cranberry yield for the New Jersey (NJ), USA growing region. Principal components analysis indicated that mean growing season temperature is important for understanding temporal patterns in useable yield and maximum temperatures and precipitation for poor quality yield. Multiple linear regression showed that some cultivars were susceptible to disease and poor quality yield in years with high maximum growing season temperatures. Analysis of spatial patterns using area to area and area to point kriging, local cluster analysis and geographically weighted regression helped identify clusters of fields that were consistently yielding or alternated between high and low yielding. They also showed differences between owners and soil types particularly in hot or wet years showing the different response to soil types to weather and the potential for improvement in irrigation practices by some owners. The methods used should be useful for other growing regions and crops, particularly where there are no yield monitors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Investigating temporal and spatial patterns of cranberry yield in New Jersey fields

Loading next page...
 
/lp/springer_journal/investigating-temporal-and-spatial-patterns-of-cranberry-yield-in-new-ps70L0dDSI
Publisher
Springer US
Copyright
Copyright © 2016 by Springer Science+Business Media New York
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.
10.1007/s11119-016-9471-8
Publisher site
See Article on Publisher Site

Abstract

Cranberries are grown in sensitive wetland ecosystems and precision farming could be beneficial to reduce agro-chemical pollution and increase production without expanding area. Precision farming requires knowledge of the variation of yield within-fields but cranberry harvesting methods produce only one yield value per field unless an expensive pre-harvest berry count is done. Co-operatives and extension services have an important role in precision farming to: (1) determine important factors affecting yield patterns within a growing region and (2) identify fields that would benefit most from future intensive survey. This paper reports a study to investigate temporal and spatial patterns in useable and poor quality cranberry yield for the New Jersey (NJ), USA growing region. Principal components analysis indicated that mean growing season temperature is important for understanding temporal patterns in useable yield and maximum temperatures and precipitation for poor quality yield. Multiple linear regression showed that some cultivars were susceptible to disease and poor quality yield in years with high maximum growing season temperatures. Analysis of spatial patterns using area to area and area to point kriging, local cluster analysis and geographically weighted regression helped identify clusters of fields that were consistently yielding or alternated between high and low yielding. They also showed differences between owners and soil types particularly in hot or wet years showing the different response to soil types to weather and the potential for improvement in irrigation practices by some owners. The methods used should be useful for other growing regions and crops, particularly where there are no yield monitors.

Journal

Precision AgricultureSpringer Journals

Published: Aug 23, 2016

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 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

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