English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Ensuring that crops use water and nutrients efficiently is an importantstrategy for increasing the profitability of farming and reducing theenvironmental load from agriculture. Subsurface irrigation can be analternative to surface irrigation as a means of losing less irrigation water,but the application timing and amount are often difficult to determine.Well-defined soil and crop models are useful for assisting decision support,but most of the models developed to date have been for surface irrigation. Thepresent study examines whether the Decision Support System for AgrotechnologyTransfer (DSSAT, version 4.5) cropping system model is applicable for theproduction of processing tomatoes with subsurface irrigation, and it revisesthe soil module to simulate irrigation schemes with subsurface irrigation. Fivefarmed fields in California, USA, are used to test the performance of themodel. The original DSSAT model fails to produce fruit yield by overestimatingthe water deficiency. The soil water module is then revised by introducing themovement of soil moisture due to a vertical soil moisture gradient. Moreover,an external parameter optimization system is constructed to minimize the errorbetween the simulation and observations. The revised module reduces the errorsin the soil moisture profile at each field compared to those by the originalDSSAT model. The average soil moisture error decreases from 0.065m^3/m^3 to0.029m^3/m^3. The yields estimated by the modified model are in a reasonablerange from 80 to 150 ton/ha, which is commonly observed under well-managedconditions. The present results show that although further testing is requiredfor yield prediction, the present modification to the original DSSAT modelimproves the precision of the soil moisture profile under subsurface irrigationand can be used for decision support for efficient producting of processingtomatoes.

Improving the soil water module of the Decision Support System for Agrotechnology Transfer cropping system model for subsurface irrigation