Continuous Field Monitoring of Growth and Thickness Variation in a Potato Tuber Using a Strain-Gauge Sensor

Real-time measurement of belowground tuber growth has not been conducted in field crops. Here, a strain-gauge sensor was used to monitor the growth of a single potato tuber and estimate its daily water loss. Over the 11 days preceding harvest, tuber thickness increased by 0.80 mm, corresponding to a daily gain of 1.4 g, or a 4.2% increase. The greatest diurnal fluctuation was 0.439 mm, corresponding to a transpirational water loss of 9.1 mL, or 2.9% of the tuber’s water content. Daily estimated transpiration showed a positive correlation with estimated vapor pressure deficit. This sensor may enable more precise input control and higher temporal resolution than current methods for below-ground crops, supporting improved crop management, yield prediction, and harvest decisions.

Authors

Institutions

Publication Details

Journal
Agronomy
Published
2026-09-14
DOI
https://doi.org/10.3390/agronomy16181803
Primary Topic
Potato Plant Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Continuous Field Monitoring of Growth and Thickness Variation in a Potato Tuber Using a Strain-Gauge Sensor

Steven O. Link
Agronomy
Potato Plant Research
article

Continuous Field Monitoring of Growth and Thickness Variation in a Potato Tuber Using a Strain-Gauge Sensor

Steven O. Link
article en

Abstract

Real-time measurement of belowground tuber growth has not been conducted in field crops. Here, a strain-gauge sensor was used to monitor the growth of a single potato tuber and estimate its daily water loss. Over the 11 days preceding harvest, tuber thickness increased by 0.80 mm, corresponding to a daily gain of 1.4 g, or a 4.2% increase. The greatest diurnal fluctuation was 0.439 mm, corresponding to a transpirational water loss of 9.1 mL, or 2.9% of the tuber’s water content. Daily estimated transpiration showed a positive correlation with estimated vapor pressure deficit. This sensor may enable more precise input control and higher temporal resolution than current methods for below-ground crops, supporting improved crop management, yield prediction, and harvest decisions.

AgronomyVol. 16(18)
Agricultural University of Iceland (IS)
Zero hunger
Openalex Percentile: Top 13%
Potato Plant Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.