Identification of significant factors affecting potato tuber yield for precision management of soil nutrients

Humna Khan, Travis J. Esau, Aitazaz A. Farooque, Farhat Abbas, Qamar Uz Zaman, Ryan Barrett, Bishnu Acharya

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The development of precision agricultural technologies for an adequate potato tuber yield requires knowledge and understanding of significant factors affecting crop growth and its yield. This study was designed to identify the significant factors responsible for fluctuations in tuber yield within the potato fields. The field experiments were conducted during potato growing seasons of 2017 and 2018 in the region of Souris alongside the LaPierre Lane in Prince Edward Island (PEI), Canada. Both fields were under conventional farming and received traditionally recommended agronomic practices and amounts of agrochemicals over the past decade. Grids of 25 x 25 m2 were established to collect horizontal coplanar geometry of ground electrical conductivity (HCP). The soil samples were collected from the same grids to determine soil organic matter content (SOM), pH, Lime Index (LI), phosphorous (P), potassium (K), calcium (Ca), Iron (Fe), cation exchange capacity (CEC) and %P/Al (P aluminum ratio). The soil moisture content (θ) was recorded using time domain reflectometry (TDR) probes. The normalized difference vegetative index (NDVI) was recorded using GreenSeekerTM. Potato tuber yield was collected manually from 0.91 x 3 m2 strips at the same grids. Results revealed that the selected soil and crop properties showed a low, moderate, and high variability and spatial dependence within the fields. Tuber yield had significant (p < 0.001) correlations with HCP, θ, SOM, and P during the first sampling at the beginning of the growing season. However, during the second sampling, the tuber yield was significantly correlated with HCP, θ, NDVI, SOM, P, and K. Stepwise regression (through backward elimination at α = 0.01) excluded the low important variables namely P and K leaving HCP, θ, SOM, and NDVI as the most influential variables for tuber yield. However, these influential variables had significant correlations with soil P and K. Results of this study suggested that managing the crop inputs based on these influential variables has a significant potential to enhance tuber yield.

Original languageEnglish
Pages (from-to)535-545
Number of pages11
JournalApplied Engineering in Agriculture
Volume37
Issue number3
DOIs
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • Precision agriculture
  • Regression analysis
  • Sensors
  • Site-specific nutrient management
  • Spatial variability

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