Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility
Soil health plays a crucial role in crop production, both in terms of quality and quantity, highlighting the importance of effective methods for preserving soil quality to ensure global food security. Soil quality indices (SQIs) have been widely utilized as comprehensive measures of soil function by...
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/3/864 |
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| author | Hiba Chaudhry Hiteshkumar Bhogilal Vasava Songchao Chen Daniel Saurette Anshu Beri Adam Gillespie Asim Biswas |
| author_facet | Hiba Chaudhry Hiteshkumar Bhogilal Vasava Songchao Chen Daniel Saurette Anshu Beri Adam Gillespie Asim Biswas |
| author_sort | Hiba Chaudhry |
| collection | DOAJ |
| description | Soil health plays a crucial role in crop production, both in terms of quality and quantity, highlighting the importance of effective methods for preserving soil quality to ensure global food security. Soil quality indices (SQIs) have been widely utilized as comprehensive measures of soil function by integrating multiple physical, chemical, and biological soil properties. Traditional SQI analysis involves laborious and costly laboratory analyses, which limits its practicality. To overcome this limitation, our study explores the use of visible near-infrared (vis-NIR) spectroscopy as a rapid and non-destructive alternative for predicting soil properties and SQIs. This study specifically focused on seven soil indicators that contribute to soil fertility, including pH, organic matter (OM), potassium (K), calcium (Ca), magnesium (Mg), available phosphorous (P), and total nitrogen (TN). These properties play key roles in nutrient availability, pH regulation, and soil structure, influencing soil fertility and overall soil health. By utilizing vis-NIR spectroscopy, we were able to accurately predict the soil indicators with good accuracy using the Cubist model (R<sup>2</sup> = 0.35–0.93), offering a cost-effective and environmentally friendly alternative to traditional laboratory analyses. Using the seven soil indicators, we looked at three different approaches for calculating and predicting the SQI, including: (1) measured SQI (SQI_m), which is derived from laboratory-measured soil properties; (2) predicted SQI (SQI_p), which is calculated using predicted soil properties from spectral data; and (3) direct prediction of SQI (SQI_dp), The findings demonstrated that SQI_dp exhibited a higher accuracy (R<sup>2</sup> = 0.90) in predicting soil quality compared to SQI_p (R<sup>2</sup> = 0.23). |
| first_indexed | 2024-03-08T03:48:30Z |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-03-08T03:48:30Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-195983d20f4b4212bd40d58e4e82ded22024-02-09T15:22:04ZengMDPI AGSensors1424-82202024-01-0124386410.3390/s24030864Evaluating the Soil Quality Index Using Three Methods to Assess Soil FertilityHiba Chaudhry0Hiteshkumar Bhogilal Vasava1Songchao Chen2Daniel Saurette3Anshu Beri4Adam Gillespie5Asim Biswas6School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaZJU-Hangzhou Global Scientific and Technological Innovation Center, Xiaoshan District, Hangzhou 311215, ChinaSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaSchool of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, CanadaSoil health plays a crucial role in crop production, both in terms of quality and quantity, highlighting the importance of effective methods for preserving soil quality to ensure global food security. Soil quality indices (SQIs) have been widely utilized as comprehensive measures of soil function by integrating multiple physical, chemical, and biological soil properties. Traditional SQI analysis involves laborious and costly laboratory analyses, which limits its practicality. To overcome this limitation, our study explores the use of visible near-infrared (vis-NIR) spectroscopy as a rapid and non-destructive alternative for predicting soil properties and SQIs. This study specifically focused on seven soil indicators that contribute to soil fertility, including pH, organic matter (OM), potassium (K), calcium (Ca), magnesium (Mg), available phosphorous (P), and total nitrogen (TN). These properties play key roles in nutrient availability, pH regulation, and soil structure, influencing soil fertility and overall soil health. By utilizing vis-NIR spectroscopy, we were able to accurately predict the soil indicators with good accuracy using the Cubist model (R<sup>2</sup> = 0.35–0.93), offering a cost-effective and environmentally friendly alternative to traditional laboratory analyses. Using the seven soil indicators, we looked at three different approaches for calculating and predicting the SQI, including: (1) measured SQI (SQI_m), which is derived from laboratory-measured soil properties; (2) predicted SQI (SQI_p), which is calculated using predicted soil properties from spectral data; and (3) direct prediction of SQI (SQI_dp), The findings demonstrated that SQI_dp exhibited a higher accuracy (R<sup>2</sup> = 0.90) in predicting soil quality compared to SQI_p (R<sup>2</sup> = 0.23).https://www.mdpi.com/1424-8220/24/3/864soil quality indexspectroscopyfertility analysissoil health indicators |
| spellingShingle | Hiba Chaudhry Hiteshkumar Bhogilal Vasava Songchao Chen Daniel Saurette Anshu Beri Adam Gillespie Asim Biswas Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility Sensors soil quality index spectroscopy fertility analysis soil health indicators |
| title | Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility |
| title_full | Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility |
| title_fullStr | Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility |
| title_full_unstemmed | Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility |
| title_short | Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility |
| title_sort | evaluating the soil quality index using three methods to assess soil fertility |
| topic | soil quality index spectroscopy fertility analysis soil health indicators |
| url | https://www.mdpi.com/1424-8220/24/3/864 |
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