Abstract
Core Ideas One‐time tillage increased soybean yield as a result of improving soil physical properties. Penetration resistance, air capacity, macroporosity, relative field capacity, and S index were the soil physical properties that best predicted soybean yield. The most sensitive soil physical properties for detecting structural related alterations were equally important for predicting soybean yield. Penetration resistance is the indicator that addresses no‐tillage soil compaction and its effect on soybean yield. Soil compaction can significantly reduce crop yield. Our objective was to identify the most sensitive soil physical property and process indicators related to crop yield using a Random Forest algorithm (RFA). This machine‐learning, decision‐making tool was used with field‐scale data from five soil management treatments designed to ameliorate compaction in no‐tillage (NT) fields. The treatments were: T1, NT for 10 yr (control); T2, NT with surface application of 3.6 Mg ha −1 of agricultural gypsum; T3, NT with subsoiling plus 1.44 Mg ha −1 of highly reactive limestone applied to a depth of 0.60 m; T4, NT planting following chisel plowing at a depth of 0.26 m; and T5, NT with subsoiling to a depth of 0.60 m plus 1.44 Mg ha −1 of surface‐applied, highly reactive limestone. Fifteen soil physical properties and processes related to growth and yield of soybean [ Glycine ma x (L.) Merr.] were measured. Mechanical intervention, specifically subsoiling, improved soil physical properties and increased soybean yield cultivated following occasional tillage. The RFA ranked penetration resistance (PR), air capacity, macroporosity, relative field capacity, and the Dexter‐S index as the most sensitive soil physical indicators affecting soybean yield. Those indicators were also sensitive to changes in soil structure due to subsoiling. We conclude that the RFA was an effective tool for screening indicators and that those chosen can be effective for monitoring soil compaction and its effect on soybean yield. Penetration resistance may be used to guide on‐farm decision‐making regarding when and how NT soil compaction should be addressed.
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Claims 7
Claim · model-written summary
Subsoiling increased soybean yield in no-till fields after occasional tillage
- Taxon
- soybean
Glycine maxe2 - Treatment
- subsoilinge1
- Outcome
- soybean yielde1
- Direction
- increasede1
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e1“Mechanical intervention, specifically subsoiling, improved soil physical properties and increased soybean yield cultivated following occasional tillage”
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
Claim · model-written summary
Subsoiling improved soil physical properties in no-till soils
- Taxon
- soybeanGlycine maxe2
- Treatment
- subsoilinge1
- Outcome
- soil physical propertiese1
- Direction
- improvede1
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e1“Mechanical intervention, specifically subsoiling, improved soil physical properties and increased soybean yield cultivated following occasional tillage”
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
Claim · model-written summary
Penetration resistance, air capacity and macroporosity ranked as the most sensitive soil physical indicators affecting soybean yield
- Taxon
- soybeanGlycine maxe2
- Outcome
- most sensitive soil physical indicators affecting soybean yielde3
- Qualifier
- penetration resistance (PR), air capacity, macroporositye3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
e3“The RFA ranked penetration resistance (PR), air capacity, macroporosity, relative field capacity, and the Dexter‐S index as the most sensitive soil physical indicators affecting soybean yield”
Claim · model-written summary
Relative field capacity and the Dexter-S index ranked among the most sensitive soil physical indicators affecting soybean yield
- Taxon
- soybeanGlycine maxe2
- Outcome
- most sensitive soil physical indicators affecting soybean yielde3
- Qualifier
- relative field capacity, and the Dexter‐S indexe3
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
e3“The RFA ranked penetration resistance (PR), air capacity, macroporosity, relative field capacity, and the Dexter‐S index as the most sensitive soil physical indicators affecting soybean yield”
Claim · model-written summary
The most sensitive indicators were also sensitive to soil structure changes caused by subsoiling
- Taxon
- soybeanGlycine maxe2
- Treatment
- subsoilinge4
- Outcome
- sensitive to changes in soil structuree4
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
e4“Those indicators were also sensitive to changes in soil structure due to subsoiling”
Claim · model-written summary
Penetration resistance may guide on-farm decisions on when and how no-till compaction should be addressed in soybean
- Taxon
- soybeanGlycine maxe2
- Outcome
- when and how NT soil compaction should be addressede5
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
e5“Penetration resistance may be used to guide on‐farm decision‐making regarding when and how NT soil compaction should be addressed”
Claim · model-written summary
The random forest approach was an effective tool for screening soil physical indicators for soybean yield
- Taxon
- soybeanGlycine maxe2
- Outcome
- effective tool for screening indicatorse6
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e2“Fifteen soil physical properties and processes related to growth and yield of soybean”
e6“We conclude that the RFA was an effective tool for screening indicators and that those chosen can be effective for monitoring soil compaction and its effect on soybean yield”
The same questions in other papers
tillage · yield · Glycine max (soybean)Positive and negative results
263 papers in the same direction as this paper · 100 in the opposite direction · 26 reporting no difference from an alternative
- positive
- no effect
- no effect
386 papers more in this group
See all 390 papers →Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.