Cover crop termination options and application of remote sensing for evaluating termination efficiency

Kumar, Vipin; Singh, Vijay P.; Flessner, Michael L.; Haymaker, Joseph; Reiter, Mark S.; Mirsky, Steven B.

doi:10.1371/journal.pone.0284529

Cited by 5 publications

(3 citation statements)

References 52 publications

(69 reference statements)

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“…In the Midwestern United States, herbicide burndown is a common cover crop termination method, used to mitigate nutrient competition and ensure a release of any scavenged nutrients back to the field (Jewett and Thelen, 2007;Palhano et al, 2018;Adetunji et al, 2020). A widely used commercial herbicide for this strategy is glyphosate (Kumar et al, 2023). While herbicidal desiccation of residual cover crop biomass increases soil nutrient levels (Jewett and Thelen, 2007), the use of glyphosate has also been associated with decreased soil biological activity and microbial diversity (Busse et al, 2001;Nguyen et al, 2016), as well as adverse non-target effects on human and environmental health (Kanissery et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

On-farm biomass recycling with biostimulant Re-Gen increases corn yields in multi-year farm trials

Gibson,

Ziobron,

Olson

et al. 2024

Preprint

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The United States produced 15.1 billion bushels of corn for grain in 2023, relying on harmful synthetic chemicals such as fertilizer and pesticides to ensure high yields. This dependency on agrochemicals has negatively impacted the environment and soil microbiome, therefore, there is a need to rebuild soil health by implementing regenerative agricultural practices. One increasingly utilized regenerative practice is the application of biostimulants, or microbial inoculants that can rebuild soil health and productivity. A multi-year corn trial was conducted to quantify the impact of Re-Gen, a biostimulant invented to degrade woody biomass and increase nutrient bioavailability in the soil, to increase corn yield at a dairy farm in Ferrisburgh, Vermont. Over the two-year trial, Re-Gen application on corn stover and cover crop residues increased corn bushels per acre by 24% and increased tons of corn silage per acre by 12.5-30%, depending on the field. Soil nutrient analysis and plant tissue analysis showed increased nutrients, particularly in one trial field. Multi-year Re-Gen application showed increased monetary value, indicating that the effects of Re-Gen do not diminish with multiple applications. Further investigation into the mechanism suggests that increased phosphatase production stimulated by Re-Gen could contribute to increased phosphorus bioavailability in the soil and uptake in the tissue, potentially increasing yields. These results highlight the potential for Re-Gen to foster regenerative agriculture processes while also increasing yield and, therefore, revenue for corn farmers in the United States.

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Section: Discussionmentioning

confidence: 99%

On-farm biomass recycling with biostimulant Re-Gen increases corn yields in multi-year farm trials

Gibson,

Ziobron,

Olson

et al. 2024

Preprint

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“…Localized economic information is essential to promote adoption [29]. Even though many farmers are, in general, very interested in using satellite and drone images to aid decision-making [63][64][65], they did not highlight remote sensing in their free word answers despite the potential.…”

Section: Farmers' To-do List For Research To Support Success With Cov...mentioning

confidence: 99%

Finnish Farmers Feel They Have Succeeded in Adopting Cover Crops but Need Down-to-Earth Support from Research

Peltonen-Sainio,

Jauhiainen,

Känkänen

2023

Agronomy

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In Finland, there is an ongoing adoption and learning process considering the cultivation of cover crops (CCs). The primary aim is to claim the benefits of CCs for agricultural production and ecosystems, which are both appreciated by Finnish farmers. A farmer survey with 1130 respondents was carried out to build an up-to-date understanding of how farmers have succeeded with CCs and whether they intend to continue with the use of CCs and to collect farmers’ views on knowledge gaps that should be filled by research or better knowledge sharing. The studied groups were farmers who had selected CCs as a registered measure in 2020 to receive agricultural payments. Data came from the Finnish Food Authority. Organic farmers were slightly more positive: they have had longer experience with CCs, but organic production is also more dependent on the ecosystem services provided by CCs. A high share of respondents agreed that their experiences with CCs have improved over time and were confident that CCs had become a permanent element of their production systems. Most of the farmers also agreed that the area under CCs would expand significantly in Finland and considered the cultivation of CCs as an effective measure to improve soil conditions. They often considered that challenges in adopting CCs were exaggerated and disagreed that bad experiences prevented them from expanding or continuing the use of CCs. The agricultural payment available for Finnish farmers to support the cultivation of CCs is quite reasonable (EUR 97 + EUR 50 per hectare) to compensate for any economic risks of CCs. Free word answers from the farmers highlighted research needs (in descending order) in the following areas: crop protection, sowing practices, the use of diverse CCs and their mixtures, and impacts on yield and profitability. Many of these are universal, i.e., have been reported elsewhere. Younger farmers (≤50 years) highlighted profitability, which is, in many European countries, a key barrier to the deployment of CCs. Farmers from the east and north regions, where the growing season is short, highlighted alternative CC choices as a knowledge gap.

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“…Given the growing popularity and potential benefits of cover crops, FHTPP emerges as a promising tool, capable of quantifying the AGB accumulation process in a non-destructive way with notable efficiency. Multispectral imaging has been employed to establish a correlation with the termination efficiency rating for various cover crop species ( Kumar et al., 2023 ). High-resolution satellite images were used to estimate cover crop biomass, achieving the highest correlation coefficient (R) of 0.74 ( Kharel et al., 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models

Bai,

Koehler-Cole,

Scoby

et al. 2024

Front. Plant Sci.

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Incorporating cover crops into cropping systems offers numerous potential benefits, including the reduction of soil erosion, suppression of weeds, decreased nitrogen requirements for subsequent crops, and increased carbon sequestration. The aboveground biomass (AGB) of cover crops strongly influences their performance in delivering these benefits. Despite the significance of AGB, a comprehensive field-based high-throughput phenotyping study to quantify AGB of multiple cover crops in the U.S. Midwest has not been found. This study presents a two-year field experiment carried out in Eastern Nebraska, USA, to estimate AGB of five different cover crop species [canola (Brassica napus L.), rye (Secale cereale L.), triticale (Triticale × Triticosecale L.), vetch (Vicia sativa L.), and wheat (Triticum aestivum L.)] using high-throughput phenotyping and Machine Learning (ML) models. Destructive AGB sampling was performed three times during each spring season in 2022 and 2023. An array of morphological, spectral, thermal, and environmental features from the sensors were utilized as feature inputs of ML models. Moderately strong linear correlations between AGB and the selected features were observed. Four ML models, namely Random Forests Regression (RFR), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), and Artificial Neural Network (ANN), were investigated. Among the four models, PLSR achieved the highest Coefficient of Determination (R2) of 0.84 and the lowest Root Mean Squared Error (RMSE) of 892 kg/ha (Normalized RMSE (NRMSE) = 8.87%), indicating that PLSR could be the most appropriate method for estimating AGB of multiple cover crop species. Feature importance analysis ranked spectral features like Normalized Difference Red Edge (NDRE), Solar-induced Fluorescence (SIF), Spectral Reflectance at 485 nm (R485), and Normalized Difference Vegetation Index (NDVI) as top model features using PLSR. When utilizing fewer feature inputs, ANN exhibited better prediction performance compared to other models. Using morphological and spectral parameters as input features alone led to a R2 of 0.80 and 0.77 for AGB prediction using ANN, respectively. This study demonstrated the feasibility of high-throughput phenotyping and ML techniques for accurately estimating AGB of multiple cover crop species. Further enhancement of model performance could be achieved through additional destructive sampling conducted across multiple locations and years.

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Cover crop termination options and application of remote sensing for evaluating termination efficiency

Cited by 5 publications

References 52 publications

On-farm biomass recycling with biostimulant Re-Gen increases corn yields in multi-year farm trials

On-farm biomass recycling with biostimulant Re-Gen increases corn yields in multi-year farm trials

Finnish Farmers Feel They Have Succeeded in Adopting Cover Crops but Need Down-to-Earth Support from Research

Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models

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