Random forest, an efficient smart technique for analyzing the influence of soil properties on pistachio yield

Seyedmohammadi, Javad; Navidi, Mir Naser; Zeinadini, Ali; McDowell, Richard W.

doi:10.1007/s10668-023-03926-2

Environ Dev Sustain

2024

DOI: 10.1007/s10668-023-03926-2

|View full text |Cite

Random forest, an efficient smart technique for analyzing the influence of soil properties on pistachio yield

Javad Seyedmohammadi,

Mir Naser Navidi,

Ali Zeinadini

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 5 publications

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang: a comprehensive study

Wang,

Xie

et al. 2024

J Sci Food Agric

View full text Add to dashboard Cite

BackgroundOptimizing biochar application is vital for enhancing crop production and ensuring sustainable agricultural production. A 3‐year field experiment was established to explore the effects of varying biochar application rates (BAR) on crop growth, quality, productivity, and yields. The BAR were set at 0, 10, 50, and 100 t ha–1 in 2018, 0, 10, 25, 50, and 100 t ha–1 in 2019, and 0, 10, 25, and 30 t ha–1 in 2020. Crop quality and growth status and production were evaluated using DTOPSIS‐EW, PCA, MFA, GRA, and fuzzy Borda combination evaluation method.Results(1) Low‐dose BAR (≤25 t ha–1 for cotton; ≤50 t ha–1 for sugar beet) effectively increased biomass, plant height, leaf area index (LAI), water and fertility (N, P, and K) productivities, and yield. Biochar application increased the salt absorption and sugar content in sugar beet, with the most notable increases being 116.45% and 20.35%, respectively. Conversely, BAR had no significant effect on cotton fiber quality; (2) GRA method was the most appropriate for assessing crop growth and quality; (3) The most indicative parameters for reflecting cotton and sugarbeet growth and quality status were biomass and LAI. (4) The 10 t ha–1 BAR consistently produced the highest scores and was the most economically viable option, as evaluated by DTOPSIS‐EW.ConclusionThe optimal biochar application strategy for improving cotton and sugar beet cultivation in Xinjiang, China, is 10 t ha–1 biochar applied continuously.This article is protected by copyright. All rights reserved.

show abstract

Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang: a comprehensive study

Wang,

Xie

et al. 2024

J Sci Food Agric

View full text Add to dashboard Cite

show abstract

Source apportionment and risk assessment of soil heavy metals in the Huangshui River Basin using a hybrid model

Zhou,

Yu,

Guo

et al. 2024

Ecological Indicators

View full text Add to dashboard Cite

Source analysis and distribution prediction of soil heavy metals in a typical area of the Qinghai-Tibet Plateau

Zha,

Deng,

Jiang

et al. 2024

Ecological Indicators

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Random forest, an efficient smart technique for analyzing the influence of soil properties on pistachio yield

Cited by 5 publications

References 53 publications

Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang: a comprehensive study

Optimizing biochar application for enhanced cotton and sugar beet production in Xinjiang: a comprehensive study

Source apportionment and risk assessment of soil heavy metals in the Huangshui River Basin using a hybrid model

Source analysis and distribution prediction of soil heavy metals in a typical area of the Qinghai-Tibet Plateau

Contact Info

Product

Resources

About