Open Journal Systems

Embracing smart irrigation management techniques empowers growers to irrigate with greater efficiency, thereby promoting sustainable agricultural production. In this context, growers often rely on crop evapotranspiration (ETc) as a key factor in making informed irrigation decisions, underscoring the significance of accurately determining and spatially mapping crop water status. Technological progress, exemplified by the emergence of unmanned aerial vehicles (UAVs), has brought about a revolutionary shift in agricultural monitoring. UAV platforms can capture high-resolution images with centimeter-level spatial accuracy and offer higher temporal coverage compared to satellite imagery. Considering these advancements, this study introduces a robust method for classifying water stress in cotton using a compact UAV platform and convolutional neural networks (CNN). The experiment was conducted at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, where the cotton field was divided into 12 drip zones. The study included three replications to evaluate four irrigation treatments: “rainfed”, “full irrigation”, “percent deficit of full irrigation”, and “time delay of full irrigation”. The results demonstrated that the CNN model successfully classified the cotton water stress using the UAV-based RGB image, achieving an overall best prediction accuracy of approximately 91%. By segmenting the original cotton images into separate canopy and soil areas using morphological image processing methods, the authors also isolated and analyzed the individual contributions of these components to cotton water stress. Additionally, a random forest classifier revealed the relative importance of different image features in the classification process through feature importance analysis. These findings highlighted the state-of-the-art performance of the proposed system in cotton water stress classification and provided valuable insights into the key image features contributing to accurate classification. The authors concluded that integrating UAV-based RGB imagery and CNN models had great potential for assessing water stress in cotton.

A new approach to measure spatial variability of soil parameters and field technique to test-value specific fertilizer

Information on the distribution of soil properties is important to know the status of nutrients in the soils based on which fertilizer nutrients are recommended. Given the variability of nutrients in the soils, making a site-specific fertilizer recommendation seems to be a compelling work. To determine the spatial variability of soil nutrients and to make judicious and precise fertilizer recommendations, new measures are designed with this study. These measures are tested against the soil samples (n = 43) for total nitrogen (N), organic matter (OM), phosphorus (P2O5), and potassium (K2O) in the study area. The descriptive statistical analysis indicated an average of low nitrogen and organic matter, while phosphorus was found to be very high and the level of potassium was high. The spread of nutrients across the data sets, however, included low, medium, high, and very high levels of ratings. The Deviation Square Index was developed and applied for the variability measurement and found that the largest variation was with phosphorus distribution, followed by potassium, nitrogen, and organic matter. The coefficient of variation (CV%) analysis also exhibited similar trends in nutrient distributions. Nitrogen was the main determinant explaining the variations in rice yield, while phosphorus and potash were negatively related to the yield. An index of fertilizer nutrient recommendation called Test-Value Specific Dose (TVSD) was developed and used to calculate the nutrient recommendation for each sampled location. This new method gave easy and more accurate doses of fertilizer over the blanket recommendation to fit the variations across the soil samples.

Root exudates from weedy ryegrass hybrid type and selected crop plants affect soil microbial communities in two soil types of the Western Cape, South Africa

Michael Ignatius Ferreira, Anélia Marais, Alfred Botha, Carl Frederick Reinhardt, Marieta van der Rijst

Article ID: 2378
Vol 4, Issue 2, 2023

DOI: https://doi.org/10.54517/ama.v4i2.2378
VIEWS - 2050 (Abstract)

Download PDF

Abstract

All growing plant roots have the ability to produce root exudates to which soil microbes are attracted. The objective of this study was to utilise the Biolog EcoPlate™ system to indicate the impact of soil type on soil microbial communities in the rhizosphere following treatment with pot leachates that contain various plant root exudates. A greenhouse experiment was conducted in 2021 and repeated in 2022 from May until July (southern hemisphere) in this winter rainfall area with Mediterranean climatic conditions. This ensured that natural daylight hours in the greenhouse coincided with those experienced in the field by winter-growing crops, from seeding until maturity (May to October). Pot leachate that contained various plant root exudates from six donor plant species (wheat, barley, two lupine cultivars, ryegrass pasture type, and weedy ryegrass hybrid type) was utilised as treatment for respective recipient pots, in which wheat (Triticum aestivum v. SST 027) was grown as a test plant. Recipient plants were grown in two sets of pots, each with two different soil types. Soil samples from recipient pots were used to inoculate the Biolog EcoPlate™ system, and the carbon utilisation patterns obtained in this process were compared to the soil microbial populations present in the soil samples collected prior to treatments. Pot leachate treatment effects on the two soil types differed. Similarly, the treatments had differential effects on the measured soil microbial populations of the recipient wheat plants. Results indicate that the pattern of substrate utilisation by the Biolog EcoPlate™ methodology indicates changes in the number of colony forming units in the soil. In this regard, it was clear that ryegrass pasture variety and weedy ryegrass hybrid type caused similar effects on the soil bacteria communities in the rhizosphere. It is concluded that the primary impact of soil type is distinct microbial communities as an important factor regulating plant and plant-microbe synergy. Secondly, due to the strong selective forces root exudates have on the soil microbiome, conspicuous microbial communities in the rhizosphere of each plant species will continue to develop over time.

Keywords

Biolog EcoPlate™ system; microbiome; pot leachate; rhizosphere; soil microbes

References

1. Bertin C, Yang X, Weston LA. The role of root exudates and allelochemicals in the rhizosphere. Plant and Soil 2003; 256(1): 67–83. doi: 10.1023/a: 1026290508166

2. Bashir O, Khan K, Hakeem KR, et al. Soil microbe diversity and root exudates as important aspects of rhizosphere ecosystem. In: Hakeem KR, Akhtar MS (editor). Plant, Soil and Microbes. Springer; 2016. Volume 2. pp. 337–357. doi: 10.1007/978-3-319-29573-2_15

3. Kong CH, Wang P, Zhao H, et al. Impact of allelochemical exuded from allelopathic rice on soil microbial community. Soil Biology and Biochemistry. 2008, 40(7): 1862–1869. doi: 10.1016/j.soilbio.2008.03.009

4. Jain A, Chakraborty J, Das S. Underlying mechanism of plant–microbe crosstalk in shaping microbial ecology of the rhizosphere. Acta Physiologiae Plantarum 2020; 42(1): 8. doi: 10.1007/s11738-019-3000-0

5. Wang N, Kong C, Wang P, Meiners SJ. Root exudate signals in plant–plant interactions. Plant, Cell & Environment 2020; 44(4): 1044–1058. doi: 10.1111/pce.13892

6. Olanrewaju OS, Ayangbenro AS, Glick BR, Babalola OO. Plant health: Feedback effect of root exudates-rhizobiome interactions. Applied Microbiology and Biotechnology 2018; 103(3): 1155–1166. doi: 10.1007/s00253-018-9556-6

7. Cipollini D, Rigsby CM, Barto EK. Microbes as targets and mediators of allelopathy in plants. Journal of Chemical Ecology 2012; 38(6): 714–727. doi: 10.1007/s10886-012-0133-7

8. Canarini A, Kaiser C, Merchant A, et al. Root exudation of primary metabolites: Mechanisms and their roles in plant responses to environmental stimuli. Frontiers in Plant Science 2019; 10. doi: 10.3389/fpls.2019.00157

9. Feng H, Zhang N, Du W, et al. Identification of chemotaxis compounds in root exudates and their sensing chemoreceptors in plant-growth-promoting rhizobacteria Bacillus amyloliquefaciens SQR9. Molecular Plant-Microbe Interactions® 2018; 31(10): 995–1005. doi: 10.1094/mpmi-01-18-0003-r

10. Zwetsloot MJ, Kessler A, Bauerle TL. Phenolic root exudate and tissue compounds vary widely among temperate forest tree species and have contrasting effects on soil microbial respiration. New Phytologist 2018; 218(2): 530–541. doi: 10.1111/nph.15041

11. Kuzyakov Y, Blagodatskaya E. Microbial hotspots and hot moments in soil: Concept & review. Soil Biology and Biochemistry 2015; 83: 184–199. doi: 10.1016/j.soilbio.2015.01.025

12. Lakshmanan V, Selvaraj G, Bais HP. Functional soil microbiome: Belowground solutions to an aboveground problem. Plant Physiology 2014; 166(2): 689–700. doi: 10.1104/pp.114.245811

13. Williams A, Langridge H, Straathof AL, et al. Comparing root exudate collection techniques: An improved hybrid method. Soil Biology and Biochemistry 2021; 161: 108391. doi: 10.1016/j.soilbio.2021.108391

14. Fernandez C, Santonja M, Gros R, et al. Allelochemicals of Pinus halepensis as drivers of biodiversity in mediterranean open mosaic habitats during the colonization stage of secondary succession. Journal of Chemical Ecology 2013; 39(2): 298–311. doi: 10.1007/s10886-013-0239-6

15. Garland JL, Mills AL. Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization. Applied and Environmental Microbiology 1991; 57(8): 2351–2359. doi: 10.1128/aem.57.8.2351-2359.1991

16. Garland JL, Campbell CD, Mills AL. Physiological profiling of microbial communities. In: Hurst CJ, Crawford RL, Garland JL, et al. (editors). Manual of Environmental Microbiology. ASM Press; 2007. pp. 126–138. doi: 10.1128/9781555815882.ch11

17. Juhanson J, Truu J, Heinaru E, Heinaru A. Temporal dynamics of microbial community in soil during phytoremediation field experiment. Journal of Environmental Engineering and Landscape Management 2007; 15(4): 213–220. doi: 10.3846/16486897.2007.9636933

18. Olsen RA, Bakken LR. Viability of soil bacteria: Optimization of plate-counting technique and comparison between total counts and plate counts within different size groups. Microbial Ecology 1987; 13(1): 59–74. doi: 10.1007/bf02014963

19. Ellis RJ, Morgan P, Weightman AJ, Fry JC. Cultivation-dependent and -independent approaches for determining bacterial diversity in heavy-metal-contaminated soil. Applied and Environmental Microbiology 2003; 69(6): 3223–3230. doi: 10.1128/aem.69.6.3223-3230.2003

20. Moretti G, Matteucci F, Ercole C, et al. Microbial community distribution and genetic analysis in a sludge active treatment for a complex industrial wastewater: A study using microbiological and molecular analysis and principal component analysis. Annals of Microbiology 2015; 66(1): 397–405. doi: 10.1007/s13213-015-1122-1

21. Zhang C, Wang J, Qian B, Li W. Effects of the invader Solidago canadensis on soil properties. Applied Soil Ecology 2009; 43(2–3): 163–169. doi: 10.1016/j.apsoil.2009.07.001

22. Marais A, Hardy M, Morris C, Botha A. Measuring culturable microbial populations and filamentous microbial growth in soil of wheat plots subjected to crop rotation and monoculture. South African Journal of Plant and Soil 2010; 27(2): 133–141.

23. Marais A, Ferreira MI, Booyse M, Botha A. The effects of the herbicide roundup on some populations of soil microbes (Afrikaans). Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 2011; 30(1): 43. doi: 10.4102/satnt.v30i1.43

24. Lorenzo P, Pereira CS, Rodríguez-Echeverría S. Differential impact on soil microbes of allelopathic compounds released by the invasive Acacia dealbata Link. Soil Biology and Biochemistry 2013; 57: 156–163. doi: 10.1016/j.soilbio.2012.08.018

25. Ferreira M, Reinhardt C, Rijst M, et al. Allelopathic root leachate effects of Lolium multiflorum × L. perenne on crops and the concomitant changes in metabolic potential of the soil microbial community as indicated by the Biolog Ecoplate™. International Journal of Plant & Soil Science 2017; 19(5): 1–14. doi: 10.9734/ijpss/2017/36918

26. Qu T, Du X, Peng Y, et al. Invasive species allelopathy decreases plant growth and soil microbial activity. PLoS One 2021; 16(2): e0246685. doi: 10.1371/journal.pone.0246685

27. Grayston SJ, Wang S, Campbell CD, Edwards AC. Selective influence of plant species on microbial diversity in the rhizosphere. Soil Biology and Biochemistry 1998; 30(3): 369–378. doi: 10.1016/s0038-0717(97)00124-7

28. Schloter M, Nannipieri P, Sørensen SJ, van Elsas JD. Microbial indicators for soil quality. Biology and Fertility of Soils 2017; 54(1): 1–10. doi: 10.1007/s00374-017-1248-3

29. Sasse J, Martinoia E, Northen T. Feed your friends: Do plant exudates shape the root microbiome? Trends in Plant Science 2018; 23(1): 25–41. doi: 10.1016/j.tplants.2017.09.003

30. Németh I, Molnár S, Vaszita E, Molnár M. The Biolog EcoPlate™ technique for assessing the effect of metal oxide nanoparticles on freshwater microbial communities. Nanomaterials 2021; 11(7): 1777. doi: 10.3390/nano11071777

31. Atlas RM. Fastidious anaerobe agar. In: Parks LC (editor). Handbook of Microbiological Media, 2nd ed. CRC Press; 1993. p. 666.

32. Ferreira MI, Reinhardt CF, Lamprecht SC, et al. Morphological identification of the ryegrass hybrid Lolium multiflorum × Lolium perenne and isolation of the pathogen Fusarium pseudograminearum in the Western cape. South African Journal of Plant and Soil 2015; 32(1): 9–15. doi: 10.1080/02571862.2014.994140

33. Soil Classification Working Group. Soil Classification: A Taxonomic System for Southern Africa. Department of Agricultural Development; 1991. pp. 1–152.

34. Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika 1965; 52(3–4): 591–611. doi: 10.1093/biomet/52.3-4.591

35. Levene H. Robust test for equality of variances. In: Olkin I (editor). Contributions to Probability and Statistics. Stanford University Press; 1960. pp. 278–292.

36. Xue D, Christenson R, Genger R, et al. Soil microbial communities reflect both inherent soil properties and management practices in Wisconsin potato fields. American Journal of Potato Research 2018; 95(6): 696–708. doi: 10.1007/s12230-018-9677-6

37. Samuels T, Bryce C, Landenmark H, et al. Microbial weathering of minerals and rocks in natural environments. In: Dontsova K, Balogh-Brunstad Z, Roux GL (editors). Biogeochemical Cycles: Ecological Drivers and Environmental Impact. Wiley; 2020. pp. 59–79. doi: 10.1002/9781119413332.ch3

38. Chen H, Dai Z, Veach AM, et al. Global meta-analyses show that conservation tillage practices promote soil fungal and bacterial biomass. Agriculture, Ecosystems & Environment 2020; 293: 106841. doi: 10.1016/j.agee.2020.106841

39. Brunel C, Da Silva AMF, Gros R. Environmental drivers of microbial functioning in mediterranean forest soils. Microbial Ecology 2020; 80(3): 669–681. doi: 10.1007/s00248-020-01518-5

40. Upton RN, Bach EM, Hofmockel KS. Belowground response of prairie restoration and resiliency to drought. Agriculture, Ecosystems & Environment 2018; 266: 122–132. doi: 10.1016/j.agee.2018.07.021

41. Guo Y, Xu T, Cheng J, et al. Above- and belowground biodiversity drives soil multifunctionality along a long-term grassland restoration chronosequence. Science of The Total Environment 2021; 772: 145010. doi: 10.1016/j.scitotenv.2021.145010

42. Oberan LV, Djurdjevic L, Mitrovic M, et al. Allelopathic interactions between the soil microorganisms and dominant plants in Orno-Quercetum virgiliana forest on Avala Mt. (Serbia). Allelopathy Journal 2008; 22(1): 167–179.

43. Bouffaud M, Poirier M, Muller D, et al. Root microbiome relates to plant host evolution in maize and other Poaceae. Environmental Microbiology 2014; 16(9): 2804–2814. doi: 10.1111/1462-2920.12442

44. Leite HMF, Calonego JC, Rosolem CA, et al. Cover crops shape the soil bacterial community in a tropical soil under no-till. Applied Soil Ecology 2021; 168: 104166. doi: 10.1016/j.apsoil.2021.104166

45. Lange M, Eisenhauer N, Sierra CA, et al. Plant diversity increases soil microbial activity and soil carbon storage. Nature Communications 2015; 6(1): 6707. doi: 10.1038/ncomms7707

46. Ge Z, Du H, Gao Y, Qiu W. Analysis on metabolic functions of stored rice microbial communities by BIOLOG ECO microplates. Frontiers in Microbiology 2018; 9. doi: 10.3389/fmicb.2018.01375

47. Stefanowicz A. The Biolog Plates technique as a tool in ecological studies of microbial communities. Polish Journal of Environmental Studies 2006; 15(5): 669–676.

48. Li YP, Feng YL, Chen YJ, Tian YH. Soil microbes alleviate allelopathy of invasive plants. Science Bulletin 2015; 60(12): 1083–1091. doi: 10.1007/s11434-015-0819-7

49. Korenblum E, Dong Y, Szymanski J, et al. Rhizosphere microbiome mediates systemic root metabolite exudation by root-to-root signaling. Proceedings of the National Academy of Sciences 2020; 117(7): 3874–3883. doi: 10.1073/pnas.1912130117

Refbacks

There are currently no refbacks.

Copyright (c) 2023 Michael Ignatius Ferreira, Anélia Marais, Alfred Botha, Carl Frederick Reinhardt, Marieta van der Rijst

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Editor-in-Chief

Prof. Zhengjun Qiu

Zhejiang University, China

Honorary Editor-in-Chief

Cheng Sun

Academician of World Academy of Productivity Science; Executive Chairman, World Confederation of Productivity Science China Chapter, China

Processing Speed

- - - ＜5 days from submission to initial review decision;
  - 64% acceptance rate

News & Announcements

2024-09-11

Smart agriculture is becoming a reality!

Modern agricultural technology is evolving rapidly, with scientists collaborating with leading agricultural enterprises to develop intelligent management practices. These practices utilize advanced systems that provide tailored fertilization and treatment options for large-scale land management.

2024-05-01

Notice on the prohibition of using AI techniques to generate papers!

This journal values human initiative and intelligence, and the employment of AI technologies to write papers that replace the human mind is expressly prohibited. When there is a suspicious submission that uses AI tools to quickly piece together and generate research results, the editorial board of the journal will reject the article, and all journals under the publisher's umbrella will prohibit all authors from submitting their articles.

Readers and authors are asked to exercise caution and strictly adhere to the journal's policy regarding the usage of Artificial Intelligence Generated Content (AIGC) tools.

2024-01-14

We are recruiting Editorial Team Members

Advances in Modern Agriculture (AMA) is looking for members of the Editorial Board.

2023-12-28

Notice on the change of publication frequency

The publication frequency of Advances in Modern Agriculture is Quarterly since 2024, that means the journal will publish 4 issues per year from 2024 onwards.

More Announcements...

Journal Center

Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.

more

Article Tools

Indexing metadata

How to cite item

Review policy