index

Sustainable Agriculture: Enhance soil fertility and plant health using natural microorganisms (bacteria, fungi, algae):
Improved Soil Health: Boost soil structure, microbial activity, and organic matter content;
Higher Productivity: Enhance crop yields and quality, improving profitability;
Environmental Protection: Reduce chemical-mineral fertilizer use, minimizing pollution and health risks;
Climate Resilience: Help plants tolerate drought and salinity, increasing resilience to climate change;
Nutrient Efficiency: Facilitate nitrogen fixation and phosphorus solubilization;
Cost-effective: Generally cheaper than chemical fertilizers, especially beneficial for developing countries (Bhattacharyya & Jha, 2012)^[1];
Circular Economy: Recycle organic waste into biofertilizers, reducing emissions and enhancing carbon sequestration.

Economic Impact (Brazil example):
- US$ 440 million savings with 25% less nitrogen use in corn crops (2019/2020) (Santos, Nogueira & Hungria, 2012)^[2];
- US$ 10.2 billion saved via inoculants in soybean cultivation (Olmo, 2022)^[3].

Master’s thesis: Santos (2024)^[4] Scientific research on biofertilizer: the birth and evolution in the field structure.

Paradigms and Trajectories

Technological Paradigm

Guides technological change by defining important problems and how to solve them, much like a scientific paradigm directs research (Dosi, 1982).^[5]

Technological Trajectories

Cumulative progress to refine and optimize solutions in line with the paradigm’s prescriptions (Dosi, 1982).^[5]

RQ1:
- Is it possible to detect technological trajectories on biofertilizer?
RQ2:
- And it’s attributes?
  1. emergence,
  2. convergence,
  3. divergence,
  4. maturity,
  5. dormancy,
  6. continuity and
  7. discontinuity.

Source: Zhang 2023^[6] A holistic method for radical concept generation based on technological evolution.

Souza et al. – `birddog`

Collect data

4,698 results from Web of Science Core Collection downloaded on February 9, 2024.

Growth

Code

library(bibliometrix)
library(birddog)
library(igraph)
library(ggraph)
library(tidygraph)
library(tidyverse)
library(fs)
library(plotly)
library(RColorBrewer)
library(ggHoriPlot)
library(ggthemes)
library(ggplot2)
source('code/sniff_group_trajectory_2d.R')
source('code/sniff_group_trajectory_3d.R')

# arquivos <- fs::dir_ls('bibs', regexp = '.bib$')

# tictoc::tic()
# M <- bibliometrix::convert2df(file = arquivos, dbsource = "wos", format = "bibtex")
# tictoc::toc()
# 25 secs - rambo


rio::import('biofertilizer/M.rds') -> pub

periodo1 <- 2000:2023

pub |>
  dplyr::count(PY, sort = T, name = 'Papers') |>
  dplyr::filter(PY %in% periodo1) |>
  dplyr::arrange(PY) |>
  dplyr::mutate(trend = 1:dplyr::n()) ->
  d

d$lnp <- log(d$Papers)

# linear model
m1 <- lm(lnp ~ trend, data = d)
# summary(m1)

beta0 <- m1$coefficients[[1]]
beta1 <- m1$coefficients[[2]]

# no linear model
m2 <- nls(Papers ~ b0 * exp(b1 * (PY - min(periodo1))), start = list(b0 = beta0, b1 = beta1), data = d)

# summary(m2)
# sjPlot::tab_model(m2, digits = 3)

d$predicted <- coef(m2)[1] * exp(coef(m2)[2] * (d$PY - min(periodo1)))

d |>
  dplyr::mutate(Year = PY) |>
  dplyr::mutate(predicted = round(predicted, 0)) ->
  d

periodo2 <- min(periodo1):(max(periodo1) + 4)
predicted <- tibble::tibble(PY = periodo2, Predicted = round(coef(m2)[1] * exp(coef(m2)[2] * (periodo2 - min(periodo2))), 0))

pub |>
  dplyr::count(PY, sort = T, name = 'Papers') |>
  dplyr::filter(PY %in% periodo1) |>
  dplyr::full_join(predicted, by = 'PY') |>
  dplyr::arrange(PY) |>
  dplyr::mutate(Papers = ifelse(PY > max(periodo1), NA, Papers)) |>
  dplyr::rename(Year = PY) ->
  d2

pub |>
  dplyr::mutate(PY = as.numeric(PY)) |>
  dplyr::count(PY, sort = F, name = 'Papers') |>
  dplyr::arrange(PY) |>
  dplyr::filter(PY %in% 2000:2022) |>
  dplyr::rename(Year = PY) |>
  dplyr::full_join(d2) ->
  d3

# TODO
# adicionar dispersão para os anos em projeção
highcharter::hchart(d3, "column", highcharter::hcaes(x = Year, y = Papers), name = "Publications", showInLegend = TRUE) |>
  highcharter::hc_add_series(d2, "line", highcharter::hcaes(x = Year, y = Predicted), name = "Predicted", showInLegend = TRUE) |>
  highcharter::hc_add_theme(highcharter::hc_theme_google()) |>
  highcharter::hc_navigator(enabled = FALSE)  |>
  highcharter::hc_exporting(enabled = TRUE, filename = 'topic_growth_rate') |>
  highcharter::hc_xAxis(plotBands = list(list(from = 2022, to = 2022, color = "#330000")))

Figure 1: Biofertilizer growth

Code

tibble::tribble(
  ~Measure,   ~Biofertilizer, ~WoS,
  "Annual growth rate (%)",  '20.1', '6.7',
  "Doubling-time", '3y+9m', '10y+8m'
) |>
  gt::gt() |>
  gt::tab_header(title = "Growth Rate", subtitle = gt::md("Biofertilizer *vs* WoS")) |>
  gt::cols_label(
    Measure = gt::md(" "),
    Biofertilizer = gt::md("Biofertilizer"),
    WoS = gt::md("WoS")
  )

Table 1: Biofertilizer growth vs WoS growth

Growth Rate
Biofertilizer vs WoS
	Biofertilizer	WoS
Annual growth rate (%)	20.1	6.7
Doubling-time	3y+9m	10y+8m

Field analysis

Code

plot_horizon_field <- function(field) {
  top_n_sc_py |>
    dplyr::mutate(SC2 = janitor::make_clean_names(SC, allow_dupes = T)) |>
    dplyr::filter(SC2 == field) |>
    ggplot() +
    geom_horizon(aes(PY, papers), origin = "min", horizonscale = 5) +
    scale_fill_hcl(palette = "BluGrn", reverse = T) +
    theme_few() +
    scale_x_continuous(limits = c(1980, 2022), breaks = seq(1980, 2022, 5), expand = c(0, 0.4)) +
    scale_y_continuous(expand = c(0, 0)) +
    theme(
      panel.spacing.y = unit(0, "lines"),
      strip.text.y = element_text(size = 11, angle = 0, hjust = 0),
      legend.position = "none",
      axis.text.y = element_blank(),
      axis.title.y = element_blank(),
      axis.ticks.y = element_blank(),
      axis.title.x = element_blank(),
      axis.ticks.x = element_blank(),
      panel.border = element_blank(),
      axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1, size = 50)
    )
}

rio::import("biofertilizer/top_n_sc_py.rds") -> top_n_sc_py
rio::import("biofertilizer/tab_field_analysis.rds") -> tab_field_analysis

tab_field_analysis |>
  gt::gt() |>
  gt::tab_header(title = "Fields Attributes") |>
  gt::cols_label(
    name2 = gt::md("Field"),
    papers = gt::md("Papers"),
    average_age = gt::md("Average age"),
    growth_rate_percentage_year = gt::md("Growth rate"),
    doubling_time = gt::md("Doubling time"),
    SC = gt::md("Horizon plot")
  ) |>
  gt::text_transform(
    locations = gt::cells_body(columns = "SC"),
    fn = function(column) {
      purrr::map(column, plot_horizon_field) |>
        gt::ggplot_image(aspect_ratio = 3, height = 100)
    }
  ) |>
  gt::tab_source_note(source_note = gt::md("**Source**: Web of Science. Data extracted, organized and estimated by the authors.")) |>
  gt::tab_footnote(footnote = "Average publication year. Example, 2015+6m means that the articles were published on average in the year of 2015 plus 6 months. Time span, 2010 until 2022.", locations = gt::cells_column_labels(columns = average_age)) |>
  gt::tab_footnote(footnote = "y = years, m = months. Calculated by ln(2)/b1 where b1 is the econometric model coefficient.", locations = gt::cells_column_labels(columns = doubling_time)) |>
  gt::tab_footnote(footnote = "Publications between 1980 and 2022. Chart type horizon plot.", locations = gt::cells_column_labels(columns = SC)) |>
  gt::tab_options(table.font.size = "14pt")

Fields Attributes
AGRICULTURE	1603	2016+5m	14.1	5y+4m
PLANT SCIENCES	590	2018+10m	29.8	3y+8m
ENV SCI \& ECOLOGY	585	2019+1m	24.8	3y+1m
BIOTECH \& A MICROB	485	2017+4m	14.6	5y+1m
SCI TECH O T	361	2019+5m	25.1	3y+1m
MICROBIOLOGY	314	2018+9m	21.6	4y+6m
ENGINEERING	153	2018+9m	22.3	3y+5m
CHEMISTRY	118	2018+7m	18.5	4y+1m
BIOCH \& MOL BIO	107	2017+7m	19.5	4y+11m
LIFE SCI \& BIO O T	86	2018+12m	20.2	4y+10m
Source: Web of Science. Data extracted, organized and estimated by the authors.
¹ Average publication year. Example, 2015+6m means that the articles were published on average in the year of 2015 plus 6 months. Time span, 2010 until 2022.
² y = years, m = months. Calculated by ln(2)/b1 where b1 is the econometric model coefficient.
³ Publications between 1980 and 2022. Chart type horizon plot.

Citation network

Total documents 4698

Source: Shibata (2009)^[7]

Through Bibliographic Coupling the Giant component holds 4604 papers
- ~ 98% of all documents

Code

# tictoc::tic()
# net <- birddog::sniff_network(M, type = 'bibliographic coupling', database_source = 'wos')
# tictoc::toc()
# 79 mins - rambo

cgn <- function(x) {gsub('^.*_', '', x)}

M <- rio::import('biofertilizer/M.rds')
net <- rio::import('biofertilizer/net-coupling.rds')

comp <- birddog::sniff_components(net)

net2 <- comp$network

comp$components |>
  dplyr::rename(documents = quantity_publications) |>
  dplyr::mutate(average_age = round(average_age, 1)) |>
  dplyr::slice(1:4) |>
  gt::gt() |>
  gt::tab_header(title = "Components") |>
  gt::cols_label(
    component = gt::md("Component"),
    documents = gt::md("Documents"),
    average_age = gt::md("Average Age")
  ) |>
  gt::tab_options(table.font.size = "16pt")

Table 2: Network components

Components
Component	Documents	Average Age
component01	4604	2018.1
component02	1	2012.0
component03	1	1994.0
component04	1	1993.0

Building groups

Code

gru <- birddog::sniff_groups(
  net2,
  min_group_size = 50,
  keep_component = "component01",
  cluster_component = "component01",
  algorithm = "louvain"
)

Group’s detected by citations similarity and maximizing modularity as Louvain Algorithm^[8].

Groups Attributes
Group	Documents	Average age	Growth rate per year	Doubling-time (y + m)	Hubs
g01	899	2018	29%	2y+8m	14
g02	891	2019	19.4%	3y+11m	17
g03	839	2018	16.5%	4y+6m	29
g04	781	2017	13.9%	5y+6m	14
g05	727	2020	31.2%	2y+7m	11
g06	463	2016	5.4%	13y+1m	3

Group	Terms NLP extracted	Description
g01	microalgae biomass; fixing cyanobacteria; algal biomass; anabaena sp.; proline content; mm nacl; c. vulgaris; polyphenol oxidase; antioxidant enzymes; wastewater treatment; microalgae cultivation; chlorella vulgaris; ascorbate peroxidase; nostoc muscorum; aqueous extract	Stress-Tolerant Bacteria, Microalgae, and Cyanobacteria for Improving Crop Growth and Yield
g02	phylogenetic analysis; hydrogen cyanide; acetic acid; insoluble phosphate; pgp traits; inorganic phosphate; p solubilization; acetic acid production; phosphate solubilization; solubilization index; growth promotion; enterobacter sp.; complete genome; endophytic bacteria; rhizobacterial isolates	Phosphate Solubilizing Endophytic Bacteria: Plant Growth Promoting (PGP) Potential
g03	food waste ; anaerobic digestion; biogas production; bovine biofertilizer; methane production; swine manure; bovine manure; cycle assessment; black soldier; liquid digestate; life cycle assessment; waste treatment; solid waste; anaerobic digestates; olive mill wastewater	Biofertilizer and Biogas Production Through Food Waste and Manure
g04	net returns; available n; am fungi; effect of integrated nutrient management; integrated nutrient; kg zn; 30 cm; microbial biomass carbon; biomass carbon; mycorrhizal inoculation; effect of integrated nutrient; kg p2o5 ha; p2o5 ha; treatment combinations; sources of nutrients	Organic Manures and Microbes for Integrated Nutrient Management
g05	soil microbiome; continuous cropping; fungal community; fusarium wilt; microbial communities; bacterial communities; fungal communities; banana fusarium; microbial community composition; community composition; soil microbial diversity; redundancy analysis; relative abundances; soil microbial communities; disease suppression	Microbiome and Microbial Diversity for Disease Suppression in a Sustainable Agriculture Scenario
g06	cm inter; row spacing; inoculation with biofertilizer; 23.8 t; 23.8 t ha; rotten straw; 150 kg; absorbent polymer; kitchen waste oil; waste oil; yellow passion; oil yield; foliar contents; tiller number; pgpr strains	Azospirillum’s Strategies as a Plant Growth-Promoting Rhizobacteria (PGPR)

Geographic distribution

Group:

Published documents by country.

Measures the prestige of each document
$K_i$ = All network citations
$k_i$ = Group citations
$Z_i$ = The within-group degree $z_i$ measures how ‘well-connected’ article $i$ is to other articles in the group [$z_i \geq 2.5$ Hub]
$P_i$ = Measures how ‘well-distributed’ the links of article $i$ are among different groups. [higher $=$ citations better distributed between groups]
zone = $R5$ provincial hubs; $R6$ connector hubs; $R7$ kinless hubs

\[ z_i = {k_i - \bar k_{s_i} \over \sigma_{k_{s_i}}} \qquad(1)\]

\[ P_i = 1 - \sum_{s=1}^{S} \left({k_{s_i} \over K_i} \right)^2 \qquad(2)\]

Source: Guimera and Amaral (2005)^[9] Functional cartography of complex metabolic networks. Nature.

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g01') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE, options = list(pageLength = 10))

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g02') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE, options = list(pageLength = 10))

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g03') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE, options = list(pageLength = 10))

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g04') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE, options = list(pageLength = 10))

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g05') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE)

Code

rio::import('biofertilizer/hubs-coupling.rds') |>
  tibble::as_tibble() |>
  dplyr::filter(zone != 'noHub') |>
  dplyr::filter(group == 'component01_g06') |>
  dplyr::arrange(dplyr::desc(zone)) |>
  dplyr::select(- group) |>
  dplyr::mutate(Zi = round(Zi, 2), Pi = round(Pi, 2)) |>
  dplyr::left_join(M |> dplyr::select(SR, url = DI) |> tibble::as_tibble(), by = 'SR') |>
  dplyr::mutate(SR = paste0('<a href="https://doi.org/', url, '">', SR, '</a>')) |>
  dplyr::select(- url) |>
  DT::datatable(rownames = FALSE, escape = FALSE, options = list(pageLength = 10))

Trajectory 2d

Group:

Label Type:

Edge Threshold:

Vertice Threshold:

Trajectory 3d

Group:

Edge Threshold:

Vertice Threshold:

Topics with STM

Source: https://images.app.goo.gl/DiZG7WixdLwkbPKg9

Topic	Proportion	Terms	Description	Hubs
g01T8	0.129	plant, growth, stress, salin, strain, promot, inocul, salt, toler, effect	Effect of Inoculation with Salt-Tolerant Strains on Plant Growth Promotion Under Salinity Stress	6
g01T3	0.119	fertil, soil, yield, organ, chemic, treatment, nitrogen, plant, use, increas	Fertilizer and Soil Treatments: Organic and Chemical Approaches to Increase Nitrogen Use and Plant Yield	3
g01T6	0.115	biomass, microalga, wastewat, product, use, treatment, cultiv, biofertil, microalg, system	Microalgae-Based Wastewater Treatment for Biofertilizer Production	9
g01T7	0.101	product, microalga, agricultur, sustain, use, applic, review, food, develop, can	Microalga-Based Products for Sustainable Agricultural Applications and Food Development	4
g01T1	0.099	water, stress, applic, irrig, yield, fertil, drought, condit, increas, content	Applications of Irrigation and Fertilization to Increase Yield Under Drought Conditions and Water Stress	14
g01T4	0.075	rice, azolla, cyanobacteria, nitrogen, biofertil, growth, strain, field, fix, anabaena	Growth and Nitrogen Fixation in Rice Fields with Azolla and Anabaena Strains as Cyanobacterial Biofertilizers	5
g01T10	0.075	plant, applic, fruit, growth, acid, foliar, treatment, tomato, yield, effect	Foliar Citric Acid Application on Tomato Plant Growth, Fruit Yield, and Quality	5
g01T9	0.072	use, wast, activ, extract, product, potenti, feather, biofertil, degrad, acid	Potential Use of Feather Waste for Biofertilizer Production	2
g01T2	0.062	extract, growth, root, seed, seawe, germin, weight, length, plant, shoot	Effect of Seaweed Extract on Seed Germination, Root Growth, and Plant Shoot Length	5
g01T11	0.062	activ, protein, stress, antioxid, increas, studi, enzym, gene, induc, express	Increasing Protein Activation in Stress-Induced Gene Expression	4
g01T5	0.052	nutrient, soil, cell, water, releas, use, studi, alga, biomass, increas	Algal Biomass to Enhance Nutrient Availability in Soil and Plant Cells	1
g01T12	0.039	soil, metal, plant, heavi, content, growth, use, biofertil, contamin, nanoparticl	Use of Biofertilizers and Nanoparticles to Enhance Plant Growth in Metal-Contaminated Soil	No hubs

Topic	Proportion	Terms	Description	Hubs
g02T7	0.167	isol, growth, plant, promot, product, iaa, bacteri, bacteria, potenti, acid	Isolation and Growth-Promoting Potential of IAA-Producing Bacteria for Plant Growth	1
g02T6	0.1	plant, growth, root, promot, rice, endophyt, seedl, strain, inocul, effect	Effect of Endophytic Strain Inoculation on Root Growth Promotion in Rice Seedlings	2
g02T5	0.099	fertil, plant, growth, yield, biofertil, inocul, treatment, use, nutrient, content	Biofertilizer Inoculation for Enhanced Plant Growth and Yield	2
g02T10	0.094	plant, agricultur, use, crop, product, soil, fertil, sustain, growth, biofertil	Biofertilizer for Plant Growth as a Sustainable Agriculture Solution	6
g02T1	0.081	activ, biocontrol, diseas, strain, pathogen, control, agent, growth, show, antagonist	Active Biocontrol Agents and Antagonistic Strains for Disease Pathogen Control and Growth Enhancement	1
g02T11	0.075	soil, phosphat, solubil, phosphorus, avail, increas, acid, organ, psb, rock	Phosphate Solubilizing Biofertilizers (PSB)-Mediated Organic Acid Solubilization of Rock Phosphate for Enhanced Plant Phosphorus Availability	4
g02T3	0.072	strain, gene, genom, sequenc, plant, promot, analysi, growth, speci, acid	Strain-Specific Gene Discovery through Genome Sequencing for Plant Growth Promotion	2
g02T2	0.07	solubil, phosphat, isol, strain, medium, bacteria, select, identifi, zinc, cultur	Selection and Identification of Zinc-Solubilizing Bacteria for Enhanced Phosphate Solubilization in Culture	4
g02T4	0.068	stress, plant, salin, toler, growth, salt, condit, promot, strain, acid	Promoting Plant Growth and Stress Tolerance under Saline Conditions Using Acid-Tolerant Strains	3
g02T12	0.064	use, biofertil, product, carrier, wast, formul, cell, ferment, organ, studi	Use of Organic Waste Carriers in Biofertilizer Production with Formulation and Fermentation of Cells	3
g02T8	0.055	seed, treatment, increas, yield, wheat, effect, field, growth, water, control	Effect of Seed Treatment on Increasing Yield and Growth under Field and Water-Controlled Conditions	2
g02T9	0.055	inocul, strain, nodul, rhizobium, soil, yield, growth, increas, control, effect	Effect of Rhizobium Inoculation on Nodule Formation, Soil Quality, and Increased Yield and Growth	3

Topic	Proportion	Terms	Description	Hubs
g03T5	0.123	digest, anaerob, bioga, product, methan, use, solid, pretreat, studi, manur	Solid Manure for Enhanced Biogas and Methane Production through Anaerobic Digestion	4
g03T12	0.117	energi, bioga, product, use, generat, system, environment, potenti, econom, scenario	Potential Economic and Environmental Benefits of Biogas Energy Systems through Product Use and Generation Scenarios	6
g03T9	0.116	biofertil, product, fertil, fruit, plant, treatment, dose, organ, evalu, use	Evaluation of Biofertilizer Treatments on Plant Organ Development and Fruit Yield with Varied Doses	17
g03T10	0.104	wast, product, food, industri, review, sustain, manag, bio, process, can	Sustainable Management of Waste Products in the Food Industry Through Bio Processes	6
g03T8	0.092	fertil, plant, soil, growth, crop, yield, bio, nutrient, increas, effect	Effect of Bio Nutrients on Soil Fertility, Plant Growth, and Crop Yield	1
g03T6	0.07	soil, organ, metal, concentr, applic, use, heavi, biofertilis, content, studi	Impact of Biofertilizer Application on Soil Heavy Metal Concentration	4
g03T11	0.068	compost, manur, wast, organ, ferment, substrat, anim, microbi, treatment, day	Composting of Manure and Organic Waste through Microbial Fermentation	4
g03T3	0.067	biochar, use, process, pyrolysi, result, product, degre, high, adsorpt, mushroom	High-Temperature Pyrolysis for High-Performance Biochar Adsorbents	3
g03T4	0.066	water, biofertil, irrig, salin, plant, soil, bovin, growth, use, conduct	Bovine Biofertilizers for Sustainable Irrigation with Saline Water	18
g03T7	0.066	technolog, studi, use, develop, environment, base, system, model, sustain, product	Technology-Based Systems for Sustainable Environmental Models and Product Use	4
g03T2	0.054	wastewat, oil, treatment, use, water, effluent, remov, oliv, sludg, mill	Olive Mill Wastewater Treatment and Oil Recovery	1
g03T1	0.037	biofertil, effect, inocul, soil, bacteria, control, rock, compound, phosphat, fertil	Effect of Biofertilizer Inoculation on Soil Bacteria and Phosphate Rock Fertilizer	3
g03T13	0.023	residu, acid, process, carbon, product, produc, biofertil, base, result, ferment	Biofertilizer Production from Residual Carbon Sources via Fermentation	2

Topic	Proportion	Terms	Description	Hubs
g04T15	0.093	amf, mycorrhiz, fungi, arbuscular, plant, root, colon, growth, inocul, soil	AMF (Arbuscular Mycorrhizal Fungi) Inoculation for Enhanced Plant Growth	3
g04T13	0.085	fertil, nutrient, organ, manur, npk, inorgan, yield, recommend, integr, dose	Integrated Nutrient Management for Optimal Yield	4
g04T14	0.079	fertil, bio, plant, growth, content, acid, effect, treatment, soil, miner	Biofertilizer Treatment on Soil Mineral Content and Plant Growth	6
g04T9	0.072	vermicompost, wast, use, earthworm, organ, compost, product, process, studi, digest	Vermicompost and Earthworm Digest in Organic Composting Processes	6
g04T12	0.067	soil, amend, activ, properti, treatment, organ, applic, studi, microbi, increas	Organic Soil Amendment for Enhanced Microbial Activit	5
g04T8	0.056	plant, growth, promot, root, effect, activ, enhanc, pgpr, strain, rhizospher	PGPR Strain on Root Growth and Rhizosphere Activity Enhancement	1
g04T5	0.052	yield, seed, psb, rdf, rhizobium, inocul, signific, applic, fertil, level	PSB (Phosphate Solubilizing Bacteria) Rhizobium Inoculation for Seed Yield and Fertilizer Application Levels	3
g04T18	0.05	three, treatment, yield, experi, design, effect, level, replic, random, complet	Treatment Effect on Yield: Randomized Complete Block Design	No hubs
g04T3	0.047	rice, crop, soil, organ, system, carbon, fym, term, long, green	Long-Term Impact of FYM (Farm Yard Manure) and Green Organ Systems on Carbon Dynamics in Rice Crop Soil	2
g04T6	0.046	yield, grain, wheat, maiz, crop, uptak, effect, applic, effici, increas	Yield and Grain Uptake Efficiency to Increase Wheat and Maize Crop Production	2
g04T2	0.045	fruit, qualiti, content, total, treatment, plant, sugar, leaf, tomato, tree	Treatments on Tomato Fruit Quality and Sugar Content	No hubs
g04T10	0.045	product, crop, agricultur, organ, farm, soil, qualiti, sustain, fertil, manag	Sustainable Management of Soil Quality in Organic Crop Agriculture through Farm Fertilization Practices	1
g04T16	0.044	plant, yield, number, per, maximum, bean, treatment, growth, height, flower	Treatment Effects on Yield, Growth, and Flower Number	No hubs
g04T7	0.041	water, stress, irrig, fertil, increas, yield, drought, improv, condit, grain	Improving Grain Yield Under Drought Conditions Through Water Stress Management, Irrigation, and Fertilization	1
g04T11	0.038	tha, soil, rdf, fym, higher, rdn, treatment, manag, nitrogen, crop	Enhancing Crop Nitrogen Management for Higher Yields through RDF (Recommended Fertilizer Dose), RDN (Recommended Dose of Nitrogen) and FYM (Farm Yard Manure) Treatments	4
g04T19	0.037	oil, intercrop, fertil, essenti, yield, content, applic, highest, ratio, quality	Fertilizer Application for Highest Yield and Essential Oil Content in Intercrops	4
g04T1	0.035	biofertil, fertil, nitrogen, growth, chemic, azotobact, treatment, plant, increas, dose	Comparing Biofertil vs. Chemical Fertilizer (Nitrogen) with Azotobacter to Enhance Plant Growth	2
g04T17	0.035	bacteria, phosphat, solubil, soil, strain, use, isol, phosphorus, studi, bacteri	Use and Isolation of Bacterial Strains for Phosphate Solubilization in Soil	2
g04T4	0.033	inocul, plant, growth, soil, dri, effect, shoot, increas, biomass, nodul	Effect of Inoculants on Plant Growth, Soil Quality, and Increased Shoot Biomass and Nodulation Under Dry Conditions	No hubs

Topic	Proportion	Terms	Description	Hubs
g05T8	0.151	agricultur, plant, soil, product, sustain, biofertil, use, fertil, crop, review	Sustainable agriculture: a review on the use of biofertilizers for plant and crop enhancement	10
g05T2	0.12	soil, fertil, microbi, communiti, organ, biofertil, increas, treatment, effect, signific	Effects of Biofertilizers on Soil Microbial Communities and Fertility	9
g05T3	0.111	yield, plant, biofertil, growth, inocul, treatment, effect, increas, seed, control	Biofertilizer Seed Treatment for Increased Plant Growth and Yield	6
g05T11	0.106	plant, growth, promot, strain, root, trichoderma, isol, bacillus, activ, endophyt	Plant Growth Promoter with Endophytic Bacteria and Trichoderma	2
g05T5	0.105	fertil, product, organ, use, nutrient, content, soil, chemic, applic, dose	Nutrient Content and Soil Chemical Properties Following Organic Fertilizer Application at Various Doses	9
g05T6	0.099	plant, rhizospher, communiti, microbiom, bacteri, root, inocul, function, microbi, interact	Plant Root Inoculant for Enhanced Rhizosphere Microbiome Function	3
g05T9	0.076	diseas, soil, fusarium, suppress, pathogen, control, wilt, banana, signific, applic	Significant Suppression of Fusarium Wilt through Soil Pathogen Control Applications	9
g05T7	0.069	bacillus, use, product, growth, bacteria, biofertil, formul, strain, isol, effect	Effect of Bacillus Strains Isolated for Use in Biofertilizer Formulations on Plant Growth	4
g05T4	0.066	use, acid, extract, result, analysi, studi, show, biofertil, content, concentr	Acid Extract Analysis of Biofertilizer Content and Concentration	3
g05T10	0.065	biofertil, soil, emiss, compost, manur, reduc, abund, urea, use, wast	Biofertilizer Made from Recycled Manure and Compost	5
g05T1	0.033	nitrogen, fix, fixat, bacteria, growth, plant, activ, gene, diazotroph, polymyxa	Nitrogen Fixation Activity and Gene Expression in Diazotroph Bacteria Polymyxa for Plant Growth	5

Topic	Proportion	Terms	Description	Hubs
g06T2	0.132	growth, strain, plant, isol, promot, pgpr, root, bacillus, potenti, rhizobacteria	Beneficial Rhizosphere Bacteria: Promoting Plant Growth Through Multiple Mechanisms	3
g06T1	0.125	inocul, yield, increas, plant, seed, growth, effect, wheat, strain, experi	Effect of Seed Inoculation and Plant Growth Strains on Wheat Yield	3
g06T3	0.121	biofertil, plant, product, agricultur, crop, use, fertil, sustain, soil, nutrient	Sustainable Biofertil Product Enhancing Plant and Crop Use in Agriculture and Soil Nutrients	4
g06T5	0.108	fertil, yield, organ, dose, treatment, combin, biofertil, crop, manur, soil	Organic Fertilizer and Biofertilizer Combination for Crop Yield Enhancement and Soil Treatment	4
g06T11	0.097	biofertil, plant, oil, fertil, chemic, yield, treatment, effect, applic, dri	Effects of Biofertilizer and Chemical Fertilizer on Plant Yield	7
g06T10	0.093	plant, growth, content, root, increas, fruit, acid, tomato, effect, seedl	Effects of Plant Growth and Acid Content on Tomato Seedling Root and Fruit Increase	No hubs
g06T4	0.073	nitrogen, biofertil, use, azospirillum, product, fix, crop, fixat, cultur, brasilens	Azospirillum brasilense Biofertilizer for Nitrogen Fixation in Crop Culture	4
g06T6	0.073	soil, biofertil, microbi, increas, amend, day, communiti, signific, effect, applic	Significant Effects of Biofertilizer Application on Soil Microbial Community Increase and Amendment	3
g06T9	0.073	plant, growth, bacteria, soil, promot, use, phosphat, solubil, wast, diseas	Use of Phosphate-Solubilizing Bacteria to Promote Plant Growth and Soil Health while Reducing Waste and Disease	2
g06T7	0.058	fertil, bio, yield, grain, applic, treatment, chemic, level, nitrogen, rate	Effects of Bio and Chemical Fertilizers on Grain Yield and Nitrogen Levels at Various Treatment Rates	2
g06T8	0.045	stress, irrig, water, salin, yield, condit, effect, drought, improv, chickpea	Effects of Irrigation and Salinity Stress on Chickpea Yield Under Drought Conditions	1

Indicators - Citations Cycle Time

Group:

Kayal (1999)^[10]
Technology Cycle Time - TCT

The median age of U.S. patents cited in a specific patent. This indicator uses patent citations to indicate the age of the inventions on which a new invention is based. It is assumed that the more recent the age the more quickly one generation of inventions is being replaced with another.

measure the pace of technological or scientific progress or change.

Indicators - Entropy

Group:

Entropy by Shannon (1948)^[11] quantifies the average level of uncertainty.

The normalised entropy is a scale-independent measure of uncertainty that can be used to compare the uncertainty of different groups.

Entropy measures the randomness or disorder in the group.

Conclusions

Biofertilizer research has grown significantly faster than general scientific research (WoS).
Sharp expansion after 2015, aligned with international agreements (Paris Agreement and 2030 Agenda).
Emergence of new scientific categories such as Energy & Fuels and Materials Science.
The proposed method, birddog, was able to effectively identify research trajectories and their attribute’s: emergence, convergence, divergence, maturity, dormancy, continuity, and discontinuity.
Six research areas and their trajectories:
- Group 01: Stress-Tolerant Bacteria, Microalgae, and Cyanobacteria - mature trajectory, dominated by solutions for basic agricultural problems (crop growth and yield) - India leads with presence of several countries from four continents;
- Group 02: Phosphate Solubilizing Endophytic Bacteria - the most incremental trajectory - populated by India and China;
- Group 03: Biofertilizer x Biogas - trajectories convergence, biofertilizer with renewable energy - dominated by Brazil;
- Group 04: Combines organic inputs with microbial inoculants for efficient nutrient - paradigms convergence, biofertilizer (organic) with fertilizer (chemical) - dominated by India;
- Group 05: Microbial Diversity for Disease Suppression in Continuous Cropping- emergent trajectory - China as main player;
- Group 06: Azospirillum’s Strategies as a Plant Growth-Promoting Rhizobacteria - mature trajectory being renewed, technology close to the market - all countries are interested.
Dominance of emerging countries: India, Brazil, and China.

References

Bhattacharyya PN, Jha DK. Plant growth-promoting rhizobacteria (PGPR): Emergence in agriculture. World Journal of Microbiology and Biotechnology [Internet]. 2011;28(4):1327–50. doi:10.1007/s11274-011-0979-9

Santos MS, Nogueira MA, Hungria M. Outstanding impact of azospirillum brasilense strains ab-V5 and ab-V6 on the brazilian agriculture: Lessons that farmers are receptive to adopt new microbial inoculants. Revista Brasileira de Ciência do Solo [Internet]. 2021;45. doi:10.36783/18069657rbcs20200128

Olmo R, Wetzels SU, Armanhi JSL, Arruda P, Berg G, Cernava T, et al. Microbiome research as an effective driver of success stories in agrifood systems – a selection of case studies. Frontiers in Microbiology [Internet]. 2022;13. doi:10.3389/fmicb.2022.834622

Santos J da S dos. Scientific research on biofertilizer: The birth and evolution in the field structure [Master thesis]. Cuiabá, Mato Grosso: Universidade Federal de Mato Grosso; 2024.

Dosi G. Technological paradigms and technological trajectories. Research Policy [Internet]. 1982;11(3):147–62. doi:10.1016/0048-7333(82)90016-6

Zhang L, Tan R, Peng Q, Yang W, Zhang J, Wang K. A holistic method for radical concept generation based on technological evolution: A case application of DC charging pile. Computers & Industrial Engineering [Internet]. 2023;179:109213. doi:10.1016/j.cie.2023.109213

Shibata N, Kajikawa Y, Takeda Y, Matsushima K. Comparative study on methods of detecting research fronts using different types of citation. Journal of the American Society for Information Science and Technology [Internet]. 2009 [cited 2014 Nov 17];60(3):571–80. doi:10.1002/asi.20994

Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment [Internet]. 2008;2008(10):P10008. doi:10.1088/1742-5468/2008/10/p10008

Guimerà R, Nunes Amaral LA. Functional cartography of complex metabolic networks. Nature [Internet]. 2005;433(7028):895–900. doi:10.1038/nature03288

10.

Kayal AA, Waters RC. An empirical evaluation of the technology cycle time indicator as a measure of the pace of technological progress in superconductor technology. IEEE Transactions on Engineering Management [Internet]. 1999;46(2):127–31. doi:10.1109/17.759138

11.

Shannon CE. A mathematical theory of communication. Bell System Technical Journal [Internet]. 1948;27(3):379–423. doi:10.1002/j.1538-7305.1948.tb01338.x

Who are we?

Why biofertilizer?

Paradigms and Trajectories

Souza et al. – birddog

Collect data

Growth

Field analysis

Citation network

Building groups

Contents

Geographic distribution

Published documents by country.

Hubs

Trajectory 2d

Trajectory 3d

Topics with STM

Indicators - Citations Cycle Time

Indicators - Entropy

Conclusions

References

Souza et al. – `birddog`