Biosystems Engineering

Top Research Topics at Biosystems Engineering?

The aim of Biosystems Engineering is to expand the discussion of research in Environmental engineering, Water content, Artificial intelligence, Hydrology and Agronomy. The journal explores topics in Environmental engineering which can be helpful for research in disciplines like Ventilation (architecture), Greenhouse and Manure. The research on Water content tackled can also make contributions to studies in the areas of Moisture and Soil science.

While Artificial intelligence is the focus of Biosystems Engineering, it also provided insights into the studies of Computer vision and Pattern recognition.

• Environmental engineering (11.20%)
• Water content (8.83%)
• Artificial intelligence (8.74%)

What are the most cited papers published in the journal?

• Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps (826 citations)
• An Overview of Microwave Processing and Dielectric Properties of Agri-food Materials (493 citations)
• Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV) (303 citations)

Research areas of the most cited articles at Biosystems Engineering:

The most cited papers are organized to address concerns in the fields of Water content, Artificial intelligence, Environmental engineering, Hydrology and Moisture. The most cited articles with studies in Artificial intelligence featured incorporate elements of Computer vision and Pattern recognition. In addition to Hydrology research, the most cited publications aim to explore topics under Soil science, Airflow, Greenhouse and Ventilation (architecture).

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Mechanical engineering
• Ecology

The previous edition focused in particular on these issues:

The journal generally zeroes in on subjects such as Artificial intelligence, Pattern recognition, Soil science, Water content and Mechanics. The work on Artificial intelligence addressed in the journal expands to the thematically related Computer vision. Pattern recognition research featured in it incorporates concerns from various other topics such as Pixel, Field (computer science), Feature (computer vision) and Machine vision.

The concepts on Water content presented in Biosystems Engineering can also apply to other research fields, including Moisture and Soil water. The majority of Mechanics studies are focused on the issues of Discrete element method.

The most cited articles from the last journal are:

• Combining plant height, canopy coverage and vegetation index from UAV-based RGB images to estimate leaf nitrogen concentration of summer maize (7 citations)
• Performance analysis of a tractor - power harrow system under different working conditions (7 citations)
• Yield estimation of soybean breeding lines under drought stress using unmanned aerial vehicle-based imagery and convolutional neural network (6 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Biosystems Engineering (based on the number of publications) are:

• Herman Ramon (40 papers) absent at the last edition,
• Guoqiang Zhang (35 papers) published 2 papers at the last edition the same number as at the previous edition,
• Wouter Saeys (30 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Daniel Berckmans (30 papers) absent at the last edition,
• Digvir S. Jayas (27 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Biosystems Engineering (based on the number of publications) are:

• Wageningen University and Research Centre (130 papers) published 11 papers at the last edition, 4 more than at the previous edition,
• Katholieke Universiteit Leuven (101 papers) published 1 paper at the last edition, 8 less than at the previous edition,
• Aarhus University (91 papers) published 6 papers at the last edition the same number as at the previous edition,
• China Agricultural University (87 papers) published 13 papers at the last edition, 1 more than at the previous edition,
• Washington State University (55 papers) published 1 paper at the last edition, 1 less than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 9.76% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.41% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.65% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.97% of all publications and 52.97% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.