Scentific Production

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2023

Forage Mass Estimation in Silvopastoral and Full Sun Systems: Evaluation through Proximal Remote Sensing Applied to the SAFER Model 

  • Remote Sensing, 2023, 15(3), 815,  https://doi.org/10.3390/rs15030815

Smartphone image-based framework for quick, non-invasive measurement of spray characteristics

  • Smart Agricultural Technology, Volume 3, February 2023, 100120 

Quantification and Evaluation of Water Requirements of Oil Palm Cultivation for Different Climate Change Scenarios in the Central Pacific of Costa Rica Using APSIM

  • Agronomy 2023, 13(1), 2404; https://doi.org/10.3390/agronomy12102404 

2022

Identifying Nematode Damage on Soybean through Remote Sensing and Machine Learning Techniques

  • Agronomy 2022, 12(10), 2404; https://doi.org/10.3390/agronomy12102404 

Agro-residual biomass and disposable protective face mask: a merger for converting waste to plastic-fiber fuel via an integrative carbonization-pelletization framework

  • Biomass Conversion and Biorefinery (2022); https://doi.org/10.1007/s13399-022-03285-4 

UAV Multispectral Data: A Reliable Approach for Managing Phosphate-Solubilizing Bacteria in Common Bean

  • Agronomy 2022, 12(10), 2284; https://doi.org/10.3390/agronomy12102284 

Loss sampling methods for soybean mechanical harvest

  • Bioscience Journal, 2022, https://doi.org/10.14393/BJ-v38n0a2022-56409

Peanut harvest quality: Relationship between soil tillage management and threshing systems

  • Spanish Journal of Agricultural Research 2022,  https://doi.org/ 10.5424/sjar/2022203-18704

The best moment to carry out the selective harvest of coffee fruits

  • Agronomy Journal 2022, 114 (); https://doi.org/10.1002/agj2.21175  

Integrating Satellite and UAV Data to Predict Peanut Maturity upon Artificial Neural Networks 

  • Agronomy 2022, 12(7), 1512; https://doi.org/10.3390/agronomy12071512 

Production of high-quality biogenic fuels by co-pelletization of sugarcane bagasse with pinewood sawdust and peanut shell 

  • Biomass Conv. Bioref. (2022). https://doi.org/10.1007/s13399-022-02818-1

The Time of Day Is Key to Discriminate Cultivars of Sugarcane upon Imagery Data from Unmanned Aerial Vehicle

  • Drones 2022, 6, 112. https://doi.org/ 10.3390/drones6050112  

UAVs to Monitor and Manage Sugarcane: Integrative Review

  • Agronomy 2022, v. 12, n.3, 661; https://doi.org/10.3390/agronomy12030661

High-Throughput Carbon-Capturing Frameworks by Pelleting Hydrochar of Food Waste and its Residual Ash as a Dopant

  • BioEnergy Research, 2022. https://doi.org/10.1007/s12155-022-10420-6

Biophysical characteristics of soybean estimated by remote sensing associated with artificial intelligence

  • Bioscience Journal, 2022, v. 38 (Continuous Publication). https://doi.org/10.14393/BJ-v38n0a2022-55925

Oil palm yield estimation based on vegetation and humidity indices generated from satellite images and machine learning techniques

  • AgriEngineering, 2022 v. 4, n. 1. https://www.mdpi.com/2624-7402/4/1/19# 

A High-Throughput Imagery Protocol to Predict Functionality upon Fractality of Carbon-Capturing Biointerfaces

  • Agronomy 2022, 12, 446. https://doi.org/10.3390/agronomy12020446 

Assessing Intra-Row Spacing Using Image Processing: A Promising Digital Tool for Smallholder Farmers

  • Agronomy, 2022, 12(2), 301; https://doi.org/10.3390/agronomy12020301 

Using UAV and Multispectral Images to Estimate Peanut Maturity Variability on Irrigated and Rainfed Fields Applying Linear Models and Artificial Neural Networks 

  • Remote Sens., 2022, v. 14, n. 93. https://doi.org/ 10.3390/rs14010093 

Rate errors in sprayer turning and circular movements: PWM valve as compensation system and why spray boom size matters

  • Crop Protection, v. 151, January 2022, 105835

Quality in the mechanized harvesting corn sown at different speeds 

  • Brazilian Journal of Development, 2022, v.8, n.6, p.46058-46066

2021

Mapping Gaps in Sugarcane by UAV RGB Imagery: The Lower and Earlier the Flight, the More Accurate

  • Agronomy, v. 11, n. 12, December 2021, 2578 

Predicting on multi-target regression for the yield of sweet potato by the market class of its roots upon vegetation indices

  • Computers and Eletronics in Agriculture, v. 191, December 2021, 106544 

Use of remote sensing to characterize the phenological development and to predict sweet potato yield in two growing seasons

  • European Journal of Agronomy, v. 129, September 2021, 126337. https://doi.org/10.1016/j.eja.2021.126337

Determination of application volume for coffee plantations using artificial neural networks and remote sensing

  • Computers and Eletronics in Agriculture, v. 184, May 2021, 106096

High-resolution satellite image to predict peanut maturity variability in commercial fields

  • Precision Agriculture, Volume 22, pages 1464-1478, March 2021

Estimated losses in soybean (Glycine max (L.) Merril) harvest according to the speed and rotation of the trail system

  • Australian Journal of Crop Science, v 15, n.04:559-563, 2021

Does moisture in pods interfere with mechanized harvesting of peanuts? 

  • Engenharia Agrícola, v. 41, n. 1, Jan-Feb 2021

Sugarcane base cutting quality using rectangular and circular blades 

  • Engenharia Agrícola, v. 41, n. 1, Jan-Feb 2021

Monitoring tractor performance using shewhart and exponentially weighted moving average charts 

  • Engenharia Agrícola, v. 41, n. 1, Jan-Feb 2021

2020

Potential of using statistical quality control in agriculture 4.0

  • December 2020 
  • Revista Ciencia Agronomica

Methodology for selective cofee harvesting in management zones of yield and maturation 

  • August 2020
  • Precision Agriculture
  • DOI: 10.1007/s11119-020-09751-1

Software Optimisation for Mechanised Sugarcane Planting Scenarios to Aid in Decision-Making  

  • August 2020
  • Sugar Tech 
  • DOI: 10.1007/s12355-020-00868-1

Economic viability of a monitoring system in mechanized citrus production 

  • June 2020
  • Científica
  • DOI: 10.15361/1984-5529.2020v48n2p107-117

Variability of harvest loss in relation to physiological characteristics of cotton

  • April 2020
  • Acta Scientiarum
  • DOI: 10.4025/actasciagron.v42i1.42587

Convolutional neural networks in predicting cotton yield from images of commercial fields 

  • March 2020
  • Computers and Electronics in Agriculture 171:105307

Technical-economic viability of mechanized picking coffee (Coffea arabica L.) in up to three annual operations

  • February 2020
  • SPANISH JOURNAL OF AGRICULTURAL RESEARCH 18(1):e0201

Can basal cutting blade wear affect sugarcane regrowth? 

  • March 2020
  • Computers and Electronics in Agriculture 171:105307

2019

Quality of multi-row harvesting in sugarcane plantations established from pre-sprouted seedlings and billets

  • October 2019
  • Industrial Crops and Products 142(142):12

Using remote sensing to map in-field variability of peanut maturity

The times, movements and operational efficiency of mechanized coffee harvesting in sloped areas 

  • May 2019
  • PLoS ONE 14(5):e0217286

Operational cost of mechanized harvesting of first-crop coffee

  • September 2019
  • Australian Journal of Crop Science 13(9):1503-10
  • DOI: 10.21475/ajcs.19.13.09.p1727

Management systems: soil cover and compaction, longitudinal distribution, and yield of soybean crop

  • July 2019
  • Engenharia Agrícola 39(4):490-497

Wear quantification of basal cutting knives in sugarcane harvesting

  • July 2019
  • Engenharia Agrícola 39(4):498-503

Soil attributes and initial corn development as a function of fertilization and intercropping systems 

  • April 2019
  • Engenharia Agrícola 39(2):257-264

Environmental variables and quality tools applied to the operator of an agricultural microtractor 

  • April 2019
  • Engenharia Agrícola 39(2):208-215

Development and technical validation of spray kit for coffee harvester 

  • March 2019
  • African journal of agricultural research 14(10):571-575
  • DOI: 10.5897/AJAR2018.13424

Morphological and productive influence of harvest on coffee plants 

  • January 2019
  • Australian Journal of Crop Science 13(01):144-150
  • DOI: 10.21475/ajcs.19.13.01.p6955

Operational performance and losses in mechanized soybean harvesting as a function of field shape

  • June 2019
  • Comunicata Scientiae 10(2):308

Adjustments for axial and sieves systems of coffee harvesters 

  • January 2019
  • African journal of agricultural research 14(3):173-179
  • DOI: 10.5897/AJAR2018.13425

Comparative performance of commonly used portable coffee harvesters 

  • January 2019
  • African journal of agricultural research 14(3):168-172
  • DOI: 10.5897/AJAR2018.13423

Straw management and fertilization in soybean production and soil cover 

  • September 2019
  • Nativa, Sinop, v. 7, n. 5, p. 506-512

Development of maize seedlings according to the treatment and seed sowing depth

  • April 2019

2018

Use of real-time extend GNSS for planting and inverting peanuts

Development of an electrohydraulic drive system for the vibrating conveyor belt of the peanut digger-inverter

Quality monitoring of soybean seed tests using Statistical Process Control 

Can combine headers and travel speeds affect the quality of soybean harvesting operations? 

Effect of Soil Management Practices on the Sweeping Operation during Coffee Harvest 

Position errors in sowing in curved and rectilinear routes using autopilot

Parameters affecting the mechanical digging of peanut crops from three different shaped plots 

Billet distribution and initial establishment of sugarcane due to the planting shifts 

Cotton and fiber quality in function of picker harvest speed 

A New Approach to Statistical Process Control: Identification of Outliers in Yield Maps 

Cotton and fiber quality in function of picker harvest speed 

Performance of a special tractor as a function of ballasting and front-wheel drive in coffee harvesting

Performance of corn sowing in fertilization system and intercropping 

Multivariate analysis of peanut mechanized harvesting 

Failure mode and effect analysis (FMEA) in mechanized harvest of sugarcane billets 

2017

Statistical process control applied to mechanized peanut sowing as a function of soil texture