Jose Paulo Molin

University of São Paulo | USP · Department of Biosystems Engineering (ZEB)

Soil sampling is a fundamental stage for recommending agricultural correctives and fertilizers, estimating the nutritional demands of plants, and consequently maximizing productivity. Therefore, this study aimed to assess the performance of three soil samplers in different management systems in terms of sample quality and operational efficiency. A...

Coffee farmers do not have efficient tools to have sufficient and reliable information on the maturation stage of coffee fruits before harvest. In this study, we propose a computer vision system to detect and classify the Coffea arabica (L.) on tree branches in three classes: unripe (green), ripe (cherry), and overripe (dry). Based on deep learning...

In soil science, near-infrared (NIR) spectra are being largely tested to acquire data directly in the field. Machine learning (ML) models using these spectra can be calibrated, adding only samples from one field or gathering different areas to augment the data inserted and enhance the models’ accuracy. Robustness assessment of prediction models usu...

To obtain a better performance when modeling soil spectral data for attribute prediction, researchers frequently resort to data pretreatment, aiming to reduce noise and highlight the spectral features. Even with the awareness of the existence of dimensionality reduction statistical approaches that can cope with data sparse dimensionality, few studi...

The biophysical parameters of coffee plants can provide important information to guide crop management. An alternative to traditional methods of sparse hand measurements to obtain this type of information can be the 3D modeling of the coffee canopy using aerial images from RGB cameras attached to remotely piloted aircraft (RPA). This study aimed to...

Monitoring the spatial variability of agricultural variables is a main step in implementing precision agriculture practices. Active optical sensors (AOS), with their instrumentation directly on agricultural machines, are suitable and make it possible to obtain high-frequency data. This study aimed to evaluate the potential of AOS to map the spatial...

Yield maps guide investigations into the causes of spatial and temporal variations in crop yields. The objective of this work was to implement an algorithm based on computer vision to quantify the number of coffee fruits and to build yield maps. Data were collected in two areas of a commercial Arabica coffee (Coffea arabica) plantation. The images...

Coffee producers are ever more interested in understanding the dynamics of coffee's spatial and temporal variability. However, it is necessary to obtain high-density yield data for decision-making. The objective of this study is to evaluate the quality of yield data obtained through a yield monitor onboard a coffee harvester, as well as to evaluate...

Proximal soil sensing technologies, such as visible and near infrared diffuse reflectance spectroscopy (VNIR), X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS), are dry-chemistry techniques that enable rapid and environmentally friendly soil fertility analyses. The application of XRF and LIBS sensors in an indi...

Mapping soil fertility attributes at fine spatial resolution is crucial for site-specific management in precision agriculture. This paper evaluated the performance of mobile measurements using visible and near-infrared spectroscopy (vis–NIR) to predict and map key fertility attributes in tropical soils through local data modeling with partial least...

The Laser Induced Breakdown Spectroscopy (LIBS) is a promising technique for soil fertility analysis in a rapid and environmentally friendly way. This application requires the selection of an optimal modelling procedure capable of handling the high spectral resolution of LIBS. This work aimed at comparing different modelling methods of LIBS data fo...

Many endeavours in precision agriculture use some kind of sensor to gain relatively inexpensive information on the spatial and temporal variation in crops, soil, weeds, diseases, and so on. However, information about sensors is scattered throughout the literature. This text fills an important niche by bringing together information on a wide range o...

This chapter presents case studies that focus on canopy sensing using proximal and unmanned aerial vehicle (UAV)-mounted optical sensors, rather than satellite-based optical sensing applications. The potential use of optical canopy sensing for crop quality and quantity is explored across four varied case studies. The case studies have been chosen t...

Coffee is a crop of great relevance in socioeconomic terms for Brazilian agribusiness, which is the world’s largest producer in cultivated areas. The implementation of precision agriculture in the coffee culture has provided countless benefits to its development, which over the years has been cultivated in the same area. However, there is a lack of...

The decision on crop population density should be a function of biotic and abiotic field parameters and optimize the site-specific yield potential, which can be a real challenge for farmers. The objective of this study was to investigate the yield of maize hybrids subjected to variable rate seeding (VRS) and in differentiated management zones (MZs)...

Data-driven decisions can be performed based on crop yield values, essential information for precision agriculture practices. Technical solutions for yield mapping have been increasing for the sugarcane crop. However, the adoption of a yield monitor is low among farmers. An alternative is associating the amount of sugarcane harvested with the yield...

The adoption of precision agriculture involves a demand for equipment and solutions to create an accurate diagnostic of the spatial variability to be managed at the field level. Sugarcane has faced some challenges due to the limited solutions adapted to the crop, which develops throughout the year and involving a large-scale harvest. LiDAR (Light D...

There is a need for new precision agriculture approaches that allow real-time intervention within sugarcane rows to reduce costs and minimize negative environmental impacts. Therefore, our goal was to test an alternative system for detection within rows of sugarcane plants. The objective was to determine the errors of an alternative system to detec...

Identifying gaps within sugarcane rows is an effective strategy to optimise inputs using site-specific approaches. This work aimed to compare four different sensor-based techniques to identify and measure sugarcane gaps.Specifically, it was analysed three strategies with sensors (vegetative index, ultrasonic, photoelectric) mounted on a tractor, an...

Measuring the mass flow of sugarcane in real-time is essential for harvester automation and crop monitoring. Data integration from multiple sensors should be an alternative to receive more reliable, accurate, and valuable predictions than data delivered by a single sensor. In this sense, the objective was to evaluate if the fusion of different sens...

Rapid, cost-effective, and environmentally friendly analysis of key soil fertility attributes requires an ideal combination of sensors. The individual and combined performance of visible and near infrared (VNIR) diffuse reflectance spectroscopy, X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS) was assessed for...

It is known that Near-infrared spectroscopy (NIRS) is a reliable technique used in industrial laboratories to measure sugarcane quality. However, its use as a proximal sensing technology for monitoring the spatial variability of attributes in the fields has not yet been evaluated. The aim of this research was to examine the potential of NIRS for pr...

Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (...

In this study, an algorithm is implemented with a computer vision model to detect and classify coffee fruits and map the fruits maturation stage during harvest. The main contribution of this study is with respect to the assignment of geographic coordinates to each frame, which enables the mapping of detection summaries across coffee rows. The model...

The understanding of the interaction between soil physicochemical attributes and herbicide behavior is fundamental for optimizing the efficient use of PRE-emergence herbicides in a more sustainable approach. However, it is still a poorly studied area within precision agriculture. Thus, the objective of this research was to evaluate the correlation...

Information regarding sugarcane yield is the starting point for the application of Precision Agriculture (PA) strategies to the management of sugarcane fields. Over the years, many sugarcane yield monitoring approaches have been developed and tested, but its use is still limited. One option is to use data generated by the sugarcane harvester provid...

The considerable volume of data generated by sensors in the field presents systematic errors; thus, it is extremely important to exclude these errors to ensure mapping quality. The objective of this research was to develop and test a methodology to identify and exclude outliers in high-density spatial data sets, determine whether the developed filt...

Yield maps provide essential information to guide precision agriculture (PA) practices. Yet, on-board yield monitoring for sugarcane can be challenging. At the same time, orbital images have been widely used for indirect crop yield estimation for many crops like wheat, corn, and rice, but not for sugarcane. Due to this, the objective of this study...

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange ca...

Crop rotation with leguminous species in sugarcane cultivation is increasing in the southeastern regions of Brazil. Most of researches done on sugarcane is focused on yield regardless its final product. In the specific case of sugarcane ethanol production, studies rely basically on the economic and sustainable points of view overlooking the energy...

Site-specific management practices have been possible due to the wide range of solutions for data acquisition and interventions at the field level. Different approaches have to be considered for data collection, like dedicated soil and plant sensors, or even associated with the capacity of the agricultural machinery to generate valuable data that a...

Nitrogen management in crops is a key activity for agricultural production. Methods that can determine the levels of this element in plants in a quick and non-invasive way are extremely important for improving production systems. Within several fronts of study on this subject, proximal and remote sensing methods are promising techniques. In this re...

Lack of yield mapping solutions is currently a bottleneck for Precision Agriculture development and adoption in many manually harvested fruit and vegetable crops. In such systems, the handpicked produce is briefly stored in bags or boxes across the field before they are loaded and transported. This study tested a simple yield mapping method based o...

Core objectives of precision agriculture are to improve the economic and environmental performance of agricultural systems. This study used a long-term experiment in citrus to assess whether site-specific nutrient management was successful from these two perspectives. Variable and uniform rate fertilisation treatments were implemented in intercalat...

MapFilter 2.0 is a software for analyzing and removing inconsistent data in high density agricultural data sets (data from crop monitor, plant sensors, soil sensors). It is a simple software, with a friendly interface, whose objective is to help users to generate maps related to their cropping areas with greater reliability from the optimization of...

The adaptation of the Global Navigation Satellite Systems (GNSS) technology to fit the needs of farmers requires knowledge of the accuracy level delivered by a GNSS receiver in working conditions. To date, no methodology indicates the minimum number of replications to perform a statistical comparison. This study aims to advance knowledge on the met...

Soybean yield estimation is either based on yield monitors or agro-meteorological and satellite imagery data, but they present several limiting factors regarding on-farm decision level. Aware that machine learning approaches have been largely applied to estimate soybean yield and the availability of data regarding soybean yield and its components (...

Sugarcane harvesters have a high level of embedded technology and the opportunity to expand applications to become an important high-density data collection machine. The acquired data, such as yield, losses, and quality, would provide valuable information for site-specific management of sugarcane. This review describes the current instrumentation u...

Currently the centrifugal spreaders are the most used for lime application in Brazil. The pendulum-action spreaders have characteristics that differentiate them from the centrifugal, such as a symmetrical pattern and the possibility to apply in different widths with the spout change, but are normally not used for lime application due to its high ra...

The matrix effect is one of the challenges to be overcome for a successful analysis of soil samples using X-ray fluorescence (XRF) sensors. This work aimed at evaluation of a simple modeling approach consisted of Compton normalization (CN) and multivariate regressions (e.g., multiple linear regressions (MLR) and partial least squares regression (PL...

Carrot yield maps are an essential tool in supporting decision makers in improving their agricultural practices, but they are unconventional and not easy to obtain. The objective was to develop a method to generate a carrot yield map applying a random forest (RF) regression algorithm on a database composed of satellite spectral data and carrot grou...

The need for accuracy in sugarcane machine traffic has boosted the adoption of automatic steering systems. These have been used in tractors pulling transhipment trailers. Such sets are long and articulated, which hinders their performance and benefits due to alignments in curved and laterally sloped paths. In this sense, this study aimed to quantif...

The successful use of energy-dispersive X-ray fluorescence (ED-XRF) sensors for soil analysis requires the selection of an optimal procedure of data acquisition and a simple modelling approach. This work aimed at assessing the performance of a portable XRF (XRF) sensor set up with two different X-ray tube configurations (combinations of voltage and...

The mapping of sugarcane yield is still not as widely available as it is for grain crops. Sugarcane harvesters cut and process the cane in a single or maximum of two rows, facilitating the monitoring of cane yield and its behavior on a small scale. This study tested a method for sugarcane yield data cleaning, investigating if the data recording fre...

O LAP (Laboratório de Agricultura de Precisão) tem disponibilizado boletins técnicos e temáticos, com linguagem técnica de fácil entendimento. Anunciamos o Boletim Técnico 05 – Sensores ópticos ativos, com uma ampla abordagem sobre o tema, esperando contribuir para a popularização destas ferramentas, fundamentais para a gestão localizada das lavour...

A utilização de Sistemas Globais de Navegação por Satélite (GNSS) expandiu-se na agricultura aliada à necessidade de maior acurácia para execução de atividades agrícolas. O objetivo deste trabalho foi comparar o erro transversal de quatro receptores código C/A e dois receptores frequência L1 com código P, utilizando como referência um GNSS com sist...

Portable X-ray fluorescence (pXRF) sensors allow one to collect digital data in a practical and environmentally friendly way, as a complementary method to traditional laboratory analyses. This work aimed to assess the performance of a pXRF sensor to predict exchangeable nutrients in soil samples by using two contrasting strategies of sample prepara...

Soil fertility attributes have different scales and forms of spatial and temporal variations in agricultural fields. Adequate spatiotemporal characterization of these attributes is fundamental to the successful development of strategies for variable rate application of fertilizers, enabling the classic benefits of precision agriculture (PA). Studie...

Spatial variability evaluation of qualitative attributes can be used as an excellent strategy to design forms of intervention that result in better crop profitability for some agricultural crops, for example, sugarcane. Based on the assumption that qualitative attributes of sugarcane present spatial variability and their distributions along the ste...

Characterizing crop spatial variability is crucial for estimating the opportunities for site-specific management practices. In the context of tree crops, ranging sensor technology has been developed to assess tree canopy geometry and control real-time variable rate application of plant protection products and fertilizers. The objective of this stud...

Site-specific management strategies are usually dependant on the understanding of the underlying cause and effect relationships that occur at the within-field level. The assessment of canopy geometry of tree crops has been facilitated in recent years through the development of light detection and ranging sensors mounted on terrestrial platforms. Th...

Elemental analysis techniques, such as X-ray fluorescence (XRF), are compatible with direct analysis of soils, allowing to collect digital data in a practical way and without the generation of chemical waste. Assessing the analytical performance of these techniques in function of different strategies of samples preparation is fundamental for the de...

Laser sensor applications associated with LiDAR (Light Detection and Ranging) technology on platforms allow the evaluation of crop and forest biomass in a non-invasive way. This study presents the development of a measurement system based on LiDAR technology aimed at the proposed assessment of the height of sugarcane plants during the pre-harvest p...

O conhecimento do ciclo das culturas, dos padrões de crescimento e desenvolvimento das plantas é fundamental para a gestão da lavoura. As informações sobre o rendimento físico (produtividade) e o custo de produção da cultura são primordiais na administração de uma empresa agrícola. A análise da eficiência da produção juntamente com o estudo de seus...

Ultrasonic and light detection and ranging (LiDAR) sensors have been some of the most deeply investigated sensing technologies within the scope of digital horticulture. They can accurately estimate geometrical and structural parameters of the tree canopies providing input information for high-throughput phenotyping and precision horticulture. A rev...

The objective of this work was to assess the performance of an antimony ion-selective electrode (ISE) sensor system, using manual and automatic operating modes, for measuring the potential of hydrogen (pH), in real time, in Oxisols with different characteristics. Samples were manually collected and sent to a laboratory for determination of pH in wa...

The objective of this work was to assess the performance of an antimony ion-selective electrode (ISE) sensor system, using manual and automatic operating modes, for measuring the potential of hydrogen (pH), in real time, in Oxisols with different characteristics. Samples were manually collected and sent to a laboratory for determination of pH in wa...

Laser sensors based on LiDAR (Light Detection and Ranging) technology and aerial images acquired by remotely piloted aircraft (RPA) are remote sensing techniques applicable to the agricultural production environment for identification of spatial variability of crops. The objective is to employ such techniques in sugarcane to detect the canopy plant...

Soil sensing techniques allow obtaining data in high spatial density and can aid the traditional techniques of soil mapping for a reliable characterization of soil attributes. Currently, among the sensing techniques, the apparent electrical conductivity (ECa) and the imaging using orbital sensor systems are highlighted. These techniques can work in...

Vis-NIR reflectance spectroscopy is one of the techniques used for soil sensing and has been outstanding for the prediction of its clay and organic matter (OM) contents. The technological advance has allowed the development of spectroradiometers of reduced size and more affordable prices. So, the present work sought to evaluate the potential of a p...

Sphenophorus levis is one of the main soil pests of sugarcane. The diagnosis is performed by sampling the whole field, in a fixed density. Its distribution does not occur in a random manner, being influenced by the physical-chemical properties of the soil. The objective of this work was to explore the relationships between the spatial distribution...