The coffee industry stands out worldwide due to its socioeconomic importance, acting directly or indirectly in the most diverse sectors. With this, new technologies and several harvester models have emerged. These harvesters have regulations that can influence the efficiency of harvesting, the selectivity of fruits and the preservation of the crop. In this way, the understanding of the behavior of

Greenhouses provide controlled environmental conditions for crop cultivation but require careful management to ensure ideal growing conditions. In this study, we tested three deep-learning-based neural network models (Artificial neural network, ANN; Nonlinear autoregressive exogenous model, NARX; and Recurrent neural networks – Long short-term memory, RNN-LSTM) to determine the best approach to predicting

Plant diseases have a disastrous impact on the safety of food production, and they can cause a significant reduction in both the quality and quantity of agricultural products. In severe cases, plant diseases may even cause no grain harvest entirely. Thus, the automatic identification and diagnosis of plant diseases are highly desired in the field of agricultural information. Many methods have been

Effective non-destructive methods for identifying poor quality and knotty timber in standing trees can contribute to higher quality timber reaching the appropriate processing mills and to a reduction in transport costs of harvested timber. Eucalyptus nitens is a major temperate plantation hardwood species primarily used in paper production. More recently it has also been considered as a potentially

Fruit production represents an important economic resource for many countries. The size and shape of fruits are crucial in production systems because they affect the market value. Particularly, in tomatoes (Solanum lycopersicum), the number of seed-containing cavities within each fruit, called locules, affects these attributes. The number of locules is also relevant for genotype-phenotype association

Unmanned helicopters are used widely in precision agriculture, especially in East Asia. However, the development of the downwash flow field of unmanned helicopters, which strongly influences the movement of spray droplets in the air, is poorly understood. Therefore, an indoor measurement technique was developed to investigate the downwash flow field of a 1:10 scaled unmanned agricultural helicopter

The accurate detection and treatment of weeds in agricultural fields is a necessary procedure for managing crop yield and avoiding herbicide pollution. With the emergence of unmanned aerial vehicles (UAV), the ability to acquire spatial data at the desired spatial and temporal resolution became available, and the resulting input data met high standards for weed management. In this paper, we tested

By using precision agriculture as the basis for site-specific input applications, this study describes the development and implementation of a web-based computational tool for the spatial analysis of agricultural data and the creation of thematic maps. This tool, which is integrated into the R software environment, can create thematic maps using ordinary kriging and inverse distance weighting interpolation

Thermal image quality is critical to accurately quantify spatial and temporal growth and stress patterns of field crops. Image data quality from a thermal sensor can be impacted by several factors including environment, flying altitude, and camera focal length. Often times the thermal sensor selection is based upon price or ease of availability for research. Metrics are available to select the flight

The traditional practice of burning at the pre-harvesting of sugarcane has being phased-out in Brazil, resulting in the maintenance of a crop s residue layer on soil surface, namely the Green Cane Trash Blanket (GCTB). New technologies for electricity and second-generation ethanol (2G) production from crop residues have raised the question on what would be the optimum amount of crop residue left on

The grooved-wheel drilling device is one of the most widely used seeding and fertilizing equipment in developing countries. In the drilling process of the grooved wheel, the particles (fertilizers or seeds) are subject to great force which easily causes the particles broken or the grooved wheel stuck. Therefore, in this paper, the EDEM simulation software was used to analyze the velocity of and force

The continual management of pest species and their preventative elimination is an ongoing, labour-intensive problem. Bait stations are pivotal in this management process as they are the point of contact between the rodents and the process, since the rodents need to enter the bait stations to consume the poisoned bait. Monitoring of these bait stations provides feedback of the effectiveness of the management

According to studies, the human population would cross 9 billion by 2050 and the food demand would increase by 60%. Therefore, increasing and improving the quality of the crop yield is a major field of interest. Recently, infectious biotic and abiotic diseases reduce the potential yield by an average of 40% with many farmers in the developing world experiencing yield losses as high as 100%. Farmers

The Decision Support System for Agrotechnology Transfer Cropping Systems Model (DSSAT-CSM) is a widely used modeling system. The DSSAT R package was developed to provide tools that would facilitate preparing required model inputs, executing simulations, and processing and analyzing outputs for DSSAT-CSM. This application note demonstrates the use of this new package for building reproducible crop modeling

Advanced intelligent systems are becoming significant to many sectors, including farming. In agriculture, the intelligent classification of post-harvested fruits seems to have a direct impact on farmers, mainly for export products. Unlike other popular fruits, coconuts tend to have limited studies due to its tropical nature grown in developing countries as well as its unique physical structure. In

Some specialty crops, such as strawberries and table grapes, are harvested by large crews of pickers who spend significant amounts of time carrying empty and full (with the harvested crop) trays. A step toward increasing harvest automation for such crops is to deploy harvest-aid robots that transport the empty and full trays, thus increasing harvest efficiency by reducing pickers’ non-productive walking

Harvest-aid robots that transport empty and full trays during manual harvesting of specialty crops such as strawberries or table grapes can increase harvest efficiency, by reducing pickers' non-productive walking times. In Part I of this work, a modeling framework, and a stochastic simulator were presented for all-manual and robot-aided harvesting. This paper reports Part II of our work, which utilized

Leaf water potential (LWP) is an effective indicator of plant water deficit. Determining the LWP by remote sensing can contribute to quick and non-destructive drought assessment. The purpose of this study was to investigate the quantitative relationship between LWP and different vegetation indices (VIs). Some previous indices and new indices proposed in this study were used to determine LWP. Our results

The acorn is the fruit of oak trees and is an important crop in the Spanish dehesa extremeña because of the value it provides to feeding Iberian pigs to obtain the “acorn-fed” certification. For this reason, it is desirable to maximise production of Iberian pigs with the appropriate weight. Knowing the area covered by the acorn treetops to determine the Tree-Covered Area (TCA), a value required to

Image analysis technology has drawn dramatic attention and developed rapidly because it enables a non-extractive and non-destructive approach to data acquisition of crab aquaculture. Owing to the irregular shape, multi-scale posture and special underwater environment, it is very challenging to adopt the traditional image recognition methods to detect crabs quickly and effectively. Consequently, we

The plant protection effect of an agricultural unmanned aerial vehicle (UAV) with multiple rotors is closely related to its speed and direction and the spatial and temporal distributions of the effective coverage of the downwash airflow. By combining compressible Reynolds-averaged Navier-Stokes (RANS) equations, the shear stress transport (SST) k-ω turbulence model, sliding grid technology and the

Gravitational flows, like silo discharge, vary in mode and are complex to identify since they depend on various parameters, ranging from silo structural properties to granular material properties. Moreover, the way cohesionless particles arrange themselves during the flow is still a matter of study and new experimental approaches are needed. Here, the paper introduces a new versatile silo model that

Technological advances in the Internet of Things (IoT) have paved the way for wireless technologies to be used in new areas. Agricultural monitoring is an example where IoT can help to increase productivity, efficiency, and output yield. However, powering these devices is a concern as batteries are often required due to devices being located where electricity is not readily available. In this paper

The characteristics of the complex background in crop disease image, the small disease area, and the small contrast between the disease region and the background that easily causes confusion between them, seriously affect the recognition robustness and accuracy. To address these issues, we propose a Self-Attention Convolutional Neural Network (SACNN), which extracts effective features of crop disease

An agricultural backhoe is an important machine designed for multiple assignments in agriculture and livestock. Due to severe working conditions, agricultural backhoe elements are subjected to high loads. Therefore, a structural design must provide a safe machine under all loading conditions at minimum weight and cost. In this work, a 3D model of an agricultural backhoe was proposed, to be used in

Light colors are important for poultry production performance, behavior, and well-being. However, drinking pereferences of layer pullets under light colors that can provide insights into welfare-oriented poultry managements remain unclear. The objectives of this study were to (1) develop a convolutional neural network (CNN) drinking behavior detector and (2) evaluate pullet drinking preferences for

Several vegetation indices have been developed, with the normalized difference vegetation index (NDVI) been the most studied and commonly used. To generate an NDVI map, a relatively high-cost multispectral sensor is required; but currently, most UAVs are equipped with low-cost RGB cameras. For that reason, other indices that utilize RGB data have been developed to generate maps similar to NDVI and

Droplet size, weather conditions and operational parameters of sprayers also affect the spray coverage, absorption attachment to the target. Unmanned aerial vehicles (UAVs) currently, is considered a modern spraying technology which is helpful for efficient spraying. However, the effect of operational parameters on deposition in target and off-target zones still required to determine. Field tests were

An accurate forecast of daily meteorological factors throughout the year is not only of great significance for the study of climate trends in a certain area but also enables the prediction of crop growth stages. Moreover, the prediction of crop growth stages is related to the scheduling of planting and tillage, the determination of machine harvest time, and the prediction of crop yield. However, highly

Sustainable and reliable management requires special attention to factors affecting crop yield. In the present study, a hybrid model of genetic algorithm and artificial neural network (GA-ANN) was employed to recognize the importance of nutrients in pistachio yield. One hundred seventy-five points in different pistachio orchards of Rafsanjan and Anar regions, Kerman province, the southeast of Iran

Crop identification and classification are the basis of fine agricultural development. Hyperspectral remote sensing has been utilized as a cost-efficient approach. Hyperspectral remote sensing data sensing technology has achieved breakthroughs in modern technologies such as long-term dynamic monitoring of crop growth, crop species damage, and acquisition the agricultural information accurately. The

Nitrogen (N) is the most limiting nutrient for cereal crop production, which often results in over-application of N fertilization to maximize crop yield. Negative environmental impacts and long-term reductions in productivity has encouraged site-specific N fertilization approaches, but these require timely and accurate crop N monitoring. The advent of hyperspectral remote sensing potentially provides

High resolution RGB imagery collected using a UAV and a handheld camera was used with structure from motion to reconstruct 3D canopies of small groups of corn plants. A methodology for the automated extraction of phenotypic characteristics of individual plants is presented based on these 3D reconstructed canopies. Such information can enhance the evaluation of crop traits and provide accurate and frequent

To avoid the issues of uneven germination and undesired soil compaction associated with the changing soil conditions, this paper presented the design of an electro-hydraulic downforce control system for planter row units. The control system deployed a PID (Proportional-Integral-Derivative) closed-loop algorithm to control planting downforce exerted on the gauge wheel in response to varying soil conditions

In the present study, moisture content evolution of cylindrical quince slices during convective drying was modelled by using artificial neural networks (ANN). Quince slices with an average initial moisture content of 81% in wet basis (w.b.) or 4.27 kgwater/kgdry matter in dry basis (d.b.), were dried in a laboratory thermal convective dryer and experimental data of moisture content versus drying time

Farmers can manage their crops and farms better if they can communicate their experiences, both positive and negative, with each other and with experts. Digital agriculture using internet communication technology (ICT) may facilitate the sharing of experiences between farmers themselves and with experts and others interested in agriculture. ICT approaches in agriculture are, however, still out of the

We describe in this paper the implementation of E-Water, an open software Decision Support System (DSS), designed to help local managers assess the Water Energy Food Environment (WEFE) nexus. E-Water aims at providing optimal management solutions to enhance food crop production at river basin level. The DSS was applied in the transboundary Mékrou river basin, shared among Benin, Burkina Faso and Niger

This paper presents a novel approach to automated classification and quantification of sow postures and posture transitions that may enable large scale and accurate continuous behaviour assessment on farm. Automatic classification and quantification of postures and posture transitions in domestic animals has substantial potential to enhance their welfare and productivity. Analysis of such behaviours

We developed a simulation model to study the effect of ventilation airflow rate with and without filtered recirculation on airborne contaminant concentrations (dust, NH3, CO, and CO2) for swine farrowing facilities. Energy and mass balance equations were used to simulate the indoor air quality and operational cost for a variety of ventilation conditions over a 3-month winter period, using time-varied