Application of electronic nose and machine learning used to detect soybean gases under water stress and variability throughout the daytime.

The development of non-invasive methods and accessible tools for application to plant phenotyping is considered a breakthrough. This work presents the preliminary results using an electronic nose (E-Nose) and machine learning (ML) as affordable tools. An E-Nose is an electronic system used for smell global analysis, which emulates the human nose structure.

Exploring the Adoption of Precision Agriculture for Irrigation in the Context of Agriculture 4.0: The Key Role of Internet of Things.

In recent years, the concept of Agriculture 4.0 has emerged as an evolution of precision agriculture (PA) through the diffusion of the Internet of things (IoT). There is a perception that the PA adoption is occurring at a slower pace than expected.

Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture.

The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished.

Sustained enhancement of photosynthesis in coffee trees grown under free-air CO2 enrichment conditions: disentangling the contributions of stomatal, mesophyll, and biochemical limitations.

Coffee (Coffea spp.), a globally traded commodity, is a slow-growing tropical tree species that displays an improved photosynthetic performance when grown under elevated atmospheric CO2 concentrations ([CO2]). To investigate the mechanisms underlying this response, two commercial coffee cultivars (Catuaí and Obatã) were grown using the first free-air CO2 enrichment (FACE) facility in Latin America.

Soil calcium and pH monitoring sensor system.

An agrarian sensorial system based on temperature, moisture, and all solid-state ion-selective potentiometric sensors was developed with the objective of monitoring the behavior of H+ and Ca2+ ions in soil and in real conditions, contributing with a new tool that tries to complement the current precision agriculture technology. The evaluation of the sensorial system to pH monitoring presented a good correlation between the results obtained by the system and the standard methodology, allowing us to notice the soil buffer capacity at different soil depths. With regard to calcium, the sensor system also presented an agreement between its results and those obtained by flame atomic absorption spectrometry, using a calibration model based on multiple linear regressions that allows the correct determination of Ca2+ concentrations in soil depths where the relative moisture is different.

In-soil potassium sensor system.

A potentiometric sensor system based on potassium ion-selective electrodes was developed for agricultural purposes. Sensors were built using PVC ion-selective membranes over an inner solid contact prepared with graphite-epoxy composites. A copper plate was used as a reference electrode.