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Artificial Intelligence (AI) has changed how processes are developed, and decisions are made in the agricultural area replacing manual and repetitive processes with automated and more efficient ones. This study presents the application of deep learning techniques to detect and segment weeds in agricultural crops by applying models with different architectures in the analysis of images captured by an Unmanned Aerial Vehicle (UAV). This study contributes to the computer vision field by comparing the performance of the You Only Look Once (YOLOv8n, YOLOv8s, YOLOv8m, and YOLOv8l), Mask R-CNN (with framework Detectron2), and U-Net models, making public the dataset with aerial images of soybeans and beans. The models were trained using a dataset consisting of 3021 images, randomly divided into test, validation, and training sets, which were annotated, resized, and increased using the Roboflow application interface. Evaluation metrics were used, which included training efficiency (mAP50 and mAP50-90), precision, accuracy, and recall in the model's evaluation and comparison. The YOLOv8s variant achieved higher performance with an mAP50 of 97%, precision of 99.7%, and recall of 99% when compared to the other models. The data from this manuscript show that deep learning models can generate efficient results for automatic weed detection when trained with a well-labeled and large set. Furthermore, this study demonstrated the great potential of using advanced object segmentation algorithms in detecting weeds in soybean and bean crops. [ABSTRACT FROM AUTHOR]

In addition to being an important instrument in the search for increasingly greater productivity, agricultural production with adequate use of irrigation systems significantly minimizes the impact on water resources. To meet high productivity and yield, as well as industrial quality, a series of studies on sugarcane cultivation are necessary. Despite being able to adapt to drought, sugarcane is still a crop highly dependent on irrigation to guarantee the best quality standards. Our study aimed to analyze the agronomic performance and technological attributes of two sugarcane cultivars, evaluating the vegetative and productive pattern, as well as the industrial quality of the cultivars RB92579 and SP80–1816, which were cultivated under split-irrigation management in the Sugarcane Research Unit of IF Goiano—Campus Ceres, located in the state of Goiás in the Central-West region of Brazil. A self-propelled sprinkler irrigation system (IrrigaBrasil) was used, duly equipped with Twin 120 Komet sprinklers (Fremon, USA). The cultivars were propagated vegetatively and planted in 0.25 m deep furrows with 1.5 m between rows. The experiment was conducted in a completely randomized design (CRD), with a bifactorial split-plot scheme (5 × 2), with four replications, where the experimental plots were subjected to one of the following five split-irrigation management systems: 00 mm + 00 mm; 20 mm + 40 mm; 30 mm + 30 mm; 40 mm + 20 mm; or 60 mm + 00 mm. At 60 and 150 days after planting (DAP), the following respective irrigation management systems were applied: 00 mm + 00 mm and 20 mm + 40 mm. Biometric and technological attributes, such as plant height (PH) and stem diameter (SD), were evaluated in this case at 30-day intervals, starting at 180 DAP and ending at 420 DAP. Measurements of soluble solids content (°Brix), apparent sucrose content (POL), fiber content (Fiber), juice purity (PZA), broth POL (BP), reducing sugars (RS), and total recoverable sugars (TRS) were made by sampling stems at harvest at 420 DAP. RB92579 showed total recoverable sugar contents 11.89% and 8.86% higher than those recorded for SP80–1816 under split-irrigation with 40 mm + 20 mm and 60 mm + 00 mm, respectively. Shoot productivity of RB92579 reached 187.15 t ha−1 under split-irrigation with 60 mm + 00 mm, which was 42.16% higher than the shoot productivity observed for SP80–1816. Both cultivars showed higher qualitative and quantitative indices in treatments that applied higher volumes of water in the initial phase of the culture, coinciding with the dry season. Sugarcane cultivar RB92579 showed a better adaptation to the prevailing conditions in the study than the SP80–1816 cultivar. [ABSTRACT FROM AUTHOR]

Integrating advanced technologies such as artificial intelligence (AI) with traditional agricultural practices has changed how activities are developed in agriculture, with the aim of automating manual processes and improving the efficiency and quality of farming decisions. With the advent of deep learning models such as convolutional neural network (CNN) and You Only Look Once (YOLO), many studies have emerged given the need to develop solutions to problems and take advantage of all the potential that this technology has to offer. This systematic literature review aims to present an in-depth investigation of the application of AI in supporting the management of weeds, plant nutrition, water, pests, and diseases. This systematic review was conducted using the PRISMA methodology and guidelines. Data from different papers indicated that the main research interests comprise five groups: (a) type of agronomic problems; (b) type of sensor; (c) dataset treatment; (d) evaluation metrics and quantification; and (e) AI technique. The inclusion (I) and exclusion (E) criteria adopted in this study included: (I1) articles that obtained AI techniques for agricultural analysis; (I2) complete articles written in English; (I3) articles from specialized scientific journals; (E1) articles that did not describe the type of agrarian analysis used; (E2) articles that did not specify the AI technique used and that were incomplete or abstract; (E3) articles that did not present substantial experimental results. The articles were searched on the official pages of the main scientific bases: ACM, IEEE, ScienceDirect, MDPI, and Web of Science. The papers were categorized and grouped to show the main contributions of the literature to support agricultural decisions using AI. This study found that AI methods perform better in supporting weed detection, classification of plant diseases, and estimation of agricultural yield in crops when using images captured by Unmanned Aerial Vehicles (UAVs). Furthermore, CNN and YOLO, as well as their variations, present the best results for all groups presented. This review also points out the limitations and potential challenges when working with deep machine learning models, aiming to contribute to knowledge systematization and to benefit researchers and professionals regarding AI applications in mitigating agronomic problems. [ABSTRACT FROM AUTHOR]

The applicability of remote sensing enables the prediction of nutritional value, phytosanitary conditions, and productivity of crops in a non-destructive manner, with greater efficiency than conventional techniques. By identifying problems early and providing specific management recommendations in bean cultivation, farmers can reduce crop losses, provide more accurate and adequate diagnoses, and increase the efficiency of agricultural resources. The aim was to analyze the efficiency of vegetation indices using remote sensing techniques from UAV multispectral images and Sentinel-2A/MSI to evaluate the spectral response of common bean (Phaseolus vulgaris L.) cultivation in different phenological stages (V4 = 32 DAS; R5 = 47 DAS; R6 = 60 DAS; R8 = 74 DAS; and R9 = 89 DAS, in 99 days after sowing—DAS) with the application of doses of magnesium (0, 250, 500, and 1000 g ha−1). The field characteristics analyzed were mainly chlorophyll content, productivity, and plant height in an experimental area by central pivot in the midwest region of Brazil. Data from UAV vegetation indices served as variables for the treatments implemented in the field and were statistically correlated with the crop's biophysical parameters. The spectral response of the bean crop was also detected through spectral indices (NDVI, NDMI_GAO, and NDWI_GAO) from Sentinel-2A/MSI, with spectral resolutions of 10 and 20 m. The quantitative values of NDVI from UAV and Sentinel-2A/MSI were evaluated by multivariate statistical analysis, such as principal components (PC), and cophenetic correlation coefficient (CCC), in the different phenological stages. The NDVI and MCARI vegetation indices stood out for productivity prediction, with r = 0.82 and RMSE of 330 and 329 kg ha−1, respectively. The TGI had the best performance in terms of plant height (r = 0.73 and RMSE = 7.4 cm). The best index for detecting the relative chlorophyll SPAD content was MCARI (r = 0.81; R2 = 0.66 and RMSE = 10.14 SPAD), followed by NDVI (r = 0.81; R2 = 0.65 and RMSE = 10.19 SPAD). The phenological stage with the highest accuracy in estimating productive variables was R9 (Physiological maturation). GNDVI in stages R6 and R9 and VARI in stage R9 were significant at 5% for magnesium doses, with quadratic regression adjustments and a maximum point at 500 g ha−1. Vegetation indices based on multispectral bands of Sentinel-2A/MSI exhibited a spectral dynamic capable of aiding in the management of bean crops throughout their cycle. PCA (PC1 = 48.83% and PC2 = 39.25%) of the satellite multiple regression model from UAV vs. Sentinel-2A/MSI presented a good coefficient of determination (R2 = 0.667) and low RMSE = 0.12. UAV data for the NDVI showed that the Sentinel-2A/MSI samples were more homogeneous, while the UAV samples detected a more heterogeneous quantitative pattern, depending on the development of the crop and the application of doses of magnesium. Results shown denote the potential of using geotechnologies, especially the spectral response of vegetation indices in monitoring common bean crops. Although UAV and Sentinel-2A/MSI technologies are effective in evaluating standards of the common bean crop cycle, more studies are needed to better understand the relationship between field variables and spectral responses. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Research in the Tropics / Pesquisa Agropecuária Tropical is the property of Pesquisa Agropecuaria Tropical and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aimed to verify the effects of leaf application of zinc (Zn) on the growth, physiology, yield, and biofortification of snap beans. The experiment was carried out in a greenhouse, in a completely randomized design, with five doses of zinc (0, 100, 200, 300, and 400 mg L−1). The leaf application of zinc was carried out at the vegetative stage V3 (third leaves). Biometric, physiological, and yield evaluations occurred at stages R5 (flowering) and R8 (harvest). The chlorophyll of plants with zinc is 36% higher with the application of 400 mg L−1 in R8. Foliar fertilization reduced the transpiration around 41%; and it increased the temperature and photosynthetic rate at 5.2% and 16.2%, respectively. The zinc concentration increases up resulted in an increase of 85 and 942% of zinc accumulation in the snap bean plant at the R5 stage. The 100 mg L−1 dose increased crop yield by 8.4% compared to the control treatment. Higher doses can reduce productivity by up to 17% when 400 mg L−1 of Zn is applied. Foliar application of zinc is efficient in promoting an increase in the concentration and accumulation of Zn in the leaves in the stage R5, but at the harvest stage there is no influence of fertilization on the levels and accumulations of zinc in the plant. [ABSTRACT FROM AUTHOR]

Understanding and characterizing the relationship between soil and environmental temperatures is crucial for developing effective agricultural management strategies, promoting natural resource conservation, and developing sustainable production systems. Despite the direct impact of the thermal properties of Oxisols on global food production and sustainable agriculture, there is a dearth of research in this area. Therefore, this study aimed to monitor and analyze the thermal behavior of a Red Latosol (Oxisol) in Dracena-SP, Brazil, over two years (from 28 July 2020 to 27 July 2022). Using R software (version 4.3.0) and paired group comparisons, we organized the data into twelve-month sets to estimate monthly soil thermal diffusivity using amplitude, arctangent, and logarithm methods. Soil depth and thermal amplitude showed a temporal pattern characterized by inversely proportional magnitudes that followed an exponential behavior. The thermal amplitude of the Oxisol evaluated decreased with increasing depth, indicating soil thermal damping. In conclusion, the relationship between Oxisol and environmental temperature has significant implications for achieving sustainable agriculture and efficient water and plant resource management. [ABSTRACT FROM AUTHOR]

Cerrado has soils characterized by high rates of nutrient losses, either by runoff or leaching, caused mainly by rainfall intensity in the region. Among nutrients, potassium, due to its characteristics, has great potential of being lost by leaching. Thus, this study evaluates the effect of application of potassium (K) fertilizer and different irrigation depths on the potential for K leaching in soils with different granulometries. For this purpose, 60 undisturbed soil monoliths were collected and distributed in soil samples with three different granulometric ratios. The experiment was performed in a mesocosm with a randomized block design in a factorial scheme with three replicates, consisting of five doses of potassium (0, 50, 100, 150, and 200 kg ha−1) and four irrigation depths (50%, 100%, 150%, and 200% of the irrigation depth obtained in the field capacity). Potassium leaching was evaluated over 80 days of incubation, as well as the potassium remaining in the soil at the end of the experiment. The data demonstrated the effect of application of irrigation depths on the sandy loam soil. As the clay content increased, irrigation depths did not affect the K content leached. Thus, this study demonstrated that different irrigation depths on the soil may not affect the potassium content remaining in the system. [ABSTRACT FROM AUTHOR]

Irrigated agriculture has become a concern, given the scarcity of freshwater. To reduce its water consumption, new techniques and technologies have been proposed. Based on this, the objective of this work was to evaluate the influence of different soil water tensions at initiation of irrigation with magnetically treated water, on 'iceberg' lettuce Lucy Brown (Lactuca Sativa L.) development and production. The experiment was conducted in a greenhouse, using a completely randomized factorial design, to evaluate two water types (magnetically treated water - MW and ordinary water - OW) and four soil water tensions at initiation of irrigation (T1 - 15 kPa, T2 - 25 kPa, T3 - 40 kPa and T4 - 70 kPa), with three replicates. Tensiometers were used to estimate soil water tension. The evaluated parameters were: aerial part fresh and dry total mass; commercial head fresh and dry mass, root fresh and dry mass; stem fresh and dry mass; stem length and diameter; percentage of leaves with tip burn, total and commercial yield; water use efficiency related to total and commercial yield; plant exposed area; and dry matter content. Despite achieving greater water use efficiency, the magnetic treatment may have hindered the removal of water from the soil by the crop, especially at increased soil water tension at initiation of irrigation. [ABSTRACT FROM AUTHOR]

Copyright of Revista Facultad Nacional de Agronomía Medellín is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Facultad Nacional de Agronomía Medellín is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to evaluate the filtration process of a commercial sand filter operating at different filtration rates and different sand particle sizes. The second objective is to carry out sand filter efficiency evaluations and compare the standard sand filter method and the proposed method. Removal efficiency was analyzed in three filtration cycles, and determined by two methodologies: counting of particles in water at the inlet and outlet of the filtration system (standard method) and in sand bed layers (proposed method). An experimental module composed of three identical commercial sand filters was used with different sand particle sizes (G1 - 0.55 mm of sand effective diameter, G2 - 0.77 mm and G3 - 1.04 mm) and filtration rate combinations (20, 40, 60, and 75 m3 m-2 h-1), repeated for three filtration cycles (C1, C2 and C3), 4 h per cycle. The removal efficiency of sand filters increases as the filtration rate increases for the water quality used, and sand particle size decreases. Between the methodologies applied to evaluate filtration systems, the method using total suspended solids retained in sand (proposed method) has shown a greater potential when compared with the standard method. The evaluation methodology proposed provides a global and accurate evaluation of the process. This form of estimation does not have the representability problem punctual water samples collected during filtration have. In addition, it is a promising methodology for farmers and technicians to carry out equipment evaluations in the field. [ABSTRACT FROM AUTHOR]

Given the current water scarcity and aiming at sustainable agricultural development, it is necessary to identify and apply the most appropriate practices for water saving, also considering yield and water productivity improvement. Tomato is a high-water-demand vegetable crop, and excessive use of irrigation water generally leads to overexploitation of groundwater resources and deterioration of the environment. In addition, excess irrigation water leads to low water productivity (yield/water use ratio). Thus, there is an urgent need to increase crop yield with concomitant conservation of water resources. This study aimed to identify the effect of regulated deficit irrigation on the yield and water productivity of tomato cultivar N-901 for industrialization purposes. Deficit irrigation was carried out during the vegetative growth stage, considering different seedling transplanting periods. The experiment was conducted in a greenhouse at the School of Agronomy of the Federal University of Goiás (UFG). The experimental design was a randomized complete block with five replicates, in a 2 x 4 factorial arrangement. The plots were made by combining two periods of irrigation deficit (10 and 20 days after transplanting - DAT) and four soil water tension thresholds (30; 40; 60; and 70 kPa). The results showed that the studied cultivar responded significantly to the water deficit, providing different agronomic development profiles. The tensions of 30 and 60 kPa applied at 10 DAT were the ones that most intensified yield and water productivity without significantly affecting the agronomic development of the crop. Deficit irrigation at 60 kPa was shown to reduce the total volume of water applied during the cycle without significantly reducing crop production compared to the tension of 30 kPa. [ABSTRACT FROM AUTHOR]

Water management for irrigation can be defined as a strategy of planning and support systems to save and optimize water resources for human and environmental purposes. Regulated deficit irrigation (RDI) or soil water deficit is a strategy where the amount of water used is kept below the maximum level, and the minor stress that develops has minimal effects on yield. In this irrigation model, the entire root zone is irrigated at less than the maximum crop evapotranspiration, in different phenological phases, without interfering significantly in the physiological behavior of crops. This allows a quantitative and qualitative increase in different crops, and water use efficiency in the agriculture. The present study aimed to identify the effect of regulated deficit irrigation on the qualitative standards of tomato cultivar N-901 for industrialization purposes. Deficit irrigation was carried out during the vegetative growth stage, considering different seedling transplanting periods. The experiment was conducted in a greenhouse at the School of Agronomy of the Federal University of Goias (UFG). The experimental design was a randomized complete block with five replicates, in a 2 x 4 factorial arrangement. The plots were made by combining two periods of irrigation deficit (10 and 20 days after transplanting - DAT) and four soil water tension thresholds (30; 40; 60; and 70 kPa). The results showed that the studied cultivar responded significantly to the soil (substrate) water tension, providing different agronomic development profiles. Water deficit was shown to reduce the total volume of water applied during the cycle, increasing the concentration of soluble solids in the fruits and maintaining titratable acidity in the standards of processing industries, in addition to increasing pulp yield when compared to processing industries. The tensions of 60 and 70 kPa applied at 10 DAT were the ones that most intensified the soluble solids content without significantly affecting the agronomic development of the crop. [ABSTRACT FROM AUTHOR]

Copyright of Agricultural Research in the Tropics / Pesquisa Agropecuária Tropical is the property of Pesquisa Agropecuaria Tropical and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• The hydraulic architecture of rice changes along the stem, decreasing average diameters from bottom to top. • Sampling in different longitudinal positions increases precision of the estimate of hydraulic conductivity by the Hagen-Poiseuille equation. • The estimated value of hydraulic conductivity was increasing with the increase in temperature. The morphological characteristics of the xylem elements influence water ascent in the plants. Few models determine the physical process of water movement in the vascular system of plants based on the hydraulic architecture. This study aims to determine the anatomical characteristics of the xylem and potential hydraulic conductivity at different positions along the stem of rice (Oryza sativa L.). The xylem vessels characteristics were examined in four internodes using three segments in each internode. The analogy between Ohm's law and Hagen-Poiseuille was used to determine the hydraulic conductivities at three temperatures (18, 25, and 33 °C). A successive decrease in the mean vessel diameters from bottom to top stem was observed, with a significant difference between internodes. Between the Internode I and II, there was a 12% reduction in the mean diameter; between the II and III, and III and IV, the decrease was 10 and 28%, respectively. When separated into groups (left and right metaxylem), there was variation in the hydraulically weighted vessels. There was variation in the estimated value of hydraulic conductivity as a function of temperature and along the stem from the base (Internode I) to the plant's top (Internode IV). The decrease in hydraulic conductivity was 41.1 (I–II), 24 (II–III), and 73.4% (III–IV). The estimated value of hydraulic conductivity was increasing with increase in temperature. The variation of the hydraulic conductivity along the useful length of rice allowed a better application of the Hagen-Poiseuille equation. [ABSTRACT FROM AUTHOR]

Computational fluid dynamic (CFD) can be used to quantify the internal flow variables of xylem conducting vessels. This study aims to analyze through numerical simulations the xylem water ascent of African mahogany (Khayagrandifoliola) cultivated under different irrigation regimes. We determined a geometric model, defined through the variability of the anatomical structures of the species, observing characteristics of the xylem vessels such as diameter, length, number of pits, and average surface area of the pits. Then we applied numerical simulation through an Eulerian mathematical model with the discretization of volumes via CFD. Compared to other models, we observed that numerical simulation using CFD represented the xylem microstructures in a greater level of detail, contributing to the understanding of the flow of xylem vessels and the interference of its various structures. Analyzing the micrographs, we observed the non-irrigated vessels had a higher number of pits in the secondary wall thickening when compared to the irrigated treatments. This trend influenced the variability of the radial flow of the xylem vessels, causing greater fluid movement in this region and decreasing the influence of the smooth part of the wall, resulting in a lower total resistance of these vessels. [ABSTRACT FROM AUTHOR]

Precision irrigation is essential to improve water use efficiency (WUE), defined as the amount of biomass produced per unit of water used by plants. Our objective is to evaluate the effect of different soil volumetric water content (VWC) in plant growth, fruit yield, quality, and WUE of cherry tomatoes grown in a greenhouse. We tested four VWC thresholds (0.23, 0.30, 0.37, and 0.44 m3 m−3) to trigger a drip irrigation system in two tomato cultivars ('Sweet Heaven' and 'Mascot F1'). The experiment was arranged in a split-plot design with four replications. We used capacitance sensors connected to an open-source, low-cost platform to monitor and control the irrigation in real-time based on demand. Plants were watered every time the soil VWC dropped below the set thresholds. The treatment with VWC 0.44 m3 m−3 resulted in the highest fruit yield, with 102.10% higher WUE when compared to the VWC 0.23 m3 m−3 in both cultivars. Fruit quality traits such as longitudinal and equatorial diameter increased asymptotically with soil water content. In contrast, treatments with deficit irrigation increased the fruit soluble solids by 15.73% in both cultivars. These results strongly suggest that accurate control of the soil VWC is essential to modulate the fruit yield and quality attributes in tomatoes produced in the greenhouse. [ABSTRACT FROM AUTHOR]