ABSTRACT. We tested the hypothesis that the increase in soil stiffness, induced by variations in bulk density and water content at the tire-soil contact interface, causes a reduction in the contact area. For this, we examined the contact area from different tire-ground contact scenarios and compared the measurements and simulations using a contact area description model. Front and rear tractor tires were used for the measurement of the contact area under tilled soil, sugarcane field, unpaved road, and paved ground scenarios, which induced different bulk densities and water content levels. The results revealed that soil stiffness reduced the tire-soil contact area. The tire-soil contact area increased as the water content increased and the bulk density was reduced. For the front tractor tire, the theoretical contact area was similar to the values found for tilled soil, but there was a large difference between the measurements (2,200 cm2, for the tilled soil) and the theoretical estimates (3,100 cm2) for the rear tractor tire (likely induced by tire dimensions). Our results suggest that increases in soil stiffness reduce the tire-soil contact area. The higher the soil bulk density and the lower the soil moisture, the lower the contact area. The results also revealed that the tire tractor tread might reduce the contact at the hard surface, making the shape of the contact area more geometrically irregular and different from those predicted by models using regular geometry (e.g., cycles, ellipses, or rectangles). This study suggests that two-body (soil and tire) contact models for deformable surfaces should be used in future tire-soil contact models of agricultural field vehicles.

ABSTRACT. In science, technology and assistance to smallholder farming or large crop acreages of Stevia rebaudiana is necessary to report data using information components to facilitate investors to understand the local field conditions to make assertive economic decisions for long periods. Stevia rebaudiana produces consistent natural sweeteners with safe performance as reported in a multitude of scientific publications. The leaf chemicals components are suitable to humans with healthy disorders affected by the consumption of sugarcane or many other industrial sweeteners. Otherwise, aspects related to the agriculture of sweeteners production still require additional discussion to improve qualitative and quantitative traits necessary for cultivating cost-effective crops. The current text highlighted some agriculture decisions necessary to make the crop more profitable to investors as researchers, agriculture influencers, farmer assistants and consultants of companies looking for alternatives within agro-ecological systems.

ABSTRACT. Jangada is a municipality in the Baixada Cuiabana region, State of Mato Grosso, Brazil. This study aimed to evaluate the collection of local cassava conserved by four traditional communities of Jangada in terms of ethnobotanical/socioeconomic and genetic aspects. Socioeconomic and ethnobotanical analyses were carried out with 40 farmers using qualitative techniques and descriptive statistics. Seven microsatellite markers were used for genetic analysis. A total of 182 cassava citations were verified, 31 of which were different. The Broto Branco variety was the most frequent (94.3%), followed by Vermelha Gaiadeira and Liberata (82.9 and 77.1%, respectively). The calculated median age for farmers was 56 years. Spearman’s coefficient indicated a positive correlation between the increase in farmer’s age and the number of cultivated local varieties. Few varieties are planted by many farmers, and most are planted by few farmers. High genetic diversity was observed, and most of the variability occurred within communities (88%). Two groups were formed in the cluster analysis, with two communities in each group. The propagule circulation network helped to understand the genetic similarity of communities with the closest geographic location. Cassava cultivation plays an important role in the studied communities, which maintain a high ethnobotanical and genetic diversity and relevant knowledge about the cultivated varieties.

ABSTRACT. It is common to observe conventional methods for estimating soybean crop yields, making the process slow and susceptible to human error. Therefore, the objective was to develop a model based on deep learning to estimate soybean yield using digital images obtained through a smartphone. To do this, the ability of the proposed model to correctly classify pods that have different numbers of grains, count the number of pods and grains, and then estimate the soybean crop yield was analyzed. As part of the study, two types of image acquisition were performed for the same plant. Image acquisition 1 (IA1) included capturing the images of the entire plant, pods, leaves, and branches. Image acquisition 2 (IA2) included capturing the images of the pods removed from the plant and deposited in a white container. In both acquisition methods, two soybean cultivars, TMG 7063 Ipro and TMG 7363 RR, were used. In total, combining samples from both cultivars, 495 images were captured, with each image corresponding to a sample (plant) obtained through methods AI1 and AI2. With these images, the total number of pods in the entire dataset was 46,385 pods. For the training and validation of the model, the data was divided into subsets of training, validation, and testing, representing, respectively, 80, 10, and 10% of the total dataset. In general, when using the data from IA2, the model presented errors of 7.50 and 5.32% for pods and grains, respectively. These values are considerably lower than when the model used the IA1 data, where it presented errors of 34.69 and 35.25% for pod and grain counts, respectively. Therefore, the data used from IA2 provide better results to the model.

ABSTRACT. This study investigates the meteorological variables exerting the most significant influence on the growth and productivity of four tomato hybrids cultivated for industrial processing in the Brazilian Savannah of Goiás State. Data on morphological and meteorological variables were collected in five locations (Hidrolândia, Itaberaí, Palmeiras de Goiás, Piracanjuba, and Silvânia) during the year 2020. Morphological characteristics assessed included plant height, number of branches, and leaf area index (LAI). Meteorological variables considered were average air temperature, global solar irradiance, thermal sum, and soil water availability. Pearson correlations, canonical correlations, and multivariate Stepwise regression were employed to analyze the relationships between morphological and meteorological variables. The study revealed that soil water availability significantly impacts tomato crop development, indicating the need for improved irrigation management. Adequate irrigation management contributed to an 86.1% increase in plant height and a 79.7% boost in leaf area index, while average air temperature influenced a 34% increase in the number of branches. In conclusion, proper irrigation management is crucial for enhancing tomato crop growth and development and optimizing water use.

ABSTRACT. One of the domains of genetic enhancement that has extensively employed both simulation and authentic data is Biometrics. Selecting efficient models for the Genome-Wide Selection (GWS) process using molecular markers (SNPs) presents several challenges. Among these challenges is the effective identification of the optimal model for fitting a given dataset. To contribute to this endeavor, this paper's primary objective is to assess the predictive accuracy of nine (9) distinct models, each following different paradigms within the realm of Biometrics. The data employed in this study were generated through simulation, encompassing the primary issues encountered in this field of research, including high dimensionality, nonlinearity, and multicollinearity. As the primary findings, notable observations include the enhancement of predictive efficiency as data noise decreases, the predominance of the tree paradigm (for low noise levels, BOO), and the efficacy of the neural network paradigm (for high noise levels, RBF).

ABSTRACT. For a banana tree to reach its productive potential, plants must be nutritionally balanced. Therefore, it is important to use methods that diagnose the nutritional status of plants through chemical leaf analysis, considering the relationships between nutrients and taking advantage of productivity and nutritional monitoring data from orchards. This study aimed to establish norms and ranges of nutrient sufficiency for ‘Nanica’ banana trees in Vale do Ribeira, São Paulo state, using the Diagnosis and Recommendation Integrated System (DRIS) method. Productivity data and chemical analysis of the leaf tissue of 291 commercial plots of Nanica banana trees, collected between 2015 and 2020 in Vale do Ribeira, were used. The DRIS method was used to establish norms and sufficiency ranges for N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn. Fruit yield did not correlate with the average nutritional balance index (NBIa), indicating that its variation was affected by non-nutritional factors. The contents of K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn showed high correlations with their respective nutritional indices. The sufficiency ranges and adequate nutrient contents differed from the values established for bananas in the literature.

ABSTRACT. Rich in oil and protein, canola is a significantly promising crop and is widely explored as an alternative to grain cultivation in the winter period. Recently, canola oil has been largely consumed due to a variety of health benefits and low production costs. Nonetheless, impasses such as determining the correct sowing date and optimizing harvesting methods make it difficult to expand cultivation. Accordingly, the purpose of the study was to evaluate the performance of two canola hybrids on three sowing dates and distinct harvesting procedures. The study was conducted in Cachoeira do Sul, Rio Grande do Sul, Brazil, on three sowing dates (2019, 2020, and 2021), with two hybrids (Hyola 433 and Hyola 575 CL). The methods of direct harvesting, direct harvesting with the application of adjuvant, cut-row, and cut-row with the application of adjuvant were evaluated. The main yield components were determined, in addition to biochemical parameters, such as oil and protein content and determination of oil quality (acid, peroxide, iodine, extinction, and saponification indices). Appropriately, this study indicated that canola is significantly sensitive to climatic conditions, mainly to temperature and sowing time, reducing grain and biomass yield in late sowing and resulting in serious harvest losses. Oil and grain protein contents were affected by climatic conditions. Nevertheless, the protein content was not affected by late sowing. Canola oil presented significant chemical conditions, with a correlation between the crops with higher oil yield and better oil quality.

ABSTRACT. Strawberry cultivation possesses unique features, including the need for high-quality seedlings adapted to the cultivation environment and proper fertigation management. These elements influence plant growth and production. This study evaluated the growth and dry matter partitioning of strawberry plants of the cultivar "Albion" at different seedling ages (0, 14, 28... 196 DAT) using two fertigation methods: open-loop and closed-loop systems. Fifteen evaluations occurred throughout the cultivation cycle, spanning from planting to 196 days after transplanting (DAT), with the study replicated over two consecutive years. We evaluated dry matter partitioning among roots, stems, leaves, senescent leaves, flowers, commercial fruits, and non-commercial fruits. We also measured root volume and length, besides counts of leaves, flowers, and both commercial and non-commercial fruits. Despite no significant differences between fertigation systems for most variables, the closed-loop system shows promise, contingent on proper nutrient solution management. The partitioning analysis revealed that fruits, followed by leaves, were the primary consumers of photoassimilates.

ABSTRACT. The objective of this study was to identify the genetic, phenotypic and environmental parameters related to chemical compounds associated with beverage quality in a conilon coffee collection, grown in an irrigated system, in the Cerrado. The experiment was carried out at Embrapa Cerrados using green grains harvested in two years from 84 genotypes of the cultivar Robusta Tropical. Caffeine content, protein, ether extract, total soluble solids, pH and titratable acidity were evaluated. The data were subjected to analysis of variance. Significant differences were observed at 1% probability among accessions for all evaluated chemical characteristics in both harvest years. The high heritability, genetic coefficients of variation and selective accuracy reveal the potential for achieving genetic gains via the selection of genotypes adapted to the irrigated system in the Cerrado combined with high beverage quality.

ABSTRACT. Garlic cultivation holds significant importance in Brazil. However, research on garlic crops is currently limited and outdated, highlighting the necessity for new studies, particularly focused on enhancing weed management and optimizing the use of agricultural inputs. This study aimed to assess the extent of yield losses attributed to weed interference and the specific periods during which weed interference impacts garlic crop yields in the state of Santa Catarina, Brazil. The experiments were conducted in Curitibanos, Santa Catarina State, Brazil, during 2019 and 2020, using the garlic cultivars Chonan and Ito, respectively. A randomized block experimental design was employed, consisting of 16 treatment groups with four replications. The design incorporated a 2×8 factorial arrangement, involving two weed management strategies (coexistence and control) and eight crop-weed coexistence periods (0, 15, 30, 45, 60, 90, 120, and 130 days after crop emergence - DAE). The study evaluated the weed community and recorded data on the number of bulbs, bulb diameter, as well as total and commercial bulb yields of garlic crops. The results indicated average losses of 24.3% in total bulb yield and 28.9% in commercial bulb yield. Critical periods for effective weed control were identified as 6 to 126 DAE in 2019, 5 to 126 DAE in 2020 for total yield, 3 to 126 DAE in 2019, and 5 to 126 DAE in 2020 for commercial bulb yield. Consequently, it is imperative to maintain garlic crops weed-free throughout most of their growth cycle.

ABSTRACT. Excessive changes in factor levels can lead to a high cost in practice and hinder the conduction of experiments, in addition to adding a higher computational cost and loss of the orthogonality property, resulting in numerical problems in estimating the parameters of a model. The sequential specification of experimental points, seen as treatments in a 2k factorial design, results in a high-order bias in some factors, which is caused by the accumulation of −1 or +1 signals. This study aimed to propose new designs generated by the simulated annealing technique, respecting the main A-optimal and D-optimal optimality criteria as random execution orders that minimize the order bias. This approach allowed the generation of 24 and 25 factorials, which were compared to the designs in standard order. The simulated annealing technique is a viable method to generate optimal designs with the same efficiency as the usual designs to obtain A-optimal and D-optimal designs with new execution orders, which minimize the effect of order bias relative to standard order designs. Regarding efficiency, the generated designs were precise in the variance of model parameter estimates, similar to the original designs.

ABSTRACT. The grain production area in the Brazilian agricultural region known as SEALBA, especially in Alagoas State, has seen significant growth in recent years. This study aims to contribute to sustainable regional development by evaluating the effects of inoculation, co-inoculation, and the application of starter mineral nitrogen (N), either individually or in combination, on soybean growth and yield. Eight field experiments were conducted from 2018 to 2021 in two municipalities within Alagoas, covering soybean cultivation areas ranging from the first to the fourth year. The experiments followed a randomized complete block design with four replications, employing a factorial arrangement of treatments. The first factor encompassed five levels related to inoculation technologies and N management: 1) Inoculation with Bradyrhizobium; 2) Inoculation with Bradyrhizobium combined with N basal fertilization; 3) Co-inoculation of Bradyrhizobium + Azospirillum; 4) Co-inoculation of Bradyrhizobium + Azospirillum + N fertilization at the base; and 5) Control treatment without microbiological inputs or nitrogen fertilizers. The second factor involved the evaluation of different soybean cultivars, with two materials assessed in 2018 and three cultivars in 2019, 2020, and 2021. Results demonstrated that seed inoculation with Bradyrhizobium led to increased soybean grain yield in first-year cultivation areas. However, N basal fertilization, commonly known as starter fertilization, did not result in yield improvements compared to the use of microbiological inputs alone. Soybean cultivars BRS 9383 IPRO and FTR 3191 IPRO exhibited greater responsiveness to seed inoculation with Bradyrhizobium.

ABSTRACT. Plant growth models, derived from reliable databases, enable development of software for recommending cultural practices, harvest predictions, and enhancing productivity. This study aimed to create, refine, and simulate reference models for pineapple growth and development, adapting them based on nitrogen supply per plant and plant density per hectare. We utilized a field test database with periodic assessments of root, stem, leaf, fruit, and stem diameter fresh and dry weight, along with climate data from meteorological stations in or near the experimental areas. These growth models were developed, considering significant correlations and high correlation coefficients, using both simple non-destructive (stem diameter) and destructive (fresh or dry weight of D leaf) plant evaluations, either separately or in combination. The resulting models can provide estimated predictions for pineapple growth, adaptable to varying plant populations and nitrogen fertilization rates (measured in grams of N per plant).

ABSTRACT. This study aimed to evaluate the effect of silicon and acibenzolar-S-methyl sources on the development of yellow melon (Cucumis melo L.) in the field and the occurrence of diseases in different years. The treatments consisted ofthe silicon sources Agrosilício® (3 g L−1), Rocksil® (3 g L−1), and Chelal® Si (2 L 100 L−1), the additional treatments acibenzolar-S-methyl (ASM) (2 mM) and the fungicide thiabendazole (400 mL 100 L−1), and a control (sterile distilled water). The following characteristics were evaluated: natural incidence of diseases; gas exchange: CO2 assimilation rate, transpiration, stomatal conductance, internal CO2 concentration, water use efficiency, instantaneous water use efficiency, and carboxylation; postharvest aspects: fruit weight, pulp thickness, pulp firmness, titratable acidity, pH, soluble solids, and vitamin C content; productivity; and the enzymatic activity of peroxidases, polyphenol oxidases, and phenylalanine ammonia-lyase. No significant response was observed for naturally occurring diseases. Treatments with Chelal®Si, Rocksil®, and Thiabendazole® increased photosynthetic and transpiration rates in the yellow melon. The silicon and ASM sources did not influence the physicochemical characteristics or the enzymatic activity of fruits. No effect was observed on the biometric characteristics, productivity, and chemical quality of fruits in both years of cultivation. Si sources increased photosynthetic rate and transpiration. However, no diseases were observed during the experimental period. Leaf spraying with silicon and acibenzolar-S-methyl sources did not influence the biometric characteristics and fruit production of yellow melon. The silicon and acibenzolar-S-methyl sources did not induce an increase in the enzymatic activity of peroxidases, polyphenol oxidase, and phenylalanine ammonia-lyase. Fruit production was higher in 2020.