ABSTRACT Favorable soil conditions are essential to the proper growth and production of any crop worldwide. Only 9 % of the Ecuadorian Amazon Region (EAR) territory is suitable for agriculture and/or livestock farming, due to limitations imposed by physio-edaphoclimatic factors. This study evaluated the soil potential suitability for coffee, cocoa and tropical pastures to determine optimal, moderate and marginal areas in three provinces in the EAR (Orellana, Sucumbios and Pastaza) under different agroecological conditions. On-site field work was carried out to analyze the soil profile to determine the mineral composition. Eight environmental variables were evaluated through the integration of GIS-based modeling to determine the agroecological zoning of the crops. The results showed that the main determining factors for optimal areas of soil suitability within the three provinces included soil depth (30 cm), organic matter content (5.3 %), concentration of macronutrients (2,700 mg kg–1), and slope (< 10 %), whereas annual temperature (18-26 °C), annual precipitation (1200-3000 mm), altitude (0-500 m), and pH (4.38) were included for moderate and marginal areas. Depending on the crop and the province, soil suitability was classified into two or three classes (optimal, moderate, and marginal areas), relying on the agroecological conditions specific to each crop. This study highlights that all crops showed mostly optimal soil suitability for proper development under the agroecological conditions analyzed, which contributes to the provision of valuable information to decision-makers about key limiting factors, land-use planning and mapping soil suitability when considering the best location for a specific crop. worldwide (EAR andor farming physioedaphoclimatic physio edaphoclimatic coffee Orellana, Orellana (Orellana Pastaza Onsite On site composition GISbased GIS based 30 (3 cm, cm , cm) 5.3 53 5 3 (5. %, %) 2,700 2700 2 700 (2,70 kg–1, kg1 kg kg–1 1 kg–1) < ( 1826 18 26 (18-2 °C, C °C °C) 12003000 1200 3000 (1200-300 mm, mm mm) 0500 0 500 (0-50 m, m m) 4.38 438 4 38 (4.38 province (optimal areas, areas) analyzed decisionmakers decision makers landuse land use 5. (5 2,70 270 70 (2,7 kg– 182 (18- 1200300 120 300 (1200-30 050 50 (0-5 4.3 43 (4.3 2,7 27 7 (2, (18 120030 12 (1200-3 05 (0- 4. (4. 2, (2 (1 12003 (1200- (0 (4 (1200 (120 (12

ABSTRACT The technology provided by greenhouses is essential for protecting crops sensitive to bioclimatic adversities and for improving agricultural production indexes. However, the need to know the exact interaction between the flexible coating and the structure under wind action has motivated new studies. The objective was to perform an in-depth review of the scientific and technological advances regarding methodologies to obtain parameters related to wind actions that are essential for the structural safety of greenhouses. This study showed the relevance of experimental methods; however, the limitations of the study are diverse, as field experiments require the construction and modifications of a prototype, which demand time and financial resources. Experiments in wind tunnels with models on a reduced scale have contributed significantly, as it allows to control the wind flow; however, in plastic-covered greenhouses, discrepancies occur due to the impossibility to represent the aeroelasticity of the construction. Modeling via computational fluid dynamics (CFD) has proven to be a solution for extrapolating limitations in experimental methods by facilitating changes in the construction model and wind flow. In addition to pure turbulence models, studies on hybrid turbulence models (Scale-Resolving Simulation) must be deepened to obtain greater accuracy of pressure coefficients. The complexity of the subject and the need for new contributions to plastic-covered greenhouse projects are a reality, which outlines a promising horizon for research development in the rural construction sector. indexes However indepth depth however diverse prototype resources significantly flow plasticcovered plastic covered CFD (CFD ScaleResolving Scale Resolving Simulation coefficients reality sector

ABSTRACT The knowledge of correlations between multiple characteristics in plant breeding leads to more effective selection strategies. The path analysis allows refining these correlations and partitioning them into direct and indirect effects on the main variable. The path analysis becomes more effective when based on predicted genotypic values rather than phenotypic values. The objective was to evaluate correlations between the main agronomic characteristics of grapevine cultivation and their direct and indirect effects on yield per plant to improve selection strategies to reach superior progenies. A randomized complete block design was installed using four cultivars and two rootstocks, five repetitions, and plots of four plants. Data from three crop seasons were analyzed from a mixed model and genetic correlations were subject to the path analysis. A high and positive significant correlation was found between average fruit production and the number of clusters per plant. On the other hand, the average production per plant showed a low correlation to cluster width and height per grapevine. Wider and higher berries tend to increase berry fresh mass and therefore increase the contents of soluble solids and reducing sugars. Among the features, the number of clusters per plant has the strongest direct effect on fruit production in grape cultivars. Berry fresh mass, berry length, and berry width were indirectly influenced by the number of clusters and showed high heritability compared to yield and number of clusters. These characteristics could be used in indirect selection. variable progenies rootstocks repetitions plants hand sugars features length

ABSTRACT This study aimed to evaluate the use of decision trees to select sows based on the production parameters of parity order (PO) 1 sows from a commercial herd. Data were collected at a piglet production unit with a capacity of housing 5,500 sows in collective pens. Piglet production and sow culling information was collected from PO1 and PO2 sows. The period from January 2017 to March 2020 was analyzed. The correlation analysis was used to identify the influence of the production parameters on sow culling after exploring the database using the graphical analysis and descriptive statistics. The ANOVA was applied to evaluate differences in the response variables between culled and unculled sows. Two models were proposed using the decision tree method: model 1 referred to sow culling, and model 2 comprised the total number of liveborn piglets (TBA). The calculated value was close to 0, although the correlations of the production parameters with culling were statistically significant. The mean number of weaned piglets was higher for unculled sows in PO1 (p < 0.05). The number of weaned piglets, total number of liveborn piglets, and weaning-service interval did not differ in the unculled and culled sows in PO2 (p > 0.05). Using a confusion matrix as a metric tool, the decision tree method used in this study provided consistent results for this database, indicating its possible use for decision-making in sow selection. PO (PO herd 5500 5 500 5,50 pens 201 202 analyzed statistics TBA. TBA . (TBA) 0 significant p 0.05. 005 0.05 05 0.05) weaningservice weaning service tool decisionmaking making selection 550 50 5,5 20 (TBA 00 0.0 55 5, 0.

ABSTRACT Rice (Oryza sativa) is among the most important crops worldwide; however, rice crops demand high water consumption. Future projections indicate reduced water availability and severe drought events, which may affect rice crops as the cereal is highly sensitive to drought stress. Thus, cultivars with lower water demand for irrigation or drought escape capacities are among the strategies to address this issue. This study aimed to assess five mutant rice genotypes in terms of growth cycle length, other agronomic interest traits, and drought response in the reproductive stage. The mutant genotypes evaluated showed a shortening of the growth cycle compared to the original cultivar, BRS Pampeira, representing a drought escape strategy. In addition, mutations did not negatively affect plant height and crop yield. However, similar to the original cultivar, mutants are not tolerant to water deficit in the reproductive stage. The genotypes evaluated have potential to be released as early cycle cultivars, which can reduce water demand during the harvest season while presenting a drought escape strategy. Oryza sativa worldwide however consumption events stress Thus issue length traits stage cultivar Pampeira strategy addition yield However

ABSTRACT The coffee sector is estimated to have a retail market value in excess of USD 83 billion, and over 125 million jobs have been created in the global coffee chain. The coffee specialty market has recently increased significantly, generating opportunities to certify coffee beans produced by sustainable practices. This avoids practices potentially harmful to the environment. Agroforestry, organic farming, intercropping, and soil conservation strategies are examples of sustainable alternatives in the production of coffee. In this review, we focus on practices for the sustainable management of coffee plantations that can help farmers fight problems caused by global warming. More specifically, we address soil organic matter and microbiota, the use of Urochloa grass as intercrop in coffee plantations, shading systems (including agroforestry), and organic coffee production. We concluded that from the agronomic viewpoint, we already have production techniques that can replace traditional ones with significant advantages accruing to the quality of coffee orchard ecosystems. Nevertheless, we need scientific research efforts to deal with the existing gaps and the engagement of the whole coffee chain as a means of guaranteeing an adequate profit to those smallholders who adopt and maintain sustainable practice and are capable of bringing several positive changes to the coffee crop, including the use of microbia-based commercial products and new organic sources of nutrients to complement chemical fertilizers and improve coffee quality. 8 billion 12 significantly environment Agroforestry farming intercropping review warming specifically microbiota agroforestry, agroforestry , agroforestry) viewpoint ecosystems Nevertheless crop microbiabased microbia based 1

ABSTRACT The ordinary least squares (OLS) can be affected by errors associated with heteroscedasticity and outliers, and extreme points can influence the regression parameters. Methods based on the median rather than on the mean and variance are more resistant to outliers and extreme points. These methods could be used to obtain regression parameter estimates that reflect more accurately the genuine relationship between the Y and X variables, leading to better identification of outliers and extreme points by comparing the slopes and intercepts of both methods. The Theil-Sen (TS) regression computes all possible pairwise slopes and determines the median of slopes as the regression slope. Here, we illustrated the potential use of TS and frequently used robust regression (RR) techniques to single linear regression using synthetic datasets and a practical problem in animal science. Three synthetic datasets were created assuming the normal distribution of Y and X values: one was free of outliers, while the other two had one or two clusters of outliers but the same X values. The TS, OLS, and RR had nearly identical regression parameter estimates for the dataset without synthetic outliers. However, the intercept and slope estimates by the OLS method differed considerably from the TS and RR methods when one or two clusters of outliers were included. The TS approach could be used to indirectly determine the presence of outliers or extreme points by comparing the 95 % confidence interval of the TS and OLS parameter estimates. (OLS parameters variables TheilSen Theil Sen (TS Here (RR science values However included 9

ABSTRACT Leaf litter decomposition and the release of nutrients from macauba palm leaves play a major role in nutrient return to the soil in a conservation environment. This study evaluated macauba palm leaf decomposition, macronutrient contents and biochemical composition under contrasting water conditions in the Brazilian Cerrado. Macauba leaves were collected from plants in two different environments (low and high water table conditions), placed in litter bags and evaluated according to their decomposition, macronutrients, lignin, cellulose and hemicellulose for 420 days. In addition, green and dry leaves were collected for macronutrient analyses. Litter decomposition ranged between 49 % and 59 % up to 180 days. The half-life of litter ranged from 141 to 198 days. The leaf litter decomposition of macauba was practically stable during the dry season, whereas at the beginning of the rainy season, decomposition resumed. Nitrogen, P and S were higher in the green leaves, whereas the Ca levels were higher in the dry leaves. In addition, the K levels were twofold higher in the green leaves than in the dry leaves. Lignin release from macauba residues was slower than cellulose and hemicellulose. The decomposition rates of hemicellulose were higher initially due to its high solubility, although it gradually decreased with the decomposition process. Lignin decomposition was also higher at the beginning of the process but stabilized during the drought period. The study indicates that the decomposition process and nutrient cycling of macauba are influenced by its biochemical composition. environment Cerrado low conditions, , conditions) macronutrients lignin 42 days addition analyses 4 5 18 halflife half life 14 19 season resumed Nitrogen solubility period 1

ABSTRACT Previous cultivation of sorghum (Sorghum bicolor), Congo grass (Urochloa ruziziensis), and palisade grass (Urochloa brizantha cv. ‘Marandu’) may influence soybean (Glycine max) agronomic performance. The present work evaluated the decomposition of sorghum, grass, and sorghum intercropped with grass in the off-season to improve soybean yield in integrated crop systems in the Brazilian Cerrado and their dry matter production. This study was conducted in Planaltina, DF, in Central-West Brazil, on a Typical Acrustox soil from Mar 2010 until Feb 2012. The experimental design was a randomized block, with six crop systems before soybean: fallowing, sorghum, palisade grass (alone or intercropped with sorghum), and Congo grass (alone or intercropped with sorghum) with four replicates. Soybean agronomic performance, the crop systems’ dry mass, and its decomposition rate were estimated over two years. Higher soybean grain yields were observed in cropping systems including Congo grass alone (3,349 kg ha–1) or intercropped with sorghum (3,317 kg ha–1). Sorghum intercropped with palisade grass produced 18,702 kg ha–1 of dry matter and 64.9 % (on average) of soil coverage during the soybean cycle. However, the highest lignin content was observed in sorghum intercropped with Congo grass (5.1 % on average). The results indicate that the cultivation of Congo grass, either alone or intercropped with sorghum, improves the agronomic performance of soybean in succession, compared to sorghum alone or palisade grass (alone or intercropped with sorghum). The intercropped systems provided the best nutrient efficiency use aiming at sustainable agriculture in the Cerrado region. bicolor, bicolor , bicolor) Urochloa ruziziensis, ruziziensis ruziziensis) cv ‘Marandu Marandu ‘Marandu’ Glycine max offseason off season production Planaltina DF CentralWest Central West Brazil 201 2012 block fallowing replicates mass years 3,349 3349 3 349 (3,34 ha1 ha 1 3,317 3317 317 (3,31 ha–1. . 18702 18 702 18,70 ha– 649 64 9 64. average cycle However 5.1 51 5 (5. average. succession sorghum. region 20 3,34 334 34 (3,3 3,31 331 31 1870 70 18,7 6 5. (5 2 3,3 33 (3, 187 7 18, ( 3, (3

ABSTRACT present study aimed to determine the effects of different light restriction levels (shading levels) on soybean genetic parameters using a Bayesian multi-trait model (MTM) and select high-yielding soybean cultivars. Eighteen commercial soybean cultivars bred in a soybean breeding program were evaluated over two agricultural seasons. Three shading levels were used over two agricultural crop seasons, giving six treatments (light restriction × crop season). The experiments were arranged in a randomized complete block design with six treatments replicated thrice. The genetic values and parameters were estimated using a Monte Carlo Markov Chain algorithm. Broad-sense heritability range from 0.2093 to 0.7153. The lowest genotypic variance estimate was observed at the 45 % photosynthetically active radiation level in the 2019/2020 crop season year compared with that of other shading levels. Furthermore, a 40 % selection intensity had the highest soybean yield under different shading levels. The Bayesian MTM combined with the factor analysis and genotype-ideotype distance method can be used to evaluate and select soybean genotypes considering different shading levels. The soybean cultivars 8579RSF, NS8338, NS7901, NS7667, RK8115, and 8473RSF had higher genetic potential than other cultivars under different shading levels. multitrait multi trait (MTM highyielding high yielding seasons season. . season) thrice algorithm Broadsense Broad sense 02093 0 2093 0.209 07153 7153 0.7153 4 20192020 2019 2020 2019/202 Furthermore genotypeideotype genotype ideotype 8579RSF RSF NS8338 NS NS7901 NS7667 RK8115 RK 0209 209 0.20 0715 715 0.715 2019202 201 202 2019/20 NS833 NS790 NS766 RK811 020 20 0.2 071 71 0.71 201920 2019/2 NS83 NS79 NS76 RK81 02 2 0. 07 7 0.7 20192 2019/ NS8 NS7 RK8

ABSTRACT The development and the use of new technologies in agriculture contribute to significant advances in research with practical applications in several fields, such as image analytical techniques, which are simple, fast, and objective analyses. This work aimed to evaluate rice seeds’ quality using X-ray, multispectral, and chlorophyll fluorescence image analytical techniques and relate this information with the photosynthetic efficiency of seedlings. Initially, the seeds were identified and enumerated, then X-ray images were obtained, and the void space (area between the endosperm + embryo and the glumes) was calculated. Next, the same seeds were used in the X-rays, multispectral, and chlorophyll fluorescence images. Afterward, the seeds were placed to germinate in polyethylene cups with a capacity of 250 mL, and evaluations of the photochemical yield of photosynthesis photosystem II (FSII) and of the seedling fluorescence chlorophyll were carried out seven, nine, and 11 days after the emergence of the seedlings. The reflectance of seeds in the spectral bands between 365 nm and 780 nm showed a positive correlation with the chlorophyll fluorescence. Furthermore, the higher photosynthetic efficiency of rice seedlings at 11 days after emergence is directly related to the reflectance of the seeds at spectral bands between 365 nm and 780 nm. fields simple fast analyses Xray, Xray X ray, ray multispectral Initially enumerated obtained area glumes calculated Next Xrays, Xrays rays, rays X-rays Afterward 25 mL FSII (FSII seven nine 1 36 78 Furthermore 2 3 7

ABSTRACT Sampling is an essential step in estimating a parameter: thus, cost and time associated to this step should be minimized. Sequential sampling is characterized by using samples of variable sizes given as a function of observations, and sequential sampling provides a smaller sample size than a fixed-size sample in most cases. In addition, the Bayesian decision theory can be incorporated into sequential sampling to perform parameter estimation because it allows the inclusion of a priori information about the parameter of interest, which optimizes the procedure. However, the great challenge to performing the Bayesian sequential estimation in establishing the stopping criteria. Most studies in this area investigate binomial distributions, while few analyze multinomial distributions. This study aimed to define the stopping criteria for the Bayesian sequential estimation of the parameters of multinomial distributions with conjugate Dirichlet priors. The proposed methodology was applied to a set of X-ray test data for quality control of maize seed lots. This test uses conventional sampling techniques in which a sample has a fixed size with 200 seeds. The influence of two priors on the stopping criteria was evaluated, one uniform and one conjugate, with hyperparameters based on reference information from the literature. The results indicated a reduction in the sample size in most lots evaluated. thus minimized observations fixedsize cases addition interest procedure However Xray X ray 20 seeds evaluated literature 2

ABSTRACT This study was conducted to assess prediction models for production indexes in batches of growing pigs using performance regressors (period of the year and farm size). A database containing 663 records on the performance of pig batches (18.83 ± 4.37 to 111.26 ± 10.59 kg body weight (BW) at housing and finisher, respectively) from a private company was used to assess the following average animal characteristics: initial number of animals (INA), initial BW (IBW), initial age (IA), final BW (FBW), final age (FA), daily feed intake (DFI) and feed conversion ratio (FCR). Data were categorized by period (P) of the year (P1 = Nov to Apr and P2 = May to Oct), and farm size (FS): 0 ≤ INA ≤ 1,000, FS1; 1,001 ≤ INA ≤ 2,000, FS2; 2,001 ≤ INA ≤ 3,000, FS3; and INA > 3,000, FS4. The analysis resulted in representing 58 % of the variance of FCR data. The INA impaired FCR, and having larger pig batches improves FCR and profitability. The FBW prediction errors ranged from 2.47 to 3.38 %. Feed conversion ratio prediction errors ranged from 3.27 to 4.47 %. Based on the joint criteria of non-bias and accuracy, the models for predicting the FBW of growing pig batches have practical value in animal science on account of their accuracy. In addition, increasing the initial number of housed pigs in batches affects the FCR regardless of the period of the year. size. . size) 66 18.83 1883 18 83 (18.8 437 4 37 4.3 11126 111 26 111.2 1059 10 59 10.5 (BW finisher respectively characteristics INA, , (INA) IBW, IBW (IBW) IA, IA (IA) FBW, (FBW) FA, FA (FA) DFI (DFI FCR. (FCR) P (P P1 Oct, Oct Oct) FS (FS) 1000 1 000 1,000 FS1 1001 001 1,00 2000 2 2,000 FS2 2001 2,00 3000 3 3,000 FS3 FS4 5 data profitability 247 47 2.4 338 38 3.3 327 27 3.2 447 4.4 nonbias non bias accuracy addition 6 18.8 188 8 (18. 43 4. 1112 11 111. 105 10. (INA (IBW (IA (FBW (FA (FCR (FS 100 00 1,0 200 2,0 300 3,00 24 2. 33 3. 32 44 18. (18 1, 20 2, 30 3,0 (1 3, (

ABSTRACT Viticulture is one of the most produced fruit crops in the world; therefore, challenges of cropping systems are very relevant. Altered environments pose an obstacle; in addition, climate change influences plant-pathogen relationships and their risks. This work described the interaction of Neophysopella tropicalis (Ono) × ‘Cabernet Sauvignon’ grapevine at 25 and 30 °C, from an epidemiological and anatomical perspective. Rust severity showed no differences in plants kept at 25 and 30 °C; however, a significantly higher number of rust pustules was observed at 30 °C. The accumulation of phenolic compounds in healthy leaves at 25 °C was denser and more homogeneous than in the other treatments. The phenol pattern alteration observed in healthy leaves at 30 °C is possibly related to the larger number of lesions observed at this temperature. world therefore relevant obstacle addition plantpathogen plant pathogen risks Ono (Ono Cabernet Sauvignon 2 3 C perspective however treatments temperature

ABSTRACT Elephant grass is an allogamous perennial forage crop with asexual propagation, allowing plant breeders to explore heterosis and develop hybrids. However, selecting parents for diallel crossing schemes is a major hurdle in the development of hybrids. In addition, this perennial crop has several harvests, which increases the dataset size and the complexity of the statistical analyses. Here, we propose a diallel analysis based on linear mixed models with repeatability information to identify parents and hybrids, and the optimum number of harvests. We performed a complete diallel crossing of 11 parents with data from five harvests for morphological traits and two harvests for nutritive value traits. The diallel model with repeatability information aids in the estimation of the genetic effect of diallel analysis to infer the ideal number of harvests and genotype × harvest interaction. We observed that the specific combining ability (SCA) is more critical for morphoagronomic traits, while the general combining ability (GCA) has greater importance for traits related to nutritive value. Furthermore, we detected that five harvests were sufficient for the morphoagronomic traits with a coefficient of determination (R2) of 0.8; however, ten harvests were required for an R2 of 0.9. The model is a promising single-analysis alternative for plant breeders to analyze a diallel with repeated measures and to estimate important parameters without incurring in additional financial costs. propagation hybrids However addition analyses Here 1 interaction SCA (SCA GCA (GCA Furthermore R (R2 0.8 08 0 8 however 09 9 0.9 singleanalysis single costs (R 0.