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Chemical desiccation in the preharvest of grains and seeds is commonly used in production fields. Using herbicides for this purpose is a viable alternative to reduce beans' exposure to adverse crop conditions. Our objectives were to evaluate (1) the efficacy of herbicides for accelerated defoliation of cowpea, (2) the impact of herbicide application on antioxidant enzyme activity and protein and amino acid contents in seeds, and (3) the effects of different herbicide application schedules on the physiological aspects of seeds. In the first experiment, in addition to the control treatment (without herbicides), seven herbicides and two mixtures were applied at night: diquat, flumioxazin, diquat + flumioxazin, glufosinate ammonium, saflufenacil, carfentrazone, diquat + carfentrazone, atrazine, and glyphosate. Diquat and its mixtures showed greater efficacy in anticipating the harvest. Flumioxazin and diquat alone reduced amino acid content by 61.72 and 51.44%, respectively. The same trend was observed for total soluble proteins. The activity of antioxidant enzymes (CAT, POD, PPO) increased, indicating oxidative stress caused by diquat and flumioxazin. In the second experiment, we tested three application times (6 a.m., 12 p.m., 6 p.m.) with diquat, diquat + flumioxazin, and diquat + carfentrazone. The lowest damage to chlorophyll a was at 6 a.m.; other times reduced photosynthetic pigments and increased carotenoid content. Total soluble sugars decreased by 27.74% with nocturnal application of diquat + flumioxazin. Our data indicate that herbicide use for desiccation affects seed quality. These findings highlight the need for selecting appropriate herbicides and application times. Future research should explore long-term impacts on crop yield and quality.

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The present work aimed to study oxidative damage and protection, phenylpropanoid metabolism, and the quality of minimally processed colored sweet potatoes cultivated with increments in P2O5 fertilization. Sweet potato was cultivated with 0, 60, 120, 180, and 240 kg ha-1 of P2O5. The roots were harvested, and the P content in the roots and leaves was quantified. The roots were minimally processed and kept for 20 days at 5 °C. In general, the roots that were fertilized with P2O5 showed a higher content of the analyzed variables. The highest P dosage in the soil increased the P content in roots and leaves and the agro-industrial yield. Roots cultivated with P2O5 showed a higher content of hydrogen peroxide, phenolic compounds, vitamin C, yellow flavonoids, anthocyanins, and carotenoids, antioxidant capacity by the DPPH method, and higher activity of the enzymes polyphenol oxidase, peroxidase, and phenylalanine ammonia lyase. These results demonstrated the role of phosphorus in protecting against oxidative damage due to the accumulation of bioactive compounds, thus improving the physicochemical quality of minimally processed orange sweet potato.

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The estimative of the leaf area using a nondestructive method is paramount for successive evaluations in the same plant with precision and speed, not requiring high-cost equipment. Thus, the objective of this work was to construct models to estimate leaf area using artificial neural network models (ANN) and regression and to compare which model is the most effective model for predicting leaf area in sesame culture. A total of 11,000 leaves of four sesame cultivars were collected. Then, the length (L) and leaf width (W), and the actual leaf area (LA) were quantified. For the ANN model, the parameters of the length and width of the leaf were used as input variables of the network, with hidden layers and leaf area as the desired output parameter. For the linear regression models, leaf dimensions were considered independent variables, and the actual leaf area was the dependent variable. The criteria for choosing the best models were: the lowest root of the mean squared error (RMSE), mean absolute error (MAE), and absolute mean percentage error (MAPE), and higher coefficients of determination (R2). Among the linear regression models, the equation yˆ=0.515+0.584*LW was considered the most indicated to estimate the leaf area of the sesame. In modeling with ANNs, the best results were found for model 2-3-1, with two input variables (L and W), three hidden variables, and an output variable (LA). The ANN model was more accurate than the regression models, recording the lowest errors and higher R2 in the training phase (RMSE: 0.0040; MAE: 0.0027; MAPE: 0.0587; and R2: 0.9834) and in the test phase (RMSE: 0.0106; MAE: 0.0029; MAPE: 0.0611; and R2: 0.9828). Thus, the ANN method is the most indicated and accurate for predicting the leaf area of the sesame.

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Phosphate fertilization of cassava cultivars leads to increased production costs that may be economically viable depending on the quantity used and the corresponding productivity. In this sense, the objective of the work was to analyse the economic viability of the irrigated cultivation of table cassava cultivars in response to the application of phosphorus doses in the Brazilian semiarid region. Two agricultural crops were conductedat the Experimental Farm Rafael Fernandes, Mossoró, RN, from June 2018 to April 2019 and from June 2019 to April 2020. The experimental design was in randomized blocks arranged in subdivided plots, with four replications. The doses of phosphorus (0, 60, 120, 180, and 240 kg ha-1of P2O5) were applied to the plots and the table cassava cultivars (Água Morna, BRS Gema de Ovo, Recife and Venâncio) arranged in the subplots. The total costs for one hectare of cultivation were estimated and the gross income, netincome, rate of return, and profitability index were calculated. The use of phosphatefertilizer was economically viable for the cassava cultivars studied in the two crops. The cultivars Água Morna, BRS Gema de Ovo, and Recife are the best cultivation options for the semiarid region of Rio Grande do Norteas they give high yields with the highest profitability. The Recife cultivar was the region's most profitable cultivation, with a profit ranging from R$ 40,331.07 ha-1to R$ 57,603.46 ha-1in both seasons,with an average recommendation of 120 kg ha-1of P2O5.(AU)

A adubação fosfatada de cultivares de mandioca leva ao aumento dos custos de produção que podem ser economicamente viáveis dependendo da quantidade utilizada e da respectiva produtividade. Nesse sentido, o objetivo dotrabalho foi analisar a viabilidade econômica do cultivo irrigado de cultivares de mandioca de mesa em resposta à aplicação de doses de fósforono semiárido brasileiro. Foram conduzidos duas safras agrícolas na Fazenda Experimental Rafael Fernandes, Mossoró, RN, nos meses de junho de 2018 a abril de 2019 e junho de 2019 a abril de 2020. O delineamento experimental foi em blocos casualizados dispostos em parcelas subdivididas, com quatro repetições. As doses de fósforo (0, 60, 120,180 e 240 kg ha-1de P2O5) foram aplicadas nas parcelas e as cultivares de mandioca de mesa (Água Morna, BRS Gema de Ovo, Recife e Venâncio) dispostas nas subparcelas. Estimaram-se os custos totais de um hectare de cultivo e calcularam-se a receita bruta,a receita líquida, a taxade retorno e o índice de lucratividade. O uso da adubação fosfatada mostrou-se economicamente viável para as cultivares de mandioca estudadas nas duas safras. As cultivares Água Morna, BRS Gema de Ovo e Recife são as melhores opções de cultivo para o semiárido do Rio Grande do Norte, pois apresentam altas produtividades com maior rentabilidade. A cultivar Recife foi o cultivo mais rentável da região, com rendimento variando de R$ 40.331,07 ha-1a R$ 57.603,46 ha-1nas duas safras,com recomendação média de120 kg ha-1de P2O5.(AU)

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Potassium (K) participates in critical processes in sunflower cultivation, such as osmotic regulation and translocation of photosynthesis. However, the absorption or accumulation of this nutrient occurs differently owing to edaphoclimatic factors or between cultivars. The objective of this study was to evaluate the nutritional efficiency of sunflower cultivars as a function of different dosage K dosages in a semiarid region. To this end, two experiments were conducted in 2016 and 2017. The treatments consisted of five dosages of K at 0, 30, 60, 90, and 120 kg ha-1 K2O and four sunflower cultivars, Aguará 6, Altis 99, Multissol, and BRS 122. The experimental design was a randomized block with four replications and subdivided plots. The characteristics evaluated were agronomic efficiency, physiological efficiency, recovery efficiency, utilization efficiency, and accumulation of total K in the plant. Sunflower cultivars responded to K dosages in the two crops, with variations in efficiency parameters. Crop 2 showed better nutritional efficiency compared to crop 1. Aguará 6 showed greater nutritional efficiency than the other two crops. The use of dosages between 75 and 91 kg ha-1 of K2O provided better efficiency in K usage for the cultivars.

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The large variation in the response of sunflower to nitrogen fertilization indicates the need for studies to better adjust the optimum levels of this nutrient for production conditions. Our objectives were to analyze the agronomic yield of sunflower cultivars as a function of nitrogen fertilization; indicate the cultivar with high nitrogen use efficiency; and measure the adequate N dose for sunflower through nutritional efficiency. The completely randomized block design with split plots was used to conduct the experiments. The treatments included five nitrogen rates being allocated in the plots and the four sunflower cultivars. To estimate the nutrient use efficiency in the sunflower, we measured agronomic efficiency (AE), physiological efficiency (PE), agrophysiological efficiency (APE), apparent recovery efficiency (ARE), and utilization efficiency (UE). The results indicate that all cultivars had a reduction in AE due to the increase in N doses in the first crop. For PE, the highest values were observed for Altis 99 during the 2016 harvest. In that same harvest, Altis 99 had the highest APE. The dose of 30 kg ha-1 provided greater ARE for all cultivars in both crops, with greater emphasis on BRS 122 and Altis 99. The cultivation of cultivars Altis 99 and Multissol at a dose of 30 kg ha-1 in is recommended semiarid regions.

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The objective of this work was to evaluate the diversity between accessions of Cucurbita moschata from the Northeast of Brazil and preserved at the Universidade Federal Rural do Semi-Árido (UFERSA) in Mossoró-RN. The experiment was carried out in complete randomized blocks, with two replications and three plants per plot. The treatments consisted of 51 accessions of C. moschata Duch and a commercial cultivar of Cucurbita maximum Duch. After ripening, the fruits were harvested (one fruit per plant) and evaluated for morpho-agronomic descriptors. Univariate and multivariate variance analyzes were performed. From the dissimilarity matrices, accessions were hierarchically grouped by the UPGMA method. The relative contribution of quantitative characters to the divergence was also estimated. There was an effect of accessions (p <0.01 or p <0.05) for all characters in univariate analyzes, indicating that there is heterogeneity between the accessions evaluated. Considering the quantitative descriptors, the accessions formed eight groups and for the qualitative six groups. When considering the two sets of descriptors, the accessions were distributed in eight groups but presenting a greater distribution of accessions. The descriptors that most contributed to the discrimination of accessions were the firmness of the pulp and the length of the fruit.

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This study proposes to relate the increase in phosphorus (P) supply in the soil, via phosphate fertilization, to oxidative damage and protection, phenylpropanoid metabolism, and enzymatic browning in minimally processed cassava. The roots were grown with 0, 60, and 120 kg ha-1 P2O5. The roots were harvested, and the yield and P content in the root, stem, and leaves were quantified. The roots were minimally processed and stored for 12 days at 5 °C. The higher supply of P in the soil increased the P content of roots and stems but not the agro-industrial yields. Roots grown at 120 kg ha-1 P2O5 showed higher detection of hydrogen peroxide, which was accompanied by increased phenolic compounds, soluble quinones, and antioxidant capacity and increased activities of the enzymes superoxide dismutase, catalase, ascorbate peroxidase, polyphenol oxidase, and peroxidase. The present study thus demonstrates the role of phosphorus application, induction of the synthesis of phenolic compounds, and quality of fresh-cut cassava.

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BACKGROUND: Weed control can be economically viable if implemented at the necessary time to minimize interference. Empirical mathematical models have been used to determine when to start the weed control in many crops. Furthermore, empirical models have a low generalization capacity to understand different scenarios. However, computational development facilitated the implementation of supervised machine learning models, as artificial neural networks (ANNs), capable of understanding complex relationships. The objectives of our work were to evaluate the ability of ANNs to estimate yield losses in onion (model crop) due to weed interference and compare with multiple linear regression (MLR) and empirical models. RESULTS: MLR constructed from non-destructive and destructive methods show R2 and root mean square error (RMSE) values varying between 0.75% and 0.82%, 13.0% and 19.0%, respectively, during testing step. The ANNs has higher R2 (higher than 0.95) and lower RMSE (less than 6.95%) compared to MLR and empirical models for training and testing steps. ANNs considering only the coexistence period and system have similar performance to MLR models. However, the insertion of variables related to weed density (non-destructive ANN) or fresh matter (destructive ANN) increases the predictive capacity of the networks to values close to 99% correct. CONCLUSION: The best performing ANNs can indicate the beginning of weed control since they can accurately estimate losses due to competition. These results encourage future studies implementing ANNs based on computer vision to extract information about the weed community.

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Nitrogen (N) is an essential macronutrient for plant growth and rate applications can influence the performance of sesame, and when applied in excess can cause nitrogen loss in the environment, and consequently make the cost of production more costly to the producer. Therefore, the objective of this work was to evaluate the efficiency of nitrogen use by different cultivars of irrigated sesame seeds under the edaphoclimatic conditions of the northeastern semi-arid region in two harvests. The experiments were carried out from February to May (1st harvest) and from July to October (2nd harvest) in 2016. The treatments were arranged in a split plot scheme, in which the plots were the five nitrogen doses (0, 30, 60, 90 and 120 kg ha-1), and in the subplots, the four sesame genotypes (CNPA G2, CNPA G3, CNPA G4 and BRS Seda), the design was in randomized complete blocks with four replications. The nitrogen use efficiency assessments evaluated were: agronomic efficiency (AE), physiological efficiency (PE), agrophysiological efficiency (APE), recovery efficiency (RE) and efficiency of use (EU). The rate that provided the greatest efficiency of use was 30 kg ha-1 of N applied. The cultivar BRS Seda had greater efficiency of use in relation to the other cultivars studied. The crop that had better efficiency of use was the 2nd agricultural harvest.

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