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Copyright of Revista de Ciencias Agroveterinarias is the property of Revista de Ciencias Agroveterinarias 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.)

Knowledge about herbicide-soil interactions is essential for the safe use of these products. The objective of this study was to evaluate the potential of multivariate discriminant analysis to predict the picloram sorption and desorption capacity of soils and to determine soil groups based on the risk of environmental contamination. Physicochemical properties of 17 soils were subjected to principal component analysis (PCA). Thereafter, the soils were grouped by cluster analysis (CA). Discriminant analysis (DA) was used to determine the efficiency of the clusters. The CA generated three groups of soils, and the coefficients of sorption (Kfs) and desorption (Kfd) were 2.85 and 4.29 for G1, 0.93 and 11.71 for G2, and for G3, 0.36 and 30.76 mg1−1/n L1/n kg−1, respectively. The similarity of soil physicochemical properties in each group resulted in similar picloram sorption and desorption coefficients. Clay, organic matter, pH, and sum of bases showed the greatest influence on the sorption and desorption of picloram. Grouping soils by PCA and CA based on soil physicochemical properties is an alternative approach to determine the risk of environmental contamination by picloram in agricultural areas. [ABSTRACT FROM AUTHOR]

In no-tillage systems, soil compaction has caused negative impacts on crop productivity and soil quality. The objective of this study was to evaluate the soil physical quality after different crops of the second season: maize, sorghum, and millet in compacted and uncompacted soils, in addition to evaluating the performance of soybean in succession in Rhodic Ferralsol under no-tillage (NT) in the Brazilian Cerrado biome. A field experiment was conducted during the second season of 2019 and the first season of 2019/20 in Rio Verde, Brazil. The experimental design used randomized blocks in a 3 × 2 factorial scheme, with six replications. The first factor corresponded to the cultivation of maize, sorghum, and millet; the second factor was the cultivation of these crops in compacted and uncompacted soils. The physical properties of the soils in the 0–0.1 and 0.1–0.2 m depth layers were evaluated after the second season of cultivation, in addition to the agronomic characteristics of the soybean cultivated in succession. The results indicate that the compaction influenced the soil physical quality, mainly in the 0.1–0.2 m layer, reflecting a decrease in the performance of the soybean crop (i.e., the plant height, number of pods per plant, and grain yield). The use of the second-season crop of millet improved the soil physical properties of penetration resistance and macroporosity and improved the water/air relation. The use of millet provided a reduction of up to 20% in the soil penetration resistance. About 10% more soybean was produced after cultivation in succession to millet compared to maize and sorghum. [ABSTRACT FROM AUTHOR]

The management of weeds in melon is hindered by the slow initial growth of the crop, favouring weed infestation and reducing production. During the years 2016 and 2017, weed interference periods were evaluated in two melon hybrids, yellow and frog skin, to determine the time of weed control in the crop. Four-parameter logistic regression was used to determine the critical weed control period (CPWC). The weed species with the highest occurrences in 2016 were Merremia aegyptia, Senna obtusifolia, and Urochloa plantaginea. In 2017, there was a predominance of M. aegyptia, indicating the possibility of successive cultivation, favouring the predominance of species with growth habits similar to melons. The increase in the period of living with weeds reduced the productivity and quality of melon fruits. Coexistence with weeds throughout the cycle reduced productivity by about 50%. The CPWC was 15 to 58 and 10 to 45 for frog skin and 12 to 52 and 4 to 50 days for yellow melon in 2016 and 2017, respectively, considering a productivity loss of 5%. These results underscore the importance of adopting strategies that allow melons to grow free from the presence of weeds, especially before they are fully established in the growing area. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Copyright of Revista Caatinga is the property of Revista Caatinga 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 Caatinga is the property of Revista Caatinga 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 Verde de Agroecologia e Desenvolvimento Sustentável is the property of Revista Verde de Agroecologia e Desenvolvimento Sustentavel 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 Caatinga is the property of Revista Caatinga 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 Caatinga is the property of Revista Caatinga 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 Acta Agronómica 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 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.)

The genetic improvement of soybean cultivars over the years has focused on increasing the yield potential and tolerance to some abiotic and biotic factors. However, during the transfer of genes of interest, some genes responsible for a lower tolerance to herbicides can be integrated into the genome of the new cultivar. Thus, the objective of this study was to evaluate the selectivity of herbicide associations applied in the postemergence period of three soybean cultivars. The experiment was conducted in a randomized completely block design, with four replications. The selected cultivars were M7110 IPRO®, Foco IPRO®, and Bônus IPRO®. The herbicides and the respective doses (g a.i. ha-1) used were glyphosate (1176), glyphosate + bentazon (1176 + 600), glyphosate + fomesafen (1176 + 175), glyphosate + lactofen (1176 + 120), glyphosate + imazethapyr (1176 + 100), glyphosate + chlorimuron (1176 + 10), glyphosate + cloransulam (1176 + 39.5), and a control without herbicide application. The visual note of intoxication was evaluated for each treatment. The components of growth and yield evaluated were height, stand, weight of one hundred grains, and yield. The application of postherbicide herbicides did not alter the plant stands of soybean cultivars. Additionally, these herbicides did not reduce the yield of the M7110 IPRO® and Foco IPRO® cultivars. Glyphosate isolated and in association with lactofen or imazethapyr reduced the grain yield of the Bônus IPRO® cultivar. [ABSTRACT FROM AUTHOR]

Weed control in the sesame crop (Sesamum indicum L.) is a fundamental practice that ensures high grain yield. Choosing adequate control methods is a crucial step to reduce costs and reach success in weed management. Among these methods, application of chemicals shows high efficiency and low cost for farmers. However, the use of this method in sesame crops is limited because there is a restricted number of herbicides registered for pre- and post-emergence applications. Considering the importance of chemical methods for weed management, the objective of this research was to select herbicides to be applied in pre-emergence that could be used to control weeds in the sesame crop. Two experiments were carried out, one to determine the efficiency and another to determine the selectivity of herbicides applied in pre-emergence. The experiments were performed in a randomized complete block design (CBD) with four replicates. The treatments consisted of seven herbicides, a mixture of herbicides applied in pre-emergence, and two control treatments, one weed-free and one with weeds. Diuron and flumioxazin were found to be selective for pre-emergence. Metribuzin exhibited high toxicity to sesame, but it was effective to control several weed species, and metolachlor did not provoke high phytotoxicity in sesame, but reduced yield. [ABSTRACT FROM AUTHOR]

Carotenoid quantification in food can be performed by various techniques, such as spectrophotometry, mass spectrometry, high performance liquid chromatography, gas chromatography, and colorimetry. The objective of this study was to verify the feasibility of indirect selection for assessment of total carotenoids in pumpkin accessions. The experimental design comprised of complete randomized blocks with two replications and three plants per plot. The treatments consisted of 51 Cucurbita moschata Duch accessions from the DCAF/UFERSA Cucurbitaceae germplasm collection and a commercial C. maxima Duch cultivar. After maturation, the fruits were harvested, and colorimetric and total carotenoid contents were evaluated. Considering the effect of accessions as random, variance components were estimated, and the genotypic values were predicted by maximum restricted likelihood (REML) or best linear unbiased prediction (BLUP). Both direct and indirect genetic gains were estimated from a selection intensity of 50%. Pulp color intensity parameters and h° angle indicated the possibility of indirect selection of accessions with higher total carotenoid contents. The ABO22 accession presented higher total carotenoid content under the evaluation conditions of the experiment. [ABSTRACT FROM AUTHOR]