ABSTRACT. The strawberry (Fragaria x ananassa Dutch.), is the only vegetable belonging to the rosacea family. All strawberry species have now emerged from wild species and belong to the genus Fragaria, being that this genus presents more than 45 described species, and only 11 are considered natural species. Due to the octoploid nature of strawberry and its variability after hybridization, selecting one or more characters may result in unfavorable genotypes and even the exclusion of promising ones, because negative genetic correlations have been observed among them that cause inefficient selection. Therefore, the objective of this study was to verify the efficiency of selection indices in selecting experimental strawberry hybrids for in natura consumption and processing. Seven commercial cultivars and 103 hybrids were used, which were obtained from populations derived from their crossings. The experiment was conducted in augmented blocks, in which four agronomical traits (total mass, amount of commercial fruit, amount of noncommercial fruit, and average fruit mass) and seven physicalchemical traits (soluble solids, soluble solids:titratable acidity ratio, total sugars, total pectin, vigor, and internal and external coloration) were evaluated. For hybrid selection, the following indices were used: Mulamba and Mock (1978), Smith (1936), Hazel (1943, and genotype-ideotype, which selected 20% of the genotypes evaluated. The three indices selected about 9% of the hybrids. The selection of two experimental hybrids (89 and 495) and the use of selection indices resulted in larger estimates of selection gains. The Mulamba and Mock (1978), Smith (1936), andHazel (1943) indices had the highest percentage of gains on selection, and are therefore recommended for the selection of strawberry clones.
Over the years, cultivated areas of sorghum have expanded considerably in Brazil. Chemical weed control has become an obstacle due to the scarcity of herbicides registered for the crop. The aim of this study was to evaluate the efficiency of weed control and selectivity of herbicides applied in pre and post emergence in the crop. Two experiments were conducted. In one of them, the hybrid BRS 310 was used while DKB 550 was used in the other. The experiments were performed in the field in randomized block design, evaluating seven treatments with four replications. The used treatments were: 1. Hand weeding, 2. S-metolachlor (1,440 g a.i. ha-1), 3. S-metolachlor (1,440 g a.i. ha-1) + atrazine (2,000 g a.i. ha-1), 4. atrazine (2,000 g a.i. ha-1), 5. atrazine (3,000 g a.i. ha-1), 6. atrazine (2,000 g a.i. ha-1) + mineral oil (0.25%), and 7. atrazine (2,000 g a.i. ha-1) + mineral oil (0.5%). It was verified that post-emergence atrazine was efficient in the weed control and selective to the sorghum crop, not affecting productivity, except in mixture with mineral oil (0.5%). S-metolachlor cannot be recommended in pre-emergence for the tested cultivars because it is not selective, reducing plants and productivity.
The herbicide lactofen has been used by producers in many conditions, in order to increase the soybean yield. This study aimed to evaluate the influence of lactofen and the phytohormone kinetin on the morpho-agronomic traits, carbohydrate partitioning and yield, in soybean cultivars. Three experiments were carried out in the field, in addition to one experiment in a greenhouse. A randomized block design, with four replications, was used. The treatments were: lactofen [144 g ha-1 of active ingredient (a.i.)], lactofen + kinetin (144 g ha-1 of a.i. + 0.5 g ha-1), kinetin (0.5 g ha-1), manual cutting of apical buds and control. In the subplots, six soybean cultivars (M 6410 IPRO, M 5917 IPRO, NS 7670 RR, NS 6909 IPRO, BMX Lança IPRO and Produza IPRO) were used. In the field, the plant lodging index, plant height, number of nodes and branches, pods and grains per plant, mass of 100 grains and grain yield were evaluated. In the greenhouse, the starch, reducing sugars, sucrose and total sugars in the leaves, stems and roots of three soybean cultivars were quantified. The application of lactofen in the V6 stage influenced the morpho-agronomic traits of the cultivars in the field and increased the soybean yield by 312 kg ha-1, considering all the cultivars. The phytohormone did not influence the morpho-agronomic traits neither the grain yield. The treatments did not induce modification in the partitioning of carbohydrates destined to the roots.
This study measured the effect of the association between agronomic traits related to the yield of canola grains grown at different sowing dates through path analysis. Another objective was to obtain a method to predict the oil content in the grains, fitting a multivariate model through near-infrared (NIR) spectroscopy analysis. The experiment was conducted in the field using a randomized block design in plots subdivided by time, with four plots (sowing dates), six subplots (canola hybrids), and four replicates. In each hybrid, phenological observations were performed, and the grain yield was determined. The data were subjected to analysis of variance in the R environment using the F test at 5% probability. The oil content in the grains was determined by the traditional chemical method, and based on the NIR spectral signature of the grain samples, partial least squares regression (PLS-R) was established to estimate the oil content in the canola grains. The sowing dates influenced the production components and oil content of the grains of all hybrids. The trait number of grains in five plants (0.6857) and their height (0.4943) had greater estimates of positive correlations with grain yield, as well as higher values of positive direct effects on yield (0.2494 and 0.1595, respectively). The NIR technique combined with PLS-R was able to predict the oil content in the grains, resulting in good predictive models (R2 of 0.86 and root mean square error (RMSE) of 1.56 in external validation).
A aplicação de herbicidas em pós-plantio das mudas pré-brotadas de cana-de-açúcar se destaca no controle de plantas daninhas na cultura, com eficácia na erradicação dessas em curto período. Contudo, efeitos de fitotoxicidade aos herbicidas podem ocorrer, a depender da variedade de cana-de-açúcar, época de aplicação e doses dos produtos. Assim, há a necessidade de pesquisas visando identificar novos ingredientes ativos eficientes no controle de plantas daninhas e que apresentem seletividade para a cultura da cana-de-açúcar. Objetivou-se, com o presente trabalho, avaliar a seletividade do herbicida tembotrione sobre genótipos de cana-de-açúcar em doses e épocas de aplicação no sistema de mudas pré-brotadas. O experimento foi dividido em duas etapas: Na primeira etapa, avaliou-se o efeito de doses do herbicida tembotrione + óleo mineral (0; 50,4; 75,6; 100,8; e 126 g i.a. ha-1 + 108 g i.a. ha-1, respectivamente), sobre épocas de aplicação; 0, 20 e 40 dias após o transplantio. Na segunda etapa, avaliou-se a aplicação de 75,6 g i.a. ha-1 do herbicida tembotrione + 108 g i.a. ha-1 de óleo mineral, sobre quatro genótipos de cana-de-açúcar: RB966928, RB855156, RB93509 e IACSP95-5000. Durante a condução das duas etapas, foram realizadas avaliações de fitotoxicidade aos 7, 14, 21 e 28 dias após aplicação e ao final determinou-se o número de perfilhos, massa fresca e massa seca da parte aérea. Verificou-se que o herbicida tembotrione, quando aplicado em doses menores e em períodos iniciais da cultura em pós-emergência, apresenta seletividade para as variedades RB867515, RB966928, RB855156, e RB93509, contudo, proporciona decréscimo no acúmulo de massa seca da parte aérea sobre a variedade IACSP95-5000.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.