Integrated Nutrient and Weed Management Practices on Quality Parameters in Aromatic Rice

Selection of appropriate weed management strategy helps reduce rice yield loss due to weeds. Despite some undesirable side-effects, no viable alternative is currently available to shift the chemical weed management in rice. However, time of herbicide application is very important with respect to its efficacy. Keeping in mind the inevitability of herbicidal weed control, the current study was designed to evaluate the response of selected aromatic fine rice varieties of Bangladesh to different herbicides based weed management practices compare to farmers’ practices. The experiment was conducted in a randomized complete block design with three replications. The experiment consisted of five aromatic rice varieties; Kalijira, BRRI dhan34, BRRI dhan37, BRRI dhan38 and Binadhan-13, and six different weed management practices comprising no weeding, weed free, mechanical + manual weeding, pre–emergence herbicide + manual weeding, post–emergence herbicide + manual weeding and pre– + post–emergence herbicide. Eleven weed species belonging to five families were observed in the experimental plots. Based on the summed dominance ratio (SDR), grassy weed species Echinochloa crusgalli (SDR of 30.7) was the most dominant species, whereas broadleaf weed Nymphaea nouchali (SDR of 0.83) was the least one. Among the weed control treatments, application of pre–+ post emergence herbicides offered the highest reduction in weed density and biomass at all sampling dates which resulted in minimum crop-weed competition facilitating improvement in the yield contributing characters and finally resulted in the highest grain yield (2.5 t ha−1) and harvest index (30.7%) next to the weed free treatment. The variety BRRI dhan38 gave the highest grain yield (3.4 t ha−1) due to the highest performance of the yield contributing characters among the varieties. In interaction, BRRI dhan38 with pre–+ post–emergence herbicide application gave the highest yield (3.4 t ha−1) apart from the weed free treatment. Being efficient in weed density and biomass reduction as well as the highest yield producer, sequential application of pre–and post–emergence herbicides may be recommended for effective weed management practices in BRRI dhan38J. Bangladesh Agril. Univ. 16(1): 31-40, April 2018

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Growth and Yield Attributes, Quality Parameters and Seed Cotton Yield of Hybrid Cotton (Gossypium spp) as Influenced by Weed Management Practices in Southern Dry Zone of Karnataka

International Journal of Pure & Applied Bioscience ◽

10.18782/2320-7051.6959 ◽

2018 ◽

Vol 6 (5) ◽

pp. 556-563

Author(s):

Honnappa, H. M. ◽

Keyword(s):

Weed Management ◽

Management Practices ◽

Quality Parameters ◽

Growth And Yield ◽

Cotton Yield ◽

Seed Cotton ◽

Yield Attributes ◽

Seed Cotton Yield ◽

Gossypium Spp ◽

Dry Zone

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Effect of Nutrient and Weed Management Practices on Yields and Economics of Aromatic Rice in Semi Arid Region of Bihar, India

International Journal of Current Microbiology and Applied Sciences ◽

10.20546/ijcmas.2020.903.011 ◽

2020 ◽

Vol 9 (3) ◽

pp. 89-95

Author(s):

Shashimala Kumari ◽

Vinay Kumar ◽

Shashidhar Yadav ◽

Vijay Kumar ◽

Santosh Kumar Singh ◽

...

Keyword(s):

Weed Management ◽

Arid Region ◽

Management Practices ◽

Aromatic Rice ◽

Semi Arid Region ◽

Semi Arid

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Weed Management in Small Grains Harvested for Grain

EDIS ◽

10.32473/edis-wg009-2020 ◽

2020 ◽

Vol 2020 (3) ◽

Author(s):

Jason Ferrell ◽

Gregory MacDonald ◽

Pratap Devkota

Keyword(s):

Weed Control ◽

Weed Management ◽

Chemical Control ◽

Management Practices ◽

Good Management ◽

Small Grains ◽

Crop Competition

Successful weed control in small grains involves using good management practices in all phases of production. In Florida, winter weeds compete with small grains for moisture, nutrients, and light, with the greatest amount of competition occurring during the first six to eight weeks after planting. Weeds also cause harvest problems the following spring when the small grain is mature. This 4-page publication discusses crop competition, knowing your weeds, and chemical control. Written by J. A. Ferrell, G. E. MacDonald, and P. Devkota, and published by the UF/IFAS Agronomy Department, revised May 2020.

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Weed Management in Peanuts

EDIS ◽

10.32473/edis-wg008-2020 ◽

2020 ◽

Vol 2020 (3) ◽

Author(s):

Pratap Devkota

Keyword(s):

Weed Control ◽

Weed Management ◽

Management Practices ◽

Application Rate ◽

Good Management ◽

Peanut Production

Successful weed control in peanuts involves use of good management practices in all phases of peanut production. This 11-page document lists herbicide products registered for use in Florida peanut production, their mode of actions group, application rate per acre and per season, and reentry interval. It also discusses the performance of these herbicides on several weeds under Florida conditions. Written by J. A. Ferrell, G. E. MacDonald, and P. Devkota, and published by the UF/IFAS Agronomy Department, revised May 2020.

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Seasonal Nonstructural Carbohydrate Patterns in Dewberry (Rubus spp.) Roots

Weed Science ◽

10.1017/wsc.2020.96 ◽

2021 ◽

pp. 1-23

Author(s):

Katherine M. Ghantous ◽

Hilary A. Sandler

Keyword(s):

Weed Management ◽

Management Practices ◽

Soluble Sugars ◽

Leaf Expansion ◽

Control Measures ◽

Growth Stages ◽

Phenological Stages ◽

Long Term Storage ◽

Nonstructural Carbohydrate ◽

Fruit Maturity

Abstract Applying control measures when carbohydrate levels are low can decrease the likelihood of plant survival, but little is known about the carbohydrate cycles of dewberry (Rubus spp.), a problematic weed group on cranberry farms. Weedy Rubus plants were collected from areas adjacent to production beds on commercial cranberry farms in Massachusetts, two locations per year for two years. For each site and year, four entire plants were collected at five phenological stages: budbreak, full leaf expansion, flowering, fruit maturity, and after onset of dormancy. Root sections were analyzed for total nonstructural carbohydrate (TNC; starch, sucrose, fructose, and glucose). Overall trends for all sites and years showed TNC were lowest at full leaf expansion or flowering; when sampled at dormancy, TNC concentrations were greater than or equal to those measured at budbreak. Starch, a carbohydrate form associated with long-term storage, had low levels at budbreak, leaf expansion and/or flowering with a significant increase at fruit maturity and the onset of dormancy, ending at levels higher than those found at budbreak. The concentration of soluble sugars, carbohydrate forms readily usable by plants, was highest at budbreak compared to the other four phenological samplings. Overall, our findings supported the hypothesis that TNC levels within the roots of weedy Rubus plants can be predicted based on different phenological growth stages in Massachusetts. However, recommendations for timing management practices cannot be based on TNC cycles alone; other factors such as temporal proximity to dormancy may also impact Rubus plants recovery and further research is warranted. Late-season damage should allow less time for plants to replenish carbohydrate reserves (prior to the onset of dormancy), thereby likely enhancing weed management tactics effectiveness over time. Future studies should consider tracking the relationship between environmental conditions, phenological stages, and carbohydrate trends.

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Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Water ◽

10.3390/w13111547 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1547

Author(s):

Jian Sha ◽

Xue Li ◽

Man Zhang ◽

Zhong-Liang Wang

Keyword(s):

Neural Network ◽

Water Quality ◽

Deep Learning ◽

Real Time ◽

Best Management Practices ◽

Input Data ◽

Management Practices ◽

Quality Parameters ◽

Water Quality Parameters ◽

Real Time Monitoring

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

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Effect of Weed Management on the Parasitoid Community in Mediterranean Vineyards

Biology ◽

10.3390/biology10010007 ◽

2020 ◽

Vol 10 (1) ◽

pp. 7

Author(s):

Gabriella Möller ◽

Tamar Keasar ◽

Idan Shapira ◽

Daniella Möller ◽

Marco Ferrante ◽

...

Keyword(s):

Cover Crops ◽

Weed Management ◽

Soil Conservation ◽

Management Practices ◽

Ground Cover ◽

Parasitoid Species ◽

Parasitoid Community ◽

Growing Seasons ◽

Conservation Biocontrol ◽

Suction Sampling

Enriching agroecosystems with non-crop vegetation is a popular strategy for conservation biocontrol. In vineyards, the effects of specific seeded or planted cover crops on natural enemies are well-studied, whereas conserving spontaneously developing weeds received less attention. We compared parasitoid communities between matched pairs of vineyard plots in northern Israel, differing in weed management practices: “herbicide”, repeated herbicide applications vs. “ground cover”, maintaining resident weeds and trimming them when needed. Using suction sampling, we assessed the parasitoids’ abundance, richness, and composition during three grape-growing seasons. Ground cover plots had greater parasitoid abundances and cumulative species richness than herbicide-treated plots, possibly because of their higher vegetation cover and richness. Dominant parasitoid species varied in their magnitude and direction of response to weed management. Their responses seem to combine tracking of host distributions with attraction to additional vegetation-provided resources. Parasitoid community composition was mildly yet significantly influenced by weed management, while season, year, and habitat (weeds vs. vine) had stronger effects. Vineyard weeds thus support local biocontrol agents and provide additional previously demonstrated benefits (e.g., soil conservation, lower agrochemical exposure) but might also attract some crop pests. When the benefits outweigh this risk, weed conservation seems a promising step towards more sustainable agricultural management.

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