Current Issue : April - June Volume : 2020 Issue Number : 2 Articles : 5 Articles
Redroot pigweed (Amaranthus retroflexus L.) is a nuisance weed that affects\ncotton (Gossypium hirsutum L.) growth and yield worldwide. Being able to\ndistinguish redroot pigweed from cotton would help producers and crop\nconsultants better implement strategies used to suppress and control it.\nHyperspectral reflectance properties of weed and crop canopies have been\nused to differentiate between them. Currently, no information is available on\nthe application of hyperspectral data to distinguish redroot pigweed from\ncotton with different leaf shapes. Positive results will further support the exploration\nof remote sensing technology for distinguishing redroot pigweed\nfrom cotton. The objectives were to compare canopy hyperspectral reflectance\nof redroot pigweed to canopy hyperspectral reflectance of okra and super\nokra leaf cotton and to identify regions of the spectrum in which differences\nexist in their reflectance properties. Hyperspectral reflectance measurements\nof redroot pigweed and cotton were obtained with a spectroradimeter\non May 6 and June 27, 2019. Plants grown in a greenhouse were used\nfor this study. One-hundred and sixty-two 10-nm bands (400 - 2350 nm\nspectral range) were evaluated with analysis of variance (p less than equal to 0.05) and Dunnettâ??s\ntest (p less than equal to 0.05) to determine the wavebands that were useful for separating\nredroot pigweed from okra leaf and super okra leaf cotton. The following\nbands were consistent in distinguishing redroot pigweed and okra leaf\ncotton on both dates: 420 nm, 510 - 650 nm, 690 - 740 nm, and 2000 - 2010\nnm; whereas, 400 - 500 nm, 1480 - 1780 nm, and 1990 - 2350 nm were identified\nfor both dates for separating redroot pigweed from super okra leaf cotton.\nCommercial imaging systems used on ground-based or airborne platforms\ncan be easily tuned into the spectral bands listed in this study, thus\nproviding managers with a tool to use for identifying redroot pigweed in cotton\nproduction systems....
A total of six experiments were conducted over a two-year period (2018,\n2019) at the University of Guelph Ridgetown Campus to assess the efficacy of\nvarious herbicides applied postemergence (POST) for the control of common\nchickweed in winter wheat. Fluroxypyr/bromoxynil/MCPA,\npyrasulfotole/bromoxynil, pyrasulfotole/bromoxynil/fluroxypyr,\npyrasulfotole/bromoxynil/thiencarbazone,\npyrasulfotole/bromoxynil/thiencarbazone + MCPA ester, tolpyralate and fluroxypyr/\nhalauxifen + MCPA EHE, applied POST, controlled common\nchickweed only 5% - 42% at 2 weeks after treatment (WAT) and 1% - 23% at\n4 WAT and resulted in common chickweed density and biomass that was\nsimilar to non-treated weedy control. Fluroxypyr/halauxifen + pyroxsulam +\nMCPA EHE, applied POST, provided 57% - 82% control of common chickweed\nand reduced density 93% and biomass 98% compared to the non-treated\ncontrol. Thifensulfuron/tribenuron, thifensulfuron/tribenuron + MCPA ester,\nthifensulfuron/tribenuron + fluroxypyr + MCPA ester, tribenuron +\nthiencarbazone, and tribenuron + thiencarbazone + MCPA ester, applied\nPOST, controlled common chickweed 98% - 100% and reduced common\nchickweed density 96% - 98% and common chickweed biomass 99%. Based\non these results, herbicide treatments which contained tribenuron including\nthifensulfuron/tribenuron, thifensulfuron/tribenuron + MCPA ester, thifensulfuron/\ntribenuron + fluroxypyr + MCPA ester, tribenuron + thiencarbazone,\nand tribenuron + thiencarbazone + MCPA ester were the most efficacious\nfor the control of common chickweed in wheat. In addition, fluroxypyr/\nhalauxifen + pyroxsulam + MCPA EHE, applied POST, can provide\nadequate control of common chickweed in winter wheat....
A variety of sensing and monitoring systems have been developed based on\nthe concept of open-source and on open-source hardware and software\ncomponents. Availability and relatively low cost of hardware components and\navailability and ease of use of software components allow access to sensing\nand monitoring technologies that were previously unattainable to many potential\nusers. Advances in electronic monitoring and evolving cellular communications\ntechnologies are increasingly offering more, simpler, and less\nexpensive options for remote monitoring. Due to the near-future cessation\nof 2G and 3G cellular network services, however, many existing monitoring\nsystems will need to be redesigned to operate on alternative cellular networks.\nA soil-moisture monitoring system was developed incorporating updated\nopen-source Arduino microcontrollers and the recently introduced LTE \nCat-M1 cellular network to transmit sensor measurements via the cellular\nnetwork for access on an internet website. The monitoring system costs approximately\nUS$130 to construct the electronic circuitry and less than US$1\nper month for cellular network access and data transmission. Data were\ntransmitted with a 95% success rate, and the monitoring system operated\ncontinuously throughout an entire crop growing season with no battery recharge\nor maintenance requirements. The design and operation of the monitoring\nsystem can serve as a basis for other remote monitoring systems....
Five experiments were conducted in Ontario, Canada from 2016 to 2018 to\ndetermine how doses of S-metolachlor and halosulfuron applied preemergence\n(PRE) should be adjusted to control specific weed species in white\nbean. S-metolachlor, halosulfuron, and S-metolachlor + halosulfuron caused\nminimal (1% to 4%) injury in white bean. Weed interference reduced white\nbean yield 54%. On average, weed interference with S-metolachlor and halosulfuron\ndecreased yield 34% and 29%, respectively. In contrast, white bean\nseed yield was similar to the weed-free control with the S-metolachlor + halosulfuron\ntankmixes. S-metolachlor applied alone controlled A. theophrasti ,\nA. retroflexus , A. artemisiifolia , C. album, E. crus-galli and S. viridis 0% to\n3%, 78% to 93%, 0% to 9%, 5% to 15%, 97% to 99% and 96% to 98%, respectively.\nHalosulfuron applied alone controlled A. theophrasti , A. retroflexus , A.\nartemisiifolia , C. album, E. crus-galli and S. viridis 39% to 87%, 93% to 99%,\n64% to 88%, 34% to 59%, 10% to 30% and 13% to 35%, respectively. S-metolachlor\n+ halosulfuron tankmixes controlled A. theophrasti , A. retroflexus , A.\nartemisiifolia , C. album, E. crus-galli and S. viridis 47% to 94%, 98% to 100%,\n78% to 94%, 37% to 78%, 94% to 98% and 91% to 96%, respectively. Weed\ndensity and biomass reductions with the herbicides evaluated followed the\nsame pattern as visible weed control assessments. Results from this study indicate\nthat doses of S-metolachlor and halosulfuron, when applied as a tankmix,\nshould be adjusted based on a weed species composition in each individual\nwhite bean field....
Binadhan-10 & Binadhan-11 are climate smart stress tolerant high yielding\nrice varieties (yield > 4 t.ha-1) have saline tolerant EC up to 12 ds/m and\nsubmergence tolerant up to 20 - 25 days capacity. The present study was an\nattempt to analyze the yield gap of stress tolerant varieties Binadhan-10 &\nBinadhan-11 in some selected areas of Bangladesh. The objectives of the\nstudy were: 1) to estimate the yield gap of Binadhan-10 &-11 growers among\nthe study areas; 2) to identify the factors affecting the yield of these variety;\nand 3) to suggest some policy guidelines to minimize the yield gap. The\nstudy was conducted in eight Binadhan-10 & Binadhan-11 growing areas in\nBangladesh. In this study, four districts namely Satkhira, Khulna, Barishal,\nand Coxâ??s Bazar were used for Binadhan-10 and Mymensingh, Jamalpur,\nSherpur and Sunamgonj were taken for Binadhan-11. It is based on primary \nlevel data from eight sub-districts among the study areas. A total of 240 farmers\nwere randomly selected (30 from each location) to collect the data with a\npre-designed questionnaire. Farmer were grouped according to saline affected\nand not-affected for saline tolerant variety Binadhan-10 and not affected,\naffected (1 - 10 days) and highly affected (10 - 20 days) for submergence\ntolerant rice variety Binadhan-11 to identify existing yield gap. Tabular\nas well as Zandstra method were applied for analysis the data. The study\nalso found factors affecting the gap and some policy guidelines to minimize\nthe gap....
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