Herbicide Reduction Methods

MartinWeis,; Keller, Martina; Ayala, Victor Rueda

doi:10.5772/31908

Cited by 5 publications

(3 citation statements)

References 71 publications

(81 reference statements)

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“…With the outcomes of PED trials, economic thresholds can be determined under today's situation and under conditions similar to farmers' fields. Such thresholds can be implemented in a site‐specific weed control system …”

Section: Introductionmentioning

confidence: 99%

Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: An example based on three winter wheat trials

et al. 2013

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Section: Introductionmentioning

confidence: 99%

Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: An example based on three winter wheat trials

et al. 2013

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“…While the first depends on experiences and agronomic knowledge of the farmer, the latter could be addressed by developing SSWM strategies. Such agronomic strategies can lead to: (i) a relevant reduction of environmental impacts on soil, and surface and shallow water bodies; (ii) a decrease of weed management costs for herbicides; (iii) compliance with the European legislation on the use of pesticides [17,18,[24][25][26][27].…”

Section: Introduction 1a Spatial Approach For Weed Management In Smart Farmingmentioning

confidence: 99%

Can Commercial Low-Cost Drones and Open-Source GIS Technologies Be Suitable for Semi-Automatic Weed Mapping for Smart Farming? A Case Study in NE Italy

et al. 2021

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Weed management is a crucial issue in agriculture, resulting in environmental in-field and off-field impacts. Within Agriculture 4.0, adoption of UASs combined with spatially explicit approaches may drastically reduce doses of herbicides, increasing sustainability in weed management. However, Agriculture 4.0 technologies are barely adopted in small-medium size farms. Recently, small and low-cost UASs, together with open-source software packages, may represent a low-cost spatially explicit system to map weed distribution in crop fields. The general aim is to map weed distribution by a low-cost UASs and a replicable workflow, completely based on open GIS software and algorithms: OpenDroneMap, QGIS, SAGA and OpenCV classification algorithms. Specific objectives are: (i) testing a low-cost UAS for weed mapping; (ii) assessing open-source packages for semi-automatic weed classification; (iii) performing a sustainable management scenario by prescription maps. Results showed high performances along the whole process: in orthomosaic generation at very high spatial resolution (0.01 m/pixel), in testing weed detection (Matthews Correlation Coefficient: 0.67–0.74), and in the production of prescription maps, reducing herbicide treatment to only 3.47% of the entire field. This study reveals the feasibility of low-cost UASs combined with open-source software, enabling a spatially explicit approach for weed management in small-medium size farmlands.

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“…Continuous use of the few available active ingredients of herbicides has enhanced the selection of resistant weed populations. These populations have increased immensely in the last decades, thus demanding that weed management strategies evolve accordingly (Weis et al 2012;Colbach et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Allelopathic properties of Calliandra haematocephala Hassk. extracts and fractions as an alternative for weed management in quinoa and rice crops

et al. 2020

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In this study, aqueous extracts of Calliandra haematocephala Hassk. leaves and inflorescences were tested on seeds of quinoa (Chenopodium album L.) and rice (Oryza sativa L.), and on some of the most noxious-associated weeds, Chenopodium album L. and Holcus lanatus L. in quinoa, and Echinochloa crus-galli (L.) P. Beauv., Echinochloa colona L., Eclipta prostrata L. and Rottboellia cochinchinensis (Lou.) W.D. Clayton in rice. The objectives were to identify extract concentrations at which 50 and 90% of germination (GR [50,90]) and radicle elongation (RR [50,90]) were inhibited, to fractionate inflorescence extracts for facilitating identifying the chemical group causing allelopathic effects, and to evaluate the fraction showing the stronger weed suppression effects and the least crop damage. Increasing extract concentration rates (0, 6.25, 12.5, 25, 50 and 100% crude extract) were applied to seeds of target crops and weeds. Flower extracts at rates < 0.30 produced GR [50] and RR [50] on H. lanatus, and GR [90] and RR [90] in C. album, while quinoa seeds were not affected. Rice and its target weeds were minimally affected by flower extracts, whereas radicle elongation of all species was significantly reduced. A concentration rate > 0.52 caused the RR [50] on rice and all its target weeds. Fractions were quantitatively and qualitatively analysed to detect phytochemical groups, using specific chemical reagents and thin-layer chromatography (TLC). The fraction F3 from aqueous flower extract showed a high content of flavonoids, assumed as the potential allelochemical substance. Total flavonoid content in F3 was quantified as 2.7 mg of quercetin per g F3, i.e., 12.8 mg of quercetin per g of inflorescence material. Additionally, field equivalent extract rates obtained from the harvested fresh inflorescence biomass could be determined. These rates ranged between 90 and 143 mL l −1 of F3 aqueous fraction, while for ethanol F3 were 131 mL l −1. Our results are encouraging for finding sustainable and ecologically friendly alternatives for weed management in crops of high nutritional value, contributing also to counteract the growing problem of herbicide resistance.

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Herbicide Reduction Methods

Cited by 5 publications

References 71 publications

Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: An example based on three winter wheat trials

Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: An example based on three winter wheat trials

Can Commercial Low-Cost Drones and Open-Source GIS Technologies Be Suitable for Semi-Automatic Weed Mapping for Smart Farming? A Case Study in NE Italy

Allelopathic properties of Calliandra haematocephala Hassk. extracts and fractions as an alternative for weed management in quinoa and rice crops

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