Assessment of yield and economic losses in agriculture due to weeds in India

Gharde, Yogita; Singh, Prabhjot; Dubey, Rachana; Gupta, P.K.

doi:10.1016/j.cropro.2018.01.007

Cited by 288 publications

(157 citation statements)

References 27 publications

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“…However, the change in land preparation practices i.e., CT to ZT not only influenced the weed species composition and level of infestation, which subsequently emerged with DSR crop, but also affected the Weed Seed Bank (WSB) dynamics. Actually, in India, in economic terms, weeds in rice field cause a loss of 4420 million USD [6]. This too differs with the Crop Establishment (CE) method; for example, uncontrolled weed growth reduces the yield of transplanted rice by 12 per cent, whereas dry seeded rice sown without soil tillage leads to 98 per cent reduction in crop yield [7].…”

Section: Introductionmentioning

confidence: 99%

Changes in the Weed Seed Bank in Long-Term Establishment Methods Trials under Rice-Wheat Cropping System

et al. 2020

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The rice-wheat cropping system in the Indo-Gangetic Plains is the backbone of food security in India. In the 1990s, due to the scarcity of resources, the traditional Crop Establishment (CE) method shifted from Conventional Till Puddle Transplanted Rice (CTPTR) to CT Direct Seeded Rice (CTDSR) and Zero-Till DSR (ZTDSR) in paddy; and in wheat, from Conventional Till Wheat (CTW) to Zero Till Wheat (ZTW), with residue retention in rice (RRR) or in both rice and wheat (RRRW). Shift in CE methods led to change in Weed Seed Bank (WSB) dynamics and ultimately affected the weed management program. After five years of field trials, soil samples were drawn as per 2-factors factorial randomized block design. Factor-I comprised 4-CE methods, whereas factor-II consisted of 3-soil depths (0-10, 10-20 and 20-30 cm). Results showed CTPTR-CTW and ZTDSR-ZTW (RRRW) record the highest seed bank (SB) of grasses, sedges and BLWs as total weeds, in general; and predominant weeds like Echinochloa spp., Ammania baccifera, Commelina benghalensis and Digitaria sanguinalis, in particular. It also showed the higher species richness (D Mg ) and Shannon-Weaver (H') indices. CTDSR-CTW and CTDSR-ZTW (RRR) show the lowest WSB and at par with Shannon-Weaver (H') index; further, lowest species richness (D Mg ) under CTDSR-CTW. Species Evenness (J') and Simpson index (λ) vary non-significantly with CE methods. Furthermore, 0-10 cm soil depth showed the highest SB of different category of total weed, predominant weeds as well as higher values of D Mg , H', and λ; whereas reverse trend was observed in Whittaker Statistic (β W ). Interaction between CE methods and soil depth revealed most of WSB lying on the top layer in case of ZTDSR-ZTW (RRRW) and CTDSR-ZTW (RRR); while CTPTR-CTW showed almost uniform WSB distribution, and in case of CTDSR-CTW, a gradual decrease in WSB with soil depth.

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Section: Introductionmentioning

confidence: 99%

Changes in the Weed Seed Bank in Long-Term Establishment Methods Trials under Rice-Wheat Cropping System

et al. 2020

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“…The cash crop yield reduction is increased when weed competition occurs in early growth stages. Overall, weed infestation contributes to the largest potential yield losses (34%) relative to other plant pests such as insects or pathogens …”

Section: Introductionmentioning

confidence: 99%

“…Overall, weed infestation contributes to the largest potential yield losses (34%) relative to other plant pests such as insects or pathogens. 4,5 Generally, the distribution of weeds in a crop field is in patches; 6,7 however, herbicides are applied uniformly across fields. Chemical methods such as the use of herbicides are the most effective method of weed control in modern agriculture.…”

Section: Introductionmentioning

confidence: 99%

Pre‐planting weed detection based on ground field spectral data

Pott

Amado

Schwalbert

et al. 2019

Pest Management Science

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BACKGROUND Site‐specific weed management (SSWM) demands higher resolution data for mapping weeds in fields, but the success of this tool relies on the efficiency of optical sensors to discriminate weeds relative to other targets (soils and residues) before cash crop establishment. The objectives of this study were to (i) evaluate the accuracy of spectral bands to differentiate weeds (target) and other non‐targets, (ii) access vegetation indices (VIs) to assist in the discrimination process, and (iii) evaluate the accuracy of the thresholds to distinguish weeds relative to non‐targets for each VI using training and validation data sets. RESULTS The main outcomes of this study for effectively distinguishing weeds from other non‐targets are (i) training and validation data exhibited similar spectral curves, (ii) red and near‐infrared spectral bands presented greater accuracy relative to the other bands, and (iii) the tested VIs increased the discrimination accuracy related to single bands, with an overall accuracy above 95% and a kappa above 0.93. CONCLUSION This study provided a novel approach to distinguish weeds from other non‐targets utilizing a ground‐level sensor before cash crop planting based on field spectral data. However, the limitations of this study are related to the spatial resolution to distinguish weeds that might be closer to the one this study presented, and also related to the soil and crop residues conditions at the time of collecting the readings. Overall the results presented contribute to an improved understanding of spectral signatures from different targets (weeds, soils, and residues) before planting time supporting SSWM. © 2019 Society of Chemical Industry

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“…Validation of these models shows that the above mention models were accurately predicting the yield loss. infestation in farmers' field (Gharde et al, 2018). In another study, it was estimated that in India the overall yield loss in different crop due to weed infestation is around 36.5% (Bhan et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…In another study, 20 to 28 billion economic losses were estimated due to weed infestation in India (Sahoo and Saraswat, 1988;Sachan, 1989). More recently, in a scientific study, Gharde et al, (2018) reported an annual loss of about 11 billion USD in 10 major crops due to weeds alone. Hence, weeds may be considered as biggest threat to crop production systems.…”

Section: Introductionmentioning

confidence: 99%