2017
DOI: 10.2134/agronj2016.06.0348
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Comparison of Weed Seedbanks in Different Rice Planting Systems

Abstract: Core Ideas Weed seedbanks were compared in three rice planting systems: machine‐transplanted rice, water direct‐seeded rice, and dry direct‐seeded rice. Weed seedbanks were mainly distributed in soil within a depth of 10 cm. Dry direct‐seeded rice tended to maintain larger seedbanks of sedges, grasses, and some upland weeds. Water direct‐seeded rice contained the smallest weed seedbank overall. Machine‐transplanted rice had larger seedbanks of broadleaf weeds and some traditional rice weeds. Machine‐transplant… Show more

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Cited by 11 publications
(13 citation statements)
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References 16 publications
(29 reference statements)
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“…e result in Table 9 shows that the feature set extracted has the potential for effective feature vector representation of paddy crop and weed images for the classification process. (11) for i ⟵ 1 to n do (12) Train C i on Train set-1 (13) end for (14) for i ⟵ 1 to len do (15) p Predict probability of classes for sample S i using C1, where S i Є Test-set ( 16) q Predict probability of classes for sample S i using C2, where S i Є Test-set (17) end for (18) for i ⟵ 1 to len do (19)…”
Section: Case Studymentioning
confidence: 99%
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“…e result in Table 9 shows that the feature set extracted has the potential for effective feature vector representation of paddy crop and weed images for the classification process. (11) for i ⟵ 1 to n do (12) Train C i on Train set-1 (13) end for (14) for i ⟵ 1 to len do (15) p Predict probability of classes for sample S i using C1, where S i Є Test-set ( 16) q Predict probability of classes for sample S i using C2, where S i Є Test-set (17) end for (18) for i ⟵ 1 to len do (19)…”
Section: Case Studymentioning
confidence: 99%
“…end if (34) if q[i][j] > max2 then (35) max2 q[i][j] (36) index2 j (37) end if (38) end for (39) (11) for i ⟵ 1 to n do (12) Fit calibrated C i using isotonic regression on Train set-1 (13) end for (14) for i ⟵ 1 to len do (15) p Predict probability of classes for sample S i using C1, where S i Є Test-set (16) q Predict probability of classes for sample S i using C2, where S i Є Test-set (17) end for (18) for i ⟵ 1 to len do (19)…”
Section: Case Studymentioning
confidence: 99%
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“…Phleum paniculatum seed is quite small, with a thousand-seed weight of only 0.17 to 0.23 g. Small seeds have limited nutritional storage and sustaining extensive seedling growth from germination stage to emergence may be the reason that seedling emergence of P. paniculatum is more sensitive to soil burial depth than other weed species (Baskin and Baskin, 1998). Many studies have reported that zero-tillage and reduced tillage often facilitate the seriousness of weed occurrence in croplands (Thomas et al, 2004;Chauhan and Johnson, 2009;Chen et al, 2017). In China, farmers either till lands to a depth of less 5 cm before seeding wheat or do not till the soil at all.…”
Section: Discussionmentioning
confidence: 99%
“…and the small, elongate Digitaria sp.. Digitaria spp. are widespread weeds, both of rice and millet cultivation(Chen et al 2017;Moody 1989). While kodo millet (Paspalum scorbiculatum)was an important cultivar in Iron Age and Early Historic southern India(Cooke and Fuller 2015).…”
mentioning
confidence: 99%