Modeling light interception and distribution in mixed canopy of common cocklebur (Xanthium stramarium) in competition with corn

Vazin, F.; Hassanzadeh, M.; Madani, Ali; Mahallati, Mehdi Nassiri; Nasri, Mohammad

doi:10.1590/s0100-83582010000300001

Cited by 20 publications

(13 citation statements)

References 8 publications

(8 reference statements)

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“…In general, the LAD max of velvetleaf was lower than LAD max of bean and soybean (Figures 1a, 1b, 1 d, 1e), which indicated greater competitive ability of this two plants compare to velvetleaf. Our findings was in according to Vazin et al (2010) results. Uchino et al (2012) reported that LAI of weed decreased due to increasing of leaf area and growth of main crops and cover crops.…”

Section: Leaf Area Densitysupporting

confidence: 79%

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Effect of cover crops on maize-velvet leaf competition: leaf area density and light interception

Zaefarian

shakibafar

Rezvani

et al. 2016

AAS

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Cover crops influence on canopy structure and light interception of maize (Zea mays L.) and velvetleaf (Abutilon theophrasti Medik), was studied in a field experiment. Treatments included planting of bean (Phaseolus vulgaris L.), soybean (Glycine max (L.) Merr.) and berseem clover (Trifolium alexandrium L.) as cover crops at the same date and 21 days after maize. Sole cropping of maize under weed-free and weedy conditions were also included in this experiment. All tested cover crops significantly reduced leaf area density and height of velvetleaf up to 50 %, while maize leaf area density increased in the presence of cover crops. Among cover crops, bean and soybean were the most effective in reducing velvetleaf leaf area density and height. Bean and soybean also strongly reduced absorbed light by velvetleaf by up to 80 % compared to clover. Maize grain yields were significantly influenced by cover crops planting in the inter row space. Compared to weeds free plots, only treatment with soybean as a cover crop resulted in similar maize grain yields, while maize intercropping with bean and clover significantly reduced maize yields. Delayed planting of cover crops, 21 day after maize, increased maize grain yield compared to cover crops and maize planting at the same time. Obravnavanja so obsegala setev nizkega fižola (Phaseolus vulgaris L.), soje (Glycine max (L.) Merr.) in aleksandrijske detelje (Trifolium alexandrium L.) kot podsevkov, posejane istega dne kot koruza ali 21 dni po njeni setvi. V poskus sta bili vključeni tudi 2 kontroli (čista setev koruze z zatiranjem in brez zatiranja plevelov). Vsi preizkušeni podsevki so značilno zmanjšali gostoto listne površine in višino bržunastega osleza do 50 %, medtem ko se je gostota listne površine koruze v prisotnosti vseh treh podsevkov povečala. Med podsevki sta bila fižol in soja najbolj učinkovita v zmanjševanju gostote listne površine in višine bržunastega osleza. Fižol in soja sta v primerjavi z deteljo najmočneje zmanjšala absorbirano svetlobo bržunastega osleza, do 80 %. Podsevki v vrste med koruzo so značilno vplivali na pridelek njenega zrnja. V primerjavi s kontrolo brez plevela je samo obravnavanje s sojo kot podsevkom dalo podobne pridelke, podsevka fižola in detelje sta značilno zmanjšali pridelek zrnja koruze. Odložena setev podsevkov, 21 dni po setvi koruze, je povečala pridelek zrnja koruze v primerjavi z obravnavanji, ko so bili koruza in podsevki posejani istočasno.Ključne besede: zgradba sestoja, gostota listne površine, prestrezanje svetlobe, indeks listne površine, koruza, bržunasti oslez, tekmovalnost plevelov Zahra SHAKIBAFAR et al.

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Section: Leaf Area Densitysupporting

confidence: 79%

“…Light is one of the crucial factors affecting on competition in mixed canopy (Vazin et al, 2010). The total photosynthetically active radiation (PAR) intercepted and distribution of light in plant canopy are important for evaluating the potential carbon uptake by crop (Sassenrath-Cole, 1995).…”

Section: Introductionmentioning

confidence: 99%

Effect of cover crops on maize-velvet leaf competition: leaf area density and light interception

Zaefarian

shakibafar

Rezvani

et al. 2016

AAS

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“…One of the greatest successes of the Green Revolution was based on the modification of plant architecture leading to major increase in production per unit area (Khush 2001). Plant architecture improvement can contribute to maize grain yield by enhancing photosynthetic efficiency and increasing planting density (Duvick 2005;Vazin et al 2010;Tian et al 2011). Leaf angle and leaf space above ear position in maize are both important components of plant architecture, influencing canopy morphology and photosynthetic efficiency and, as a result, overall yield.…”

Section: Discussionmentioning

confidence: 99%

Identification of QTL for leaf angle and leaf space above ear position across different environments and generations in maize (Zea mays L.)

Chen

Zheng

et al. 2015

Euphytica

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The yield of maize (Zea mays L.) is affected by the plant architecture which is associated with the distribution of light within canopy and utilization of solar energy within population. Plant architecture of maize is mainly characterized by leaf angle (LA) and leaf space (LS). To analyze the genetic mechanism of LA and LS above ear position in maize, a genetic linkage map composed of 212 simple sequence repeat markers was constructed based on a F 2 population derived from the cross between the compact inbred line CY5 and the expanded inbred line YL106. The map spanned 1,153.39 cM in length with an average interval of 5.44 cM. By using the inclusive composite interval mapping method, QTLs for LA and LS above ear position were identified based on two field mapping populations consisted of 144 F 2:3 families in three environments and 144 F 4 families, respectively. In F 2:3 population, three consistent QTLs qSecLA1a, qThiLA1a, and qThiLS7 were detected in both single-environment analysis and joint-environment analysis. The qSecLA1a between bnlg1803 and bnlg1007 on chromosome 1.02 explained 26.99 and 18.51 % of the phenotypic variation, qThiLA1a between bnlg1803 and bnlg1007 on chromosome 1.02 explained 24.14 and 22.00 % of the phenotypic variation and qThiLS7 between bnlg1305 and umc1787 on chromosome 7.02/7.03 explained 13.77 and 9.96 % of the phenotypic variation in single environment analysis while the three QTLs explained 29.10, 31.86 and 11.20 % of the phenotypic variation, respectively in joint environment analysis. Moreover, there were major QTLs near bnlg1803 on chromosome 1 for SecLA and ThiLA stably expressing in F 2:3 and F 4 generations. The results of this study could provide references for genetic modification and molecular marker-assisted selection for LA and LS in maize.

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“…Maize grain yield is normally highly and positively correlated with kernel numbers. The number of kernels per plant depends on the number of ears per plant and the number of mature kernels per ear [16]. To produce more grain per unit area, the genetic potential of most recent hybrids takes advantage of their capacity to withstand higher densities [17].…”

Section: Plant Density and Kernel Numbermentioning

confidence: 99%

Estimation of Maize (Zea mays L.) Yield Per Harvest Area: Appropriate Methods

Tandzi

Mutengwa

2019

Agronomy

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Standardization of crop yield estimation methods at various levels of farming helps to obtain accurate agricultural statistics as well as assessing the suitability of agricultural practices under various production conditions. The current paper reviews various maize yield estimation methods, taking into account available yield parameters, and it also analyses the yield gap between maize potential and attainable yield. The easiest and more reliable methods of yield estimation are based on yield parameters collected from the field. However, farmer estimation methods are cheaper and faster compared to any other method of yield estimation from farmers’ fields. This paper also elaborates on the importance of the use of more complex methods for yield estimation, such as remote sensing and crop modelling. These complex methods are more accurate and can predict yield before field harvest with less deviation from the exact harvest yield. However, they are very expensive and not efficient for small plots of land (less than 1 ha). Factors that contribute to the gap between potential and actual yield include poor implementation of agricultural policies, strict regulation of fertilizer inputs, vulnerability of smallholder cropping systems to adverse climatic conditions, occurrence of biotic and abiotic constraints, as well as unavailability of seeds and labor.

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Modeling light interception and distribution in mixed canopy of common cocklebur (Xanthium stramarium) in competition with corn

Cited by 20 publications

References 8 publications

Effect of cover crops on maize-velvet leaf competition: leaf area density and light interception

Effect of cover crops on maize-velvet leaf competition: leaf area density and light interception

Identification of QTL for leaf angle and leaf space above ear position across different environments and generations in maize (Zea mays L.)

Estimation of Maize (Zea mays L.) Yield Per Harvest Area: Appropriate Methods

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