Results 131 to 140 of about 2,519 (160)

Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance. [PDF]

Theor Appl Genet
Berlingeri J, Fuentes A, Ranario E, Yun H, Rim EY, Garrett O, Howard A, LaPorte MF, Lo S, Pauli D, Hershberger J, Earles M, Van Deynze A, Brummer EC, Michelmore R, Wong CYS, Magney TS, Ronald PC, Runcie DE, Bailey BN, Diepenbrock CH.   +20 more
europepmc   +1 more source

​Fusarium Protein Toolkit: a web-based resource for structural and variant analysis of Fusarium species. [PDF]

BMC Microbiol
Kim HS, Haley OC, Portwood Ii JL, Harding S, Proctor RH, Woodhouse MR, Sen TZ, Andorf CM.   +7 more
europepmc   +1 more source

Design of Microbial Consortia Based on Arbuscular Mycorrhizal Fungi, Yeasts, and Bacteria to Improve the Biochemical, Nutritional, and Physiological Status of Strawberry Plants Growing under Water Deficits. [PDF]

Plants (Basel)
Pérez-Moncada UA, Santander C, Ruiz A, Vidal C, Santos C, Cornejo P.   +5 more
europepmc   +1 more source

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Testing the CERES-Maize model in Belgian conditions

European Journal of Agronomy, 1993
Abstract CERES-Maize was tested in two years with two cultivars at Louvain-la-Neuve, Belgium. Observed values of the genetic coefficients differed between cultivars and were within the wide range of values found elsewhere in N. W. Europe for cultivars of the same precocity group.
A. Lahrouni, J.-F. Ledent, R. Cazanga Solar, D. Mouraux   +3 more
openaire   +1 more source

Application of CSM-CERES-Maize model in optimizing irrigated conditions

Outlook on Agriculture, 2016
Maize is one of the main cereal crops in Pakistan with sensitivity to drought at various developmental stages known to influence the yield. The impact of variable weather conditions on maize yield can be analyzed with crop simulation models. The CSM-CERES-Maize model has been widely used to assess irrigation strategies for maize.
Muhammad Mubeen, Ashfaq Ahmad, Aftab Wajid, Tasneem Khaliq, Hafiz Mohkum Hammad, Syeda Refat Sultana, Shakeel Ahmad, Shah Fahad, Wajid Nasim   +8 more
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Simulation of Kernel Number and Yield using CERES-Maize 3.51

Transactions of the Kansas Academy of Science, 2011
The primary objective in corn production is to produce maximum yield, but many factors can interact to reduce yields. Crop models can be used as management tools to maximize returns to the producer and help manage resources. However, crop models need to accurately predict yield and yield components to be accepted on a large scale. The objective of this
Annette A. James, Richard L. Vanderlip, Steve Welch   +2 more
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ALTERNATE APPROACH TO IMPROVE KERNEL NUMBER CALCULATION IN CERES–MAIZ

Transactions of the ASAE, 2001
CERES–Maize is a process–oriented model that has been widely used to predict growth, development, and yield of a maize crop as affected by environment, genotypes, and management. The model has performed well in predicting yield on a large scale (field, county, region) but has had difficulty in predicting the range of variation in kernel numbers found
null J. I. Lizaso, null W. D. Batchelor, null S. S. Adams   +2 more
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Enhancing the ability of CERES-Maize to compute light capture

Agricultural Systems, 2003
Abstract Recently it has been proposed to use the relationship between average intercepted photosynthetically active radiation (IPAR) around silking and total number of seeds per plant as the basis to improve kernel number prediction in CERES-Maize. However, there has been no previous evaluation of the accuracy of IPAR predictions in the model.
J.I Lizaso, W.D Batchelor, M.E Westgate, L Echarte   +3 more
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Comparing genetic coefficient estimation methods using the CERES-Maize model

Agricultural Systems, 2000
Abstract Many crop simulation models use genetic coefficients to characterize varieties or hybrids. Two methods now used with CERES-Maize to obtain genetic coefficients are: (1) direct experimental measurement; and (2) estimation using the Genetic Coefficient Calculator (GENCALC), an iterative computerized procedure.
E Román-Paoli, S.M Welch, R.L Vanderlip
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Simulating Source‐Limited and Sink‐Limited Kernel Set with CERES‐Maize

Crop Science, 2007
CERES‐Maize simulates kernel set as a source‐limited process based on average plant growth rate during the lag phase after flowering. Yet the number of kernels formed by maize (Zea mays L.) also depends on timely interaction between male and female flowers, which can limit formation of reproductive sinks under some conditions.
J. I. Lizaso, A. E. Fonseca, M. E. Westgate   +2 more
openaire   +1 more source