Field Crops Research

SCIENTIFIC NOVELTY

Field Crops Research is an international journal publishing scientific articles on:

√ Original experimental and modelling research, meta-analysis of published data.
√ Articles must demonstrate new scientific insights, original technologies or novel methods at crop, field, farm and landscape levels.

FOCUS and SCOPE

The focus of Field Crops Research is crop ecology, crop physiology, agronomy, and crop improvement of field crops for food, fibre, feed and biofuel.
The inclusion of yield data is encouraged to demonstrate how the field experiments contribute to the understanding of the bio-physical processes related to crop growth, development and the formation and realisation of yield.
Articles on quality (grain, fibre, fodder), breeding and genetics, crop protection (diseases, pests, weeds), phenotyping, remote and non-contact sensing, soils, climate and greenhouse gas emissions, are encouraged, provided they are integrated with crop ecology, crop physiology, crop improvement and/or agronomy.
Articles containing new insights into resource-use efficiency, crop intensification, precision and digital agriculture, climate smart practices and molecular and/or physiological breeding are welcome.
Studies at lower levels of organisation (plant to molecular) must demonstrate scaling up to crop level or higher.

SCIENTIFIC and PRESENTATION STANDARD

• Manuscripts must be written in grammatically sound English.

• Objectives must flow from complete, brief, unbiased and updated review of the literature.

• Experimental design must match objectives.

• Field experiments must be repeated in at least two seasons or locations.

• Key agronomic practices and environmental conditions (soil, weather) must be detailed, and weather information should be shown in relation to crop phenology.

• Data must be analysed with appropriate statistics, and results have to be concise and address objectives.

• A separate discussion must not repeat results but place findings in agronomic context with conclusions fully justified by data.

OUT of SCOPE