SUMMARY: Successful crop production depends initially on the availability of high-quality seed. By 2050 global climate change will have influenced crop yields, but will these changes affect seed quality? The present review examines the effects of elevated carbon dioxide (CO₂) and temperature during seed production on three seed quality components: seed mass, germination and seed vigour.In response to elevated CO₂, seed mass has been reported to both increase and decrease in C₃plants, but not change in C₄plants. Increases are greater in legumes than non-legumes, and there is considerable variation among species. Seed mass increases may result in a decrease of seed nitrogen (N) concentration in non-legumes. Increasing temperature may decrease seed mass because of an accelerated growth rate and reduced seed filling duration, but lower seed mass does not necessarily reduce seed germination or vigour.Like seed mass, reported seed germination responses to elevated CO₂have been variable. The reported changes in seed C/N ratio can decrease seed protein content which may eventually lead to reduced viability. Conversely, increased ethylene production may stimulate germination in some species. High-temperature stress before developing seeds reach physiological maturity (PM) can reduce germination by inhibiting the ability of the plant to supply the assimilates necessary to synthesize the storage compounds required for germination.Nothing is known concerning the effects of elevated CO₂on seed vigour. However, seed vigour can be reduced by high-temperature stress both before and after PM. High temperatures induce or increase the physiological deterioration of seeds. Limited evidence suggests that only short periods of high-temperature stress at critical seed development stages are required to reduce seed vigour, but further research is required.The predicted environmental changes will lead to losses of seed quality, particularly for seed vigour and possibly germination. The seed industry will need to consider management changes to minimize the risk of this occurring.

Multispectral imaging is a new technology that is being deployed to assess seed quality parameters. Examples of applications in the detection and identification of fungi on seeds are presented, together with an example of the technology used for maturity determination in sugar beet seed. Results from multispectral imaging are compared with reference methods, and a high correlation is found. Applications of the technique for varietal discrimination and insect damage are also presented. There is a need for non-destructive, reliable and fast techniques, and it is concluded that multispectral imaging has potential for seed quality assessment, in particular for those components associated with surface structure and chemical composition, seed colour, morphology and size.

Seed health tests are time consuming and require substantial training for characterization of pathogenic fungi on seed. A new approach to use a multispectral vision system for identifying surface properties of different fungal infections has been tested in spinach (Spinacia oleracea L.) at Aarhus University. Our study demonstrates that multispectral imaging with wavelengths ranging from 395-970 nm can be used to distinguish between uninfected spinach seeds and seeds infected with Verticillium spp., Fusarium spp., Stemphylium botryosum, Cladosporium spp. and Alternaria alternata. Analytical separation based on mean pixel intensity, Canonical Discriminant Analysis (CDA) and classification by Jeffries-Matusita (JM) distance illustrates that a combination of Near Infrared spectra (NIR) and Visual spectra (VIS) is able to identify uninfected seeds from infected seeds ranging from 80-100%. Classification using only NIR gave a separation of 26-88% between uninfected and Fusarium spp. infected seeds. Alternaria alternata and Fusarium spp. could be distinguished from each other and from Cladosporium spp., Verticillium spp. and Stemphylium spp. Separation of Cladosporium spp., Verticillium spp. and Stemphylium spp. needs further development before practical application.

The purpose of this study was to highlight the use of multispectral imaging in seed quality testing of castor seeds. Visually, 120 seeds were divided into three classes: yellow, grey and black seeds. Thereafter, images at 19 different wavelengths ranging from 375–970 nm were captured of all the seeds. Mean intensity for each single seed was extracted from the images, and a significant difference between the three colour classes was observed, with the best separation in the near-infrared wavelengths. A specified feature (RegionMSI mean) based on normalized canonical discriminant analysis, were employed and viable seeds were distinguished from dead seeds with 92% accuracy. The same model was tested on a validation set of seeds. These seeds were divided into two groups depending on germination ability, 241 were predicted as viable and expected to germinate and 59 were predicted as dead or non-germinated seeds. This validation of the model resulted in 96% correct classification of the seeds. The results illustrate how multispectral imaging technology can be employed for prediction of viable castor seeds, based on seed coat colour.