To examine whisker barrel evoked response potentials in chronically implanted rats during behavioral learning with very fast response times, rats must be calm while immobilized with their head restrained. We quantified their behaviors during training with an ethogram and measured each individual animals' progress over the training period. Once calm under restraint, rats were conditioned to differentiate between a reward and control whisker twitch, then provide a lick response when presented with the correct stimulus, rewarded by a drop of water. Rats produced the correct licking response (after reward whisker twitch), and learned not to lick after a control whisker was twitched. By implementing a high density 64 channel electrocorticogram (ECoG) electrode array, we mapped the barrel field of the somatosensory cortex with high spatial and temporal resolution during conditioned lick behaviors. In agreement with previous reports, we observe a larger evoked response after training, probably related to mechanisms of cortical plasticity.

Background and objectives In temperate rice growing regions, the application of nitrogen (N) fertilizer is often split into two applications to reduce the risk of cold‐induced sterility associated with high N uptake. This strategy involves a basal N application applied pre‐permanent water (PW) and the second application following panicle initiation (PI). Split N application generally increases crop yield, however, data describing the impact on grain quality are relatively sparse. The objective of this study was to determine the effect of the split N method on grain quality parameters. We analyzed grain quality under various pre‐PW and PI N rates. Findings N applied pre‐PW increased head rice yield (HRY; the percentage of grain that remains whole or at least 75% of the original length after milling) in all tested cultivars, however, the effect of splitting the same total N rate into two doses on HRY was cultivar specific. N rate applied pre‐PW also showed a positive and negative relationship with milled grain yellowness (b*) and brightness (L*), respectively. The effect of N on amylose content was cultivar specific. The changes in quality parameters through pre‐PW N application were associated with protein content. However, total protein content did not correlate as strongly with quality parameters in the split treatments compared with the single‐dose treatments. Analysis of protein composition revealed N rate and timing affected protein composition, which had significant impacts on quality parameters, and the effects were cultivar specific. Conclusion These results indicate altering the nutritional management of rice changes the protein composition affecting grain quality parameters. Significance and novelty This study demonstrates the importance of N rate and timing of application in regard to grain quality and the significant role protein composition plays in quality characteristics.

This study was carried out to examine the response of ‘Luiza’ apple to different storage atmospheres, durations, and chemical inhibition of ethylene action by 1-MCP. Analysis of fruit quality and physiological disorder incidence were performed every two months during eight months of storage for Exp. 1 and 2, and after eight months for Exp. 3. Both CA storage and 1-MCP treatment reduced fruit ethylene production and respiration and prevented the rapid fruit softening, flesh browning incidence and fungal decay of ‘Luiza’ apple. The combination of 1-MCP treatment before storage in CA provided an additional benefit in firmness retention after simulated marketing conditions at 22oC. Based on the time to reach a firmness of 53 N, the storage life of ‘Luiza’ apple is less than four months in air-storage and more than six months under CA-storage. ‘Luiza’ fruit did not develop symptoms of CO2 injury when stored under high CO2 partial pressures (up to 4.5 kPa). However, we observed increased flesh browning and fungal decay incidence for CA-stored fruit between six and eight months of storage. Therefore, the storage potential of ‘Luiza’ apple fruit may be limited to six months under CA-storage (1.5 kPa O2 and 2.5 kPa CO2).

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Background and objectives There are no published data on the effect of sowing rate on rice grain quality traits of medium‐ and short‐grain cultivars within the Australian environment. Studies that have reported on the impact of sowing rate on grain quality in other rice growing regions have assessed differences between densities below 100 plants/m2, which is the minimum target for Australian grown rice. Furthermore, the cultivars evaluated were long‐grain cultivars only. The effect of sowing rate (25–150 kg/ha) on the quality traits of a short (YRK5)‐ and medium (Viand)‐grain rice cultivar was investigated over two seasons. Nitrogen (N) application was included in the study as the appropriate combination of sowing and N rate for maximum yield for both cultivars was unknown. Findings Sowing and N rate affected the number of grains per panicle and plants established per m2 of both cultivars; however, changes in these parameters did not affect crop yield. The number of grains per panicle affected thousand‐grain weight (TGW) and head rice yield (HRY; the percentage of grain that remains whole or at least 75% of the original length after milling), and the response differed between cultivars. Decreasing sowing rate increased the number of grains per panicle, reduced grain length and TGW, and slightly increased HRY in Viand. In YRK5, decreased sowing rate increased TGW and in season two reduced HRY. Protein content was negatively correlated with TGW and positively correlated with HRY. There were no consistent differences in the physicochemical and cooking parameters between densities over both seasons in both cultivars. Conclusion These results indicate that plant density has an indirect effect on milling quality by influencing TGW, which affected total protein content, and thus, HRY and the response differ between cultivars. Furthermore, this study demonstrated that within a population of 18 to 231 plants/m2 at establishment, the physicochemical and cooking parameters are not affected by sowing rate. Significance and novelty This study is the first to analyze the grain physicochemical and cooking quality parameters at densities above 100 plants/m2 and evaluate the effect of sowing rate on the grain quality of differing grain types within Australia. Comparisons between the low (50–70 kg/ha) and standard sowing rate (130–150 kg/ha) revealed no difference in HRY, and these results are important to farmers and demonstrate a reduction in plant density due to poor establishment, environmental or bird damage does not affect crop yield or grain quality and thus their economic return.

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Crop yield dominates rice (Oryza sativa L.) industry research; however, it is grain quality that dictates the value and market acceptance of rice. Key parameters of rice grain quality include physical appearance, amenability to processing and the cooking and sensory properties. In Australia, rice farmers who do not meet defined high‐quality standards receive discounts to their payments. Consequently, even with high yields, poor grain quality can negatively impact grower returns. Despite the financial consequences, the quality of Australian grown rice is highly variable, because unfortunately, the underlying causes are poorly understood. The identification of genetic markers for specific traits largely dominates rice grain quality research, while research regarding the effect of crop management practices on grain quality is relatively sparse and generally lacks an Australian focus. Prior research that has assessed the effect of crop management practices on grain quality tends to focus primarily on milling quality and neglect the physicochemical and cooking properties. This review outlines the current state of knowledge of the role nutritional management, irrigation protocols, planting density, and the interaction with genotype and environment on rice grain quality. The review highlights the uniqueness of Australian management practices and that there is a need for future research to understand the impact of agronomic practices on rice grain quality in Australia. Understanding how each cultivar interacts with agronomic practices can help reduce the variability found within rice crops.

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