Flower or grain abortion causes large yield losses under water deficit. In maize (Zea mays), it is often attributed to a carbon limitation via the disruption of sucrose cleavage by cell wall invertases in developing ovaries. We have tested this hypothesis versus another linked to the expansive growth of ovaries and silks. We have measured, in silks and ovaries of well-watered or moderately droughted plants, the transcript abundances of genes involved in either tissue expansion or sugar metabolism, together with the concentrations and amounts of sugars, and with the activities of major enzymes of carbon metabolism. Photosynthesis and indicators of sugar export, measured during water deprivation, suggested sugar export maintained by the leaf. The first molecular changes occurred in silks rather than in ovaries and involved genes affecting expansive growth rather than sugar metabolism. Changes in the concentrations and amounts of sugars and in the activities of enzymes of sugar metabolism occurred in apical ovaries that eventually aborted, but probably after the switch to abortion of these ovaries. Hence, we propose that, under moderate water deficits corresponding to most European drought scenarios, changes in carbon metabolism during flowering time are a consequence rather than a cause of the beginning of ovary abortion. A carbondriven ovary abortion may occur later in the cycle in the case of carbon shortage or under very severe water deficits. These findings support the view that, until the end of silking, expansive growth of reproductive organs is the primary event leading to abortion, rather than a disruption of carbon metabolism.

The design of more sustainable cropping systems requires increasing N-input from symbiotic N 2 fixation (SNF). However, SNF can be inhibited by nitrate exposure (e.g., soil N-mineralization). Although the effect of nitrate on SNF has been extensively investigated at the cell scale, few studies have highlighted the impact of nitrate exposure on nodule number and biomass, nodule activity of the SNF apparatus or its ability to recover. Pea plants were grown in greenhouse conditions in a N-free nutrient solution and exposed to nitrate (5 mM NO 3 − L −1 ) for one week during either early vegetative growth, flowering or seed filling. After nitrate removal, the plants were grown either under natural light or shade. Nitrate exposure reduced the rate of nodule establishment during vegetative growth, whereas it caused damage to existing nodules when applied during the reproductive stages. Nitrate decreased the specific activity of nodules regardless of the stage of the exposure. After nitrate removal, an extra wave of nodulation was observed on plants grown under natural light but only when nitrate exposure occurred before the seed filling stage. The recovery of SNF activity after nitrate removal depended on the amount of carbon available to nodules.

Background: Characterizing plant genetic resources and their response to the environment through accurate measurement of relevant traits is crucial to genetics and breeding. The spatial organization of the maize ear provides insights into the response of grain yield to environmental conditions. Current automated methods for phenotyping the maize ear do not capture these spatial features. Results: We developed EARBOX, a low-cost, open-source system for automated phenotyping of maize ears. EARBOX integrates open-source technologies for both software and hardware that facilitate its deployment and improvement for specific research questions. The imaging platform consists of a customized box in which ears are repeatedly imaged as they rotate via motorized rollers. With deep learning based on convolutional neural networks, the image analysis algorithm uses a two-step procedure: ear-specific grain masks are first created and subsequently used to extract a range of trait data per ear, including ear shape and dimensions, the number of grains and their spatial organization, and the distribution of grain dimensions along the ear. The reliability of each trait was validated against ground-truth data from manual measurements. Moreover, EARBOX derives novel traits, inaccessible through conventional methods, especially the distribution of grain dimensions along grain cohorts, relevant for ear morphogenesis, and the distribution of abortion frequency along the ear, relevant for plant response to stress, especially soil water deficit. Conclusions: The proposed system provides robust and accurate measurements of maize ear traits including spatial features. Future developments include grain type and colour categorization. This method opens avenues for high-throughput genetic or functional studies in the context of plant adaptation to a changing environment.