Societal Impact Statement Therapeutic protein production in plants is an area of great potential for increasing and improving the production of proteins for the treatment or prevention of disease in humans and other animals. There are a number of key benefits of this technique for scientists and society, as well as regulatory challenges that need to be overcome by policymakers. Increased public understanding of the costs and benefits of therapeutic protein production in plants will be instrumental in increasing the acceptance, and thus the medical and veterinary impact, of this approach. Summary Therapeutic recombinant proteins are a powerful tool for combating many diseases which have previously been hard to treat. The most utilized expression systems are Chinese Hamster Ovary cells and Escherichia coli, but all available expression systems have strengths and weaknesses regarding development time, cost, protein size, yield, growth conditions, posttranslational modifications and regulatory approval. The plant industry is well established and growing and harvesting crops is easy and affordable using current infrastructure. Growth conditions are generally simple: sunlight, water, and the addition of cheap, available fertilizers. There are multiple options for plant expression systems, including species, genetic constructs and protein targeting, each best suited to a particular type of therapeutic protein production. Transient expression systems provide a mechanism to rapidly transfect plants and produce therapeutic protein in a matter of weeks, rather than the months it can take for many competing expression systems, while proteins targeted to cereal seeds can be harvested, stored and potentially purified much more easily than in competing systems. Current challenges for plant expression systems include a lack of regulatory approval, environmental containment concerns and nonhuman glycosylation, which may limit the scope of the type of therapeutic proteins that can be manufactured in plants. The specific strengths of plant expression systems could facilitate the production of certain therapeutic proteins quickly and cheaply in the near future.

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Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. We provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

Understanding how carbon source and sink strengths limit plant growth is a critical knowledge gap that hinders efforts to maximize crop yield. We investigated how differences in growth rate arise from source–sink limitations, using a model system comparing a fast‐growing domesticated annual barley (Hordeum vulgare cv. NFC Tipple) with a slow‐growing wild perennial relative (Hordeum bulbosum). Source strength was manipulated by growing plants at sub‐ambient and elevated CO2 concentrations ([CO2]). Limitations on vegetative growth imposed by source and sink were diagnosed by measuring relative growth rate, developmental plasticity, photosynthesis and major carbon and nitrogen metabolite pools. Growth was sink limited in the annual but source limited in the perennial. RGR and carbon acquisition were higher in the annual, but photosynthesis responded weakly to elevated [CO2] indicating that source strength was near maximal at current [CO2]. In contrast, photosynthetic rate and sink development responded strongly to elevated [CO2] in the perennial, indicating significant source limitation. Sink limitation was avoided in the perennial by high sink plasticity: a marked increase in tillering and root:shoot ratio at elevated [CO2], and lower non‐structural carbohydrate accumulation. Alleviating sink limitation during vegetative development could be important for maximizing growth of elite cereals under future elevated [CO2].

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