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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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Suggested Citation:"2 Crops." National Academies of Sciences, Engineering, and Medicine. 2018. Science Breakthroughs to Advance Food and Agricultural Research by 2030. Washington, DC: The National Academies Press. doi: 10.17226/25059.
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2 Crops 1. INTRODUCTION Crop agriculture is one of America’s success stories. U.S. farmers produce 34.1 percent of the world’s soybeans, 35.5 percent of the world’s corn, 13.4 percent of the world’s cotton, and 7.6 percent of the world’s wheat (USDA-FAS, 2018b). Crop production accounts for approximately $194 billion per year in agricultural cash receipts. (USDA-ERS, 2018). In 2016, agricultural domestic exports of crops reached $108 billion ($21 billion in soybeans alone) and created an estimated $171.3 billion in additional economic activity (USTR, 2017; USDA-FAS, 2018a). Yields of major staple crops grown in the United States are the highest or near to the highest in the world. Since the 1930s, yields of corn have increased more than eightfold, while soybean and cotton yields have increased more than fourfold, due primarily to advances in plant breeding, as well as fertilizer use and equipment efficiency, among other innovations (Fernandez-Cornejo, 2004; Nielsen, 2017). Despite succes- sive years of weather disasters, the yield performance of America’s premier crops are a remarkable testa- ment to the resilience and success of the varieties commercially available today (see Figure 2-1). FIGURE 2-1 Yield trends for corn in the United States from 1866-2015. SOURCE: Nielsen, 2017. 22 Prepublication Copy

Crops With increased support for public sector agricultural research and public-private partnerships, it will be possible to bring the breeding success in corn to many other crops (such as cover crops, fruits and veg- etables, and bioenergy crops) at a much faster pace than is currently possible. Moreover, these efforts can be used to “harden” crops against the effects of extreme weather and increased pest and disease pressure while maximizing yield and increasing nutritional content and flavor. These efforts can also be used to enhance other crop characteristics, such as those that will reduce the need for costly inputs. As stationary organisms, plants exhibit enormous plasticity in the face of adverse and extreme environments. Through the process of natural selection, plant communities adapt to local conditions and provide for their suste- nance by interacting with their environments both below- and above-ground. Plants have evolved to grow and thrive in almost all environments on this planet—from lands with virtually no water to lands that flood routinely, and in all temperature extremes. This evolutionary pressure has given rise to the incredi- ble genetic diversity of plant life that, when coupled with new gene-editing technologies, offers exciting new avenues for solving some of the big challenges facing crop production today. Other chapters in this report will address soil, fertilizer use (Chapter 5), and water (Chapter 6), prop- er management of which are critical for sustainable, environmentally responsible crop production. There is a pressing need for changes in agronomic practices that improve the stewardship of natural resources and decrease the environmental impacts of crop production. The focus of this chapter is on the crop toolbox and how crop germplasm can be developed over the next two decades—efforts that can be pur- sued in conjunction with agronomy and crop science to facilitate increased diversity and greater flexibility in cropping systems. The domestication of wild plant species suited to different environments, has com- mercial value in crop rotations, and can serve as habitats for beneficial insects, with the potential to ex- pand options for crop management. Similarly, the genetic tools are rapidly becoming available to endow current cultivars with traits that minimize the need for inputs (e.g., water, nitrogen, phosphate, pesticides, and fungicides), maximize yield in changing environments/climatic extremes, resist diseases and pests, and provide improved nutrition, among other characteristics. 2. CHALLENGES It is no longer safe to assume that U.S. crop production is in a self-sustaining, steady state. First and foremost, the natural resource base for U.S. agriculture is recognized as increasingly fragile. Groundwater and fertile soil are finite resources, and their use and misuse define the boundaries of sustainable produc- tion in the long term (Rockström et al., 2017). Aquifers supporting the majority of U.S. production are being drained (Konikow, 2013; Steward et al., 2013), and soil quality in some parts of the country is de- grading (Baumhardt et al., 2015). These developments set the stage for lower productivity and the need for crops that can perform well in less than optimal environments. Second, crop systems are also stressed by changing weather patterns and extreme weather events (Walthall et al., 2012). Prolonged drought over the last decade (Diffenbaugh et al., 2015; Howitt et al., 2015) and flooding more recently (Mallakpour and Villarini, 2015) have been responsible for the largest proportion of U.S. crop disaster payments from abiotic and biotic stresses (Figure 2-2). The need for crops that are resilient to multiple abiotic stresses, such as drought and flooding, will be a challenging problem for breeders over the next decade. There are success stories in addressing some of the challenges, such as the development of flood-tolerant varieties of rice via introduction of the SUB1A gene into mod- ern cultivars (Bailey-Serres et al., 2012; see Box 2-1). Third, biotic challenges to crops including pests and diseases are an increasing threat due to agricul- tural intensification, expanding global trade, and extreme weather. A recent example is Huanglongbing (HLB), also known as citrus greening disease. HLB was detected in Asia more than 100 years ago and was first seen in the United States in Florida orchards in 2005. Within 3 years the vector-transmitted bac- terial pathogen spread to the majority of citrus orchards in Florida, leading to losses of more than a billion dollars annually (Court et al., 2017). There is no known cure for HLB, which kills trees in 3-5 years and has now spread to California, Georgia, Hawaii, Louisiana, South Carolina, and Texas (NASEM, 2018). Prepublication Copy 23

Science Breakthroughs to Advance Food and Agricultural Research by 2030 FIGURE 2-2 Percentage of total annual crop losses due to different environmental stresses. SOURCE: USDA Risk Management Agency Cause of Loss Historical Data. BOX 2-1 All Major Crops Except Rice Are Flooding Intolerant The introduction of a gene called SUB1A from an Indian farmer’s rice variety into modern rice cul- tivars proved sufficient to increase tolerance of full submergence to 2 weeks or more. SUB1A rice va- rieties bred using selection with molecular markers are now grown by millions of farmers. Rice sur- vives root waterlogging because of traits that enable gases to be exchanged between the root and shoot. In the United States, extreme rains cause prolonged waterlogging of the root systems of soy- bean, maize, wheat, and other crops, resulting in over a billion dollars in crop loss per year. The im- provement of crop flooding resilience might be accomplished through breeding, genetic engineering, or other strategies. The genetic loci of crops or their relatives that enhance waterlogging tolerance can be recognized through advanced phenotyping and mapping of diverse germplasm. But because a plant may experience both flooding and drought during its life cycle, it is critical to combine resilience to both extremes of water availability in a single seed (Bailey-Serres et al., 2012). In another example, rising temperatures are leading to migrations of insect pests to higher elevations, while greater intensification is leading to more rapid evolution and spread of diseases (Katsaruware-Chapoto et al., 2017). Direct yield losses caused by pathogens and pests are predicted to lower global agricultural productivity in the future by 20 to 40 percent (Savary et al., 2012; Baltes et al., 2017). Some natural threats to crop production have been made worse by management practices, such as the emergence of herbicide resistant weeds following overuse of a single herbicide (e.g., glyphosate) to control weeds. Improved resistance management practices can reduce input costs, improve yields, and increase returns (Livingston et al., 2015). There is a deep sense of urgency and of opportunity to speed up and expand the power of crop im- provement to address these challenges. As previously mentioned, global food production will need to in- crease by at least 50 percent by 2030 to feed a growing global population (UN DESA, 2017). However, 24 Prepublication Copy

Crops the current pace of yield growth worldwide may not be sufficient to meet the predicted need for 2030 and beyond (Ray et al., 2012), and there are even signs that the rate of yield increase in many crops is begin- ning to plateau (Wei et al., 2015; Andersen et al., 2018). The question of why yield growth is slowing has yet to be answered, with speculation ranging from the decline in agricultural research for basic crop im- provement (Pardey and Beddow, 2013; Andersen, 2015); temperature and other effects of climate change (Lobell and Field, 2007); or that some crops are nearing their biological yield potential (Evans and Fisch- er, 1999; Alston et al., 2009; Ort et al., 2015). 3. OPPORTUNITIES 3.1 Gene-Editing Systems The discovery of gene-editing systems (such as CRISPR-Cas9) has revolutionized our ability to both understand and genetically modify both plants and animals (Yin et al., 2017). For crops, new alleles can be generated and introduced directly into a cultivar of choice, leaping over the time-consuming process of making multiple crosses to combine desirable traits in the progeny. Gene editing creates the potential to identify and implement new traits in the field on a much faster timescale. Traditional plant breeding is slow and tedious as it can only exploit the limited quantitative trait alleles found in wild relatives, and then it can take between 7-12 years to utilize conventional methods to develop a new cultivar (Baenziger et al., 2006). The ability to fine-tune the expression of a quantitative trait locus rather than utilizing only what is available in wild relatives has already shown promise as a way to increase yield. For example, researchers edited genes in three pathways that contribute to productivity in tomato—plant architecture, fruit size, and inflorescence—to rapidly produce alleles that alter their promoters. The resultant plants displayed a series of previously unobserved phenotypes, including several with increased yield (Rodríguez-Leal et al., 2017). Gene editing has now opened the door for quickly exploring additional changes. Box 2-2 describes a success story of a transgenic approach used in the quest to turn a C3 plant (such as rice) into a C4 plant (such as maize). Gene editing also offers the ability to eliminate linkage drag, a problem that has plagued crop breeding since its inception. Linkage drag occurs when undesirable traits are linked to, and therefore inherited with, desirable traits (Giovannoni, 2018; Zhu et al., 2018b). Using a variety of genomic and as- sociated approaches to characterize a large tomato diversity population, Zhu and colleagues (2018b) were able to “see” the genomic outcomes of tomato domestication, many of which are undesirable. Knowledge of these so-called “hitchhiking genes” is a necessary first step toward their eventual modification or elim- ination by gene editing methodologies. BOX 2-2 Successful Engineering of Photosynthesis Photosynthesis is the engine for life on Earth, yet the efficiency of solar energy conversion is rela- tively low. As such, it has high engineering potential (Schuler et al., 2016). There is a large interna- tional effort taking many different approaches to improve photosynthetic efficiency, including optimiz- ing canopies, relaxing photoprotection and bypassing photorespiration (Ort et al., 2015). Converting a C3 plant into a C4 plant that is much more efficient at converting sunlight is another effort underway to increase photosynthetic efficiency (Long, 2015; Ort et al., 2015). Using constitutive expression of the maize GOLDEN2-LIKE gene, researchers have now shown that they can confer a set of C4-like traits on C3 rice (Wang et al., 2017). These traits include the accumulation of photosynthetic enzymes and more interconnections between cells. Another exciting direction for increasing photosynthetic efficien- cy is to expand the spectral range for photosynthesis by allowing plants to absorb far-red light (Blakenship and Chen, 2013). The “first” Green Revolution improved yield potential but did so without improving solar energy conversion, making improvement of photosynthesis the basis for a second green revolution. Prepublication Copy 25

Science Breakthroughs to Advance Food and Agricultural Research by 2030 3.2 Development of Dynamic Crops Agriculture could benefit from crops that provide farmers with the flexibility to change their crop’s physiology in response to unexpected environments. Park and colleagues (2015) designed such a crop whose water use can be controlled by chemical application (see Box 2-3). An even greater advancement would involve developing crops that can respond in real time to environmental changes (e.g., drought, floods, temperature extremes) as well as to the appearance of disease organisms and pests. Given the ina- bility to reliably predict the conditions that any particular crop may face over the growing season com- bined with more extreme weather events predicted over the long term (Walthall et al., 2012), dynamic crops could better respond to such events and become an asset for enhancing food security. 3.3 Mining Plant Diversity Traditionally, the traits to overcome the many challenges previously noted have come from wild rel- atives. Although gene editing can eliminate the laborious introgression of traits (at least for crops for which those traits can be successfully introduced; see discussion of transformation later in this chapter), there is a vast array of plant species whose agricultural potential remains untapped (see Box 2-4). There are more than 50,000 edible plants, but only 15 crops are used to meet 90 percent of the world’s energy demands, and three commodity crops (rice, maize, and wheat) account for two-thirds of human caloric intake (Gruver, 2017). Additionally, more than 70 percent of wild relatives of domesticated crops are in urgent need of conservation, and are ironically threatened by the expansion of agriculture into natural ecosystems (Castañeda Alvarez et al., 2016). Around the world, gene banks and botanical gardens hold more than 7.4 million seeds or plant issues from thousands of species (Gruber, 2017). These collections need to be maintained, curated, and explored. BOX 2-3 Synthetic Biology for Dynamic Crops An ongoing focus of plant breeding is to create drought-tolerant plants, but the drought protective response in plants is often associated with “yield drag” (Yang et al., 2010). Recent work has demon- strated that it may be possible to alter a plant’s use of water dynamically, essentially turning the de- mand for water on or off when needed. By genetically engineering the abscisic acid (ABA) protein re- ceptor that naturally plays a role in controlling plant water use to bind to a synthetic agrochemical, it was possible to control the plant’s drought protection response (Park et al., 2015). When tomato plants containing the engineered ABA were sprayed with the chemical, they used less water. The system is ready for real-world testing, suggesting that uses of synthetic biology of this type could be a near-term goal. Many aspects of plant physiology should be amenable to this approach, which could help usher in a more responsive agriculture. BOX 2-4 Pichuberry: A Crop for Rapid Domestication Cape gooseberry or pichuberry (Physalis peruviana) is native to the Andean region of South Ameri- ca. It is highly nutritious and can be eaten as fresh fruit or can be used to make juice or jam. It is gain- ing in popularity but it has a number of “wild” characteristics that prevent it from being easily cultivated. Knowledge of the genes related to the improvement and domestication of the tomato, a distant relative of P. peruviana, is motivating scientists to identify similar genes in the undomesticated pichuberry that could be targeted for domestication. Gene editing of P. peruviana’s genetic ortholog of the tomato gene CLAVATA1 (SlCLV1)—which controls meristem proliferation gave rise to plants with narrow leaves and flowers with more organs—offers proof of principle of rapid, targeted domestication using gene editing (Van Eck et al., 2017). 26 Prepublication Copy

Crops 3.4 Taking Advantage of Plant–Microbe Interactions Billions of microorganisms and macroorganisms (from viruses to nematodes) live on, inside, and near plants, both above- and below-ground (Leach et al., 2017). Beneficial plant–microbe interactions include direct stimulation of plant growth, protection of plants from pathogens and insect pests through direct production of toxins, or through induced resistance in the plant, and, improvement of resilience to environmental stress (e.g., drought, salinity) (Parnell et al., 2016; Finkel et al., 2017). Beneficial inter- actions can occur in the root zone (rhizosphere), on leaf surfaces (phyllosphere), and in internal tissues (endosphere) (APS, 2016). The greatest density and diversity of microbial life associated with plants occurs in the soil, in the rhizosphere. In leguminous plants, some species of bacteria (Rhizobium) induce the formation of root nodules in a symbiotic relationship that converts atmospheric and largely inert N2 into ammonia (NH3) and other molecular precursors that the plant uses in the biosynthesis of nucleotides, coenzymes, and amino acids. In many more species of plants, fungal symbionts (called arbuscular mycorrhizal fungi) form hyphae that increase the ability of plant roots to access minerals (particularly phosphorus) and water (Leach et al., 2017). It has been proposed that an opportunity lies in domesticating or improving specific plant-associated microbial communities to use them as soil or seed inoculants to improve plant growth (Parnell et al., 2016). The characterization of microbial communities in concert with plants, which often cannot be cul- tured outside the plant environment, has been enabled by high-throughput gene sequencing of community DNA (metagenomics) and RNA (metatranscriptomics) (Schlatter et al., 2015; Nesme et al., 2016). In ad- dition, progress has been made at the intersection of miniaturized microfluidics and imaging that permits real-time monitoring of root interactions with microbial species (Massalha et al., 2017). Based on knowledge gained from these technologies, a future opportunity is using synthetic biology tools to design plant–microbe associations that improve crop productivity. Such associations can be ap- proached by using gene editing in plants, microbes, or both. For example, plant genes controlling nodule formation by nitrogen-fixing rhizobacteria might be expanded to non-legume crops to reduce the need for fertilizer application, and microbial consortia present in the root zone could be engineered to produce novel plant growth promoters or protectants (Ahkami et al., 2017). 3.5 Making Food More Nutritious Relatively little breeding effort has gone into making staple crops as better sources of vitamins and minerals. More than 2 billion people suffer from micronutrient deficiencies because their plant-based di- ets do not provide sufficient nutrition. Factors that drive the modern food system include consistency, predictability, low cost, and high-edible yield; but the nutritional value of food produced for direct human consumption has not been a priority of the market (Dwivedi et al., 2017). There have been concerted ef- forts to survey cultivars for natural variation in levels of select nutrients. For example, a recent study ex- amined vitamin E levels in maize grain and determined that only two loci are responsible for most of the variation (Diepenbrock et al., 2017). This discovery suggests that targeting these loci in any number of crops may increase vitamin E content. There has also been some success using transgenic approaches to increase nutritional content. For example, biofortified rice that meets dietary targets for iron and zinc and has no yield penalty in the field is a major breakthrough in this area (Trijatmiko et al., 2016). There are also opportunities to increase levels of important phytonutrients that have health benefits, such as poly- phenols and carotenoids (Martin and Li, 2017; Yu and Tian, 2017). Unfortunately, breeding almost exclusively for increased yield has made some crops less nutritious. For example, the concentrations of iron, zinc and selenium in wheat have dropped by 28 percent, 25 per- cent, and 18 percent respectively, all in the period between 1920 and 2000 (Gruber, 2016). Such decreases are thought to be a dilution effect as improvements in the amount of fixed carbon have been made without a proportional increase in mineral content (Marles, 2017). This results in lower mineral concentrations when expressed on a dry weight basis. Furthermore, recent studies are projecting that levels of levels of Prepublication Copy 27

Science Breakthroughs to Advance Food and Agricultural Research by 2030 zinc and iron in grains and legumes will continue to decline as CO2 levels continue to rise (Myers et al., 2014; Zhu et al., 2018a). Because most of the world relies on plants as their dietary source of these mi- cronutrients, such decreases are a cause for concern. A key scientific question is whether these declines in micronutrients can be reversed with changes in plant traits. Therefore, more attention needs to be paid to the unintended consequences of breeding exclusively for yield. 3.6 Optimizing Crop Production Systems The gap between actual yield and yield potential can be accounted for by several sources of variance including genetics (G), environment (E), management practices (M), and socioeconomic factors (S). Nu- merous enabling technologies can be implemented in crop production systems to achieve both resilience and sustainability and to enable crop yields to reach their full potential. These include the use of precision agriculture to manage water and fertilizer use, and the use of data science to integrate information from field- and plant-based sensors and weather prediction parameters (for a more complete discussion, see Chapter 5, section 3.1 “Leveraging Advances in Microelectronics, Sensing, and Modeling” and Chapter 6 “Water-Use Efficiency and Productivity in Agriculture”). Breakthroughs in genomics, nanotechnology, and robotics along with improvements in computational, statistical, and modeling capabilities will make it possible for scientists and producers to make well informed, data-driven decisions. For example, as dis- cussed in Chapter 7, development of high-throughput automated phenotyping capabilities can speed the process of breeding via the use of artificial intelligence and machine learning. However, in order to suc- cessfully model, manage, and predict crop production in any given location, better information is also needed on how different cropping management systems (e.g., use of cover crops, crop rotation) influence soil properties such as water storage capacity and nutrient availability. The emerging field of plant nanobiotechnology promises transformative solutions for nondestructive monitoring of plant signaling pathways and metabolism (Kwak et al., 2017). This can increase plant toler- ance (e.g., drought, disease, and soil nutrient deficiencies [Elmer and White, 2016; Wu et al., 2017]), alter photosynthesis (Giraldo et al., 2014), and enable plants to communicate their biochemical status (Wong et al., 2017). These discoveries will lead to the creation of “smart” plants that are more resilient to climate- induced stresses. Better understanding of the fundamental biophysical processes controlling nanomaterial- plant interactions will enable delivery of nanomaterials to precise locations in plants where they are needed to be active. The continuous real-time monitoring of plant heat status and the ability to combine these nano- enabled technologies with wireless soil sensors and automated water and nutrient delivery systems can lead to more precise delivery of nutrients and water, leading to more efficient use of inputs and greater yields. To ensure that all aspects of GEMS are addressed in a comprehensive manner, there is an opportuni- ty to assemble teams (including geneticists, soil scientists, agronomists, plant pathologists, and entomolo- gists) to work together to evaluate the response of different crop genotypes to environmental stresses and crop management practices (Hatfield and Walthall, 2015), and to factor in socioeconomic issues such as costs, access to small growers, and technology adoption. Such a systems approach can help to identify the optimum combination of G M S for current and anticipated E. 3.8 Controlled Environment Agriculture (CEA) Controlled environment agriculture1 (CEA) offers systems-level opportunities to increase the sus- tainability of some crops (e.g., fruits, vegetables, herbs) by providing resource-efficient farming systems 1 Controlled environment agriculture includes indoor production systems that range from low-technology covers for field crops to highly automated greenhouses, vertical farms, and recirculating aquaculture systems (RASs). The latter use the latest advances in hydroponics or aquaponics to increase productivity and improve water- and nutrient- use efficiencies. For example, RAS is coupled with hydroponic plant production by using waste derived from fish production as fertilizer for plant growth (Badiola et al., 2018; Palm et al., 2018). 28 Prepublication Copy

Crops with respect to water and nutrient use. CEA can close the loop on nitrogen and phosphorus use (Thomaier et al., 2015), reduce food miles (Weber and Matthews, 2008; Cleveland et al., 2011; Nicholson et al., 2015), and lower water exports from water-poor regions to water-rich regions. Locating food production in urban areas could also help to lower food waste by decreasing the amount of time from harvest to con- sumption. CEA can also address important food safety issues such as E. coli outbreaks (CDC, 2018). CEA can provide year-long growing seasons and protection against pests and diseases. Genetic approach- es described in this chapter can be used to provide traits to plants to make them suitable for growth in CEA. The importance of CEA for improving water-use efficiency is discussed in Chapter 6. 4. GAPS There is growing excitement in the plant sciences and breeding communities that we are on the cusp of a second green revolution. While the first green revolution was facilitated by the introduction of genes from other varieties and wild relatives, this second revolution will be fueled by basic research discoveries with model organisms and analyses of massive data sets that will combine to identify genes and regulato- ry sequences for targeted editing. However, the following gaps in knowledge and capabilities will have to be addressed before these technologies can be applied to a diversity of crops. 1. Knowledge of the genetic basis of the phenotypes and of allelic variants. Although the func- tions of many plant genes are known from studies in the major model plants, such as Arabidop- sis, there is a lack of basic knowledge of the genetic basis of many traits in crop species. It logi- cally follows that understanding gene function is necessary for the use of gene editing to create desirable traits. However, a gene-editing approach can be used as a discovery tool to knock out genes in crop plants to better understand their functional roles. Additionally, because the preci- sion of gene editing permits the modification of as little as a single base pair in the genome, it can be used to create allelic variants, essentially producing a library of diverse forms of the same gene, with which to explore function and phenotype. 2. Phenotyping: Connecting genomic variation with phenotypic impact. Identification of agricul- turally desirable traits will require the design and construction of above- and below-ground phe- notyping facilities and the development of data science that can correlate phenotype to genotype from vast visual, physiological, and “omics” resources. There is a need to increase the speed to characterize phenotype, to use new technologies that include overhead imaging (e.g., photo from a drone) and underground imaging to detect morphologies and traits, including chemical exu- dates (Das et al., 2015; Shi et al., 2016). 3. Ability to improve transformation efficiency of more plant species. Gene editing requires an ability to introduce DNA into plant tissue (called genetic transformation) and, in most cases, re- generate the tissues into transformed plants. Unfortunately, despite substantial progress in se- quencing, assembling, and annotating genomes from a vast array of plant species, significant bottlenecks exist in the successful genetic transformation of most crops. Research is needed to improve plant cell and tissue culture, identify better methods of introducing genetic material, and modulate the plant development pathway to improve the receptivity, stability, and regrowth of the transformed tissue (Altpeter et al., 2016). Studies of how plants regenerate themselves from cuttings or after injury, for example, have begun to provide insight into the genetic net- work that controls cellular proliferation and reprogramming. Such insights could lead to better methods to increase the chances of growing whole plants from transformed cells and tissues (Ikeuchi et al., 2018). A second green revolution powered by gene editing will not be possible unless facile transformation protocols are developed for use on any strain of any crop in any la- boratory. Similarly, the inability to transform wild plant species will prevent the use of gene ed- iting to accelerate their domestication. 4. Workforce, education, and training (and funding). Advances arising out of basic science and technology remain relatively new and underexploited for germplasm improvement for most Prepublication Copy 29

Science Breakthroughs to Advance Food and Agricultural Research by 2030 crops. This is due in part to the relatively small community of plant scientists educated to use science and technology, and the limited public and private investments for plant trait discovery and for translating such knowledge to enable crop discoveries. Investment would be necessary to maintain a pipeline of investigators who can push the limits of scientific inquiry and train the next generation of advanced plant scientists (USDA, 2015). 5. RECOMMENDATIONS FOR NEXT STEPS Despite steady decreases in the funding of both basic and applied crop science research, U.S. scien- tists have continued to innovate and make cutting edge discoveries. However, without sufficient support, U.S. plant scientists are likely to fall behind their counterparts in other countries in fully realizing gene editing as both a basic discovery and crop improvement tool. Since 2009, plant science funding in China has quadrupled and is supported with infrastructure, eclipsing the U.S. investment. Notable advancements in all aspects of plant science have been forthcoming from the Chinese (Chong and Xu, 2014). Recogniz- ing that food security and international competitiveness are critical components of national security, the following steps are recommended to secure U.S. leadership in crop improvement: 1. Continue to genetically dissect and then introduce desirable traits (increased photosynthet- ic efficiency; drought and flood tolerance; temperature extremes tolerance; disease and pest resistance; improved taste, aroma, and nutrition) and remove undesirable traits from crop plants through the use of both traditional genetic approaches and targeted gene edit- ing. The goal will be to: a. expand the number of alleles of known breeding improvement genes from what have been in- trogressed from wild relatives; b. engineer belowground and aboveground plant architecture, by obtaining and applying basic knowledge of plant root, shoot, and influorescence development; c. modify the plant microbiome to enhance desirable crop traits, including resistance to disease and increased nutrient-use efficiency; and d. remove undesirable traits (due to negative epistasis) that are tightly linked to alleles selected during domestication. 2. Enable routine genome modification of all crop plants through the development of facile transformation and regeneration technologies. Achieving this goal will require research into improved plant cell and tissue culture, better methods of introducing genetic material, and the ability to modulate plant development to improve the regeneration of the transformed tissue into whole plants. It will also require development of facilities for more rapid phenotype detection and analysis under different environmental (soil, climate, moisture) conditions and management regimes. 3. Monitor plant stress and nutrients through the development of novel sensing technologies, and allow plants to better respond to environmental challenges (heat, drought, flood, pests, nutrient requirements) by exploring the use of nanotechnology, synthetic biology, and the plant microbiome to develop dynamic crops that can turn certain functions on or off only when needed. Developing dynamic crops will require complementary approaches to gene edit- ing, including harnessing beneficial plant-root-soil microbe interactions to enhance desirable crop traits (such as drought resistance, disease resistance, and nutrient-use efficiency), using novel sensing technologies to sense plant nutrient status and stress, and using nanotechnologies for delivering nutrients and managing plant stress. Using the genetic diversity of plant and microbial life available together with new molecular and other tools are key for unlocking many opportunities for crop improvement. The process of prioritizing the most important opportunity to pursue would be best informed by thoughtful analyses of the targeted crops and their prospective new traits from a systems perspective, as described in Chapter 9. This includes 30 Prepublication Copy

Crops envisioning their performance and impact in the context of the agro-ecological system interfacing with humans and socio-economic considerations that play a role. REFERENCES Ahkami, A. H., R. A. White III, P. P. Handakumbura, and C. Jansson. 2017. Rhizosphere engineering: Enhancing sustainable plant ecosystem productivity. Rhizosphere 3(2):233-243. Altpeter, F., N. M. Springer, L. E. Bartley, A. E. Blechl, T. P. Brutnell, V. Citovsky, L. J. Conrad, S. B. Gelvin, D. P. Jackson, A. P. Kausch, P. G. Lemaux, J. I. Medford, M. L. Orozco-Cárdenas, D. M. Tricoli, J. Van Eck, D. F. Voytas, V. Walbot, K. Wang, Z. J. Zhang, C. N. Stewart 2016. Advancing crop transformation in the era of genome editing. Plant Cell 28(7):1510-1520. Alston, J. M., J. M. Beddow, and P. G. Pardey. 2009. Agricultural research, productivity, and food prices in the long run. Science 325(5945):1209-1210. Andersen, M. A. 2015. Public investment in U.S. agricultural R&D and the economic benefits. Food Policy 51: 38- 43. Available at https://doi.org/10.1016/j.foodpol.2014.12.005 (accessed May 8, 2018). Andersen, M. A., J. M. Alston, P. G. Pardey, and A. Smith. 2018. A century of U.S. farm productivity growth: A surge then a slowdown. American Journal of Agricultural Economics. Available at https://doi.org/10.1093/ ajae/aay023 (accessed May 31, 2018). APS (American Phytopathological Society). 2016. Phytobiomes: A Roadmap for Research and Translation. St. Paul, MN: American Phytopathological Society. Available at https://www.apsnet.org/members/outreach/ppb/Docu ments/PhytobiomesRoadmap.pdf (accessed May 8, 2018). Badiola, M., O. Basurko, R. Piedrahita, P. Hundley, and D. Mendiola. 2018. Energy use in Recirculating Aquaculture Systems (RAS): A review. Aquacultural Engineering. 81. doi: 10.1016/j.aquaeng.2018.03.003. Baenziger, P. S., W. K. Russell, G. L. Graef, and B. T. Campbell. 2006. Improving lives: 50 years of crop breeding, genetics and cytology (C-1). Crop Science 46:2230-2244. Bailey-Serres, J., S. C. Lee, and E. Brinton. 2012. Waterproofing crops: Effective flooding survival strategies. Plant Physiology 160(4):1698-1709. Baltes, N.J., J. Gil-Humanes, and D.F. Voytas. 2017. Chapter One – Genome Engineering and Agriculture: Oppor- tunities and Challenges. Progress in Molecular Biology and Translational Science 149:1-26. Baumhardt, R. L., B. A. Stewart, and U. M. Sainju, 2015. North American soil degradation: Processes, practices, and mitigating strategies: A review. Sustainability 7(3):2936-2960. Blakenship, R.E., and M. Chen. 2013. Spectral expansion and antenna reduction can enhance photosynthesis for energy production. Curr. Opin. Chem. Biol. 17:457-461. Castañeda Álvarez, N., C. K. Khoury, H. A. Achicanoy, V. Bernau, H. Dempewolf, R. J. Eastwood, L. Guarino, R. H. Harker, A. Jarvis, N. Maxted, J. V. Müller, J. Ramirez-Villegas, C. C. Sosa, P. C. Struik, H. Vincent, and J. Toll. 2016. Global conservation priorities for crop wild relatives. Nature Plants 2:16022. doi: 10.1038/nplants. 2016.22. CDC (Centers for Disease Control and Prevention). 2018. Multistate Outbreak of E. coli O157:H7 Infections Linked to Romaine Lettuce, Investigation Notice: Multistate Outbreak of E. coli O157:H7 Infections April 2018. (2018). Available at https://www.cdc.gov/ecoli/2018/o157h7-04-18/index.html (accessed June 4, 2018). Chong, K. and Z. Xu. 2014. Investment in plant research and development bears fruit in China. Plant Cell Rep Apr;33(4):541-50. doi: 10.1007/s00299-014-1587-6. Cleveland, D.A., C.N. Radka, N.M. Müller, T.D. Watson, N.J. Rekstein, H. V. Wright, and S.E. Hollingshead. 2011. Effect of localizing fruit and vegetable consumption on greenhouse gas emissions and nutrition, Santa Barbara County. Environ Sci Technol 45(10):4555-4562. Court, C. D., A. W. Hodges, M. Ramani, and T. H. Spleen. 2017. Economic Contributions of the Florida Citrus In- dustry: 2015-2016. Gainsville: University of Florida Food and Economics Department. Das, A., H. Schneider, J. Burridge, A. K. M. Ascanio, T. Wojciechowski, C. N. Topp, J. P. Lynch, J. S. Weitz, and A. Bucksch. 2015. Digital imaging of root traits (DIRT): A high-throughput computing and collaboration plat- form for field-based root phenomics. Plant Methods 11:51. Available at http://doi.org/10.1186/s13007-015- 0093-3 (accessed June 4, 2018). Diepenbrock, C. H., C. B. Kandianis, A. E. Lipka, M. Magallanes-Lundback, B. Vaillancourt, E. Góngora-Castillo, J. G. Wallace, J. Cepela, A. Mesberg, P. J. Bradbury, D. C. Ilut, M. Mateos-Hernandez, J. Hamilton, B. F. Owens, T. Tiede, E. S. Buckler, T. Rocheford, C. R. Buell, M. A. Gore, D. DellaPenna. 2017. Novel loci un- derlie natural variation in vitamin E levels in maize grain. Plant Cell 29(10):2374-2392. Prepublication Copy 31

Science Breakthroughs to Advance Food and Agricultural Research by 2030 Diffenbaugh, N. S., D. L. Swain, and D. Touma. 2015. Anthropogenic warming has increased drought risk in Cali- fornia. Proceedings of the National Academy of Sciences of the United States of America 112(13):3931-3936. Dwivedi, S. L., E. T. Lammerts van Bueren, S. Ceccarelli, S. Grando, H. D. Upadhyaya, and R. Ortiz. 2017. Diver- sifying food systems in the pursuit of sustainable food production and healthy diets. Trends in Plant Science 22(10):842-856. Elmer, W.H., and J.C. White. 2016. The use of metallic oxide nanoparticles to enhance growth of tomatoes and egg- plants in disease infested soil or soilless medium. Environmental Science Nano 3:1072-1079. Evans, L. T., and R. A. Fischer. 1999. Yield potential: Its definition, measurement, and significance. Crop Science 39(6):1544-1551. Fernandez-Cornejo, J. 2004. The Seed Industry in U.S. Agriculture: An Exploration of Data and Information on Crop Seed Markets, Regulation, Industry Structure, and Research and Development. Washington, DC: USDA Economic Research Service. Available at https://www.ers.usda.gov/publications/pub-details/?pubid=42531 (accessed May 10, 2018). Finkel, O. M., G. Castrillo, S. Herrera Paredes, I. Salas González, and J. L. Dangl. 2017. Understanding and exploit- ing plant beneficial microbes. Current Opinion in Plant Biology 38:155-163. Giovannoni, J. 2018. Tomato multiomics reveals consequences of crop domestication and improvement. Cell 172(1):6-8. Giraldo, J.P. M.P. Landry, S.M. Faltermeier, T.P. McNicholas, N.M. Iverson, A.A. Boghossian, N.F. Reuel, A.J. Hilmer, F. Sen, J.A. Brew, and M.S. Strano. 2014. Plant nanobionics approach to augment photosynthesis and biochemical sensing. Nature Materials 13:400-408. Gruber, K. 2016. Re-igniting the green revolution with wild crops Nature Plants 2:16048. Gruber, K. 2017. Agrobiodiversity: The living library. Nature 544(7651):S8-S10. Hatfield, J.L. and C.L. Walthall 2015. Meeting Global Food Needs: Realizing the Potential via Genetics × Environ- ment × Management Interactions. Agron. J 107: 1215. Howitt, R., D. MacEwan, J. Medellin-Azuara, J. Lund, and D. Sumner. 2015. Economic Analysis of the 2015 Drought for California Agriculture. Available at https://watershed.ucdavis.edu/files/biblio/Final_Drought% 20Report_08182015_Full_Report_WithAppendices.pdf (accessed May 8, 2018). Ikeuchi M., Shibata M., Rymen B., Iwase A., Bågman A.M., Watt L., Coleman D., Favero D.S., Takahashi T., Ah- nert S.E., Brady S.M., and K. Sugimoto. 2018. A Gene Regulatory Network for Cellular Reprogramming in Plant Regeneration. Plant Cell Physiology 59(4):765-777. doi: 10.1093/pcp/pcy013. Leach, J. E., L. R. Triplett, C.T. Argueso, and P. Trivedi. 2017. Communication in the phytobiome. Cell 169(4):587- 596. Li, X., Y. Xie, Q. Zhu, and Y. Liu. 2017. Targeted genome editing in genes and cis-regulatory regions improves qualitative and quantitative traits in crops. Molecular Plant 10(11):1368-1370. Katsaruware-Chapoto, R. D., P. L. Mafongoya, and A. Gubba. 2017. Responses of insect pests and plant diseases to changing and variable climate: A review. Journal of Agricultural Science 9(12):160. Konikow, L. F. 2013. Groundwater depletion in the United States (1900-2008). Scientific Investigations Report 2013-5079. Reston, VA: U.S. Geological Survey. Available at http://pubs.usgs.gov/sir/2013/5079 (accessed May 10, 2018). Livingston, M., J. Fernandez-Cornejo, J. Unger, C. Osteen, D. Schimmelpfennig, T. Park, and D. Lambert. 2015. The Economics of Glyphosate Resistance Management in Corn and Soybean Production. Washington, DC: U.S. Department of Agriculture–Economic Research Service. Lobell, D. B., and C. B. Field. 2007. Global scale climate–crop yield relationships and the impacts of recent warm- ing. Environmental Research Letters 2(1):014002. Long, S. 2015. Meeting the global food demand of the future by engineering crop photosynthesis and yield potential. Cell 161(1):56-66. Mallakpour, I., and G. Villarini. 2015. The changing nature of flooding across the central United States. Nature Cli- mate Change 5(3):250. Marles, R. 2017. Mineral nutrient composition of vegetables, fruits and grains: The context of reports of apparent historical declines. J Food Composition Analysis 56: 93-103 Martin, C., and J. Li. 2017. Medicine is not health care, food is health care: Plant metabolic engineering, diet and human health. New Phytologist 216(3):699-719. Massalha, H., E. Korenblum, S. Malitsky, O. H. Shapiro, and A. Aharoni. 2017. Live imaging of root–bacteria inter- actions in a microfluidics setup. Proceedings of the National Academy of Sciences of the United States of America 114(17):4549-4554. 32 Prepublication Copy

Crops Myers, S. S., A. Zanobetti, I. Kloog, P. Huybers, A. D. B. Leakey, A. J. Bloom, E. Carlisle, L. H. Dietterich, G. Fitzgerald, T. Hasegawa, N. M. Holbrook, R. L. Nelson, M. J. Ottman, V. Raboy, H. Sakai, K. A. Sartor, J. Schwartz, S. Seneweera, M. Tausz, and Y. Usui. 2014. Increasing CO2 threatens human nutrition. Nature 510(7503):139. NASEM (National Academies of Sciences, Engineering, and Medicine). 2018. A Review of the Citrus Greening Research and Development Efforts Supported by the Citrus Research and Development Foundation: Fighting a Ravaging Disease. Washington, DC: The National Academies Press. NASS (National Agricultural Statistics Service). 2018. Crop Production Historical Track Records. Available at https://www.nass.usda.gov/Publications/Todays_Reports/reports/croptr18.pdf (accessed May 18, 2018). Nicholson, C.F., X. He, M.I. Gómez , H.O. Gao, and E. Hill. 2015. Environmental and Economic Impacts of Local- izing Food Systems: The Case of Dairy Supply Chains in the Northeastern United States. Environ Sci Technol. 49(20):12005-12014. Nielsen, R.L. 2017. Historical Corn Grain Yields for the U.S. Web publication, Purdue University Agricultural Extension. Available at https://www.agry.purdue.edu/ext/corn/news/timeless/yieldtrends.html (accessed June 13, 2018). Nesme, J., W. Achouak, S. N. Agathos, M. Bailey, P. Baldrian, D. Brunel, Å. Frostegård, T. Heulin, J. K. Jansson, E. Jurkevitch, K. L. Kruus, G. A. Kowalchuk, A. Lagares, H. M. Lappin-Scott, P. Lemanceau, D. Le Paslier, I. Mandic-Mulec, J. C. Murrell, D. D. Myrold, R. Nalin, P. Nannipieri, J. D. Neufeld, F. O'Gara, J. J. Parnell, A. Pühler, V. Pylro, J. L. Ramos, L. F. W. Roesch, M. Schloter, C. Schleper, A. Sczyrba, A. Sessitsch, S. Sjöling, J. Sørensen, S. J. Sørensen, C. C. Tebbe, E. Topp, G. Tsiamis, J. D. van Elsas, G. van Keulen, F. Widmer, M. Wagner, T. Zhang, X. Zhang, L. Zhao, Y.-G. Zhu, T. M. Vogel, and P. Simonet. 2016. Back to the future of soil metagenomics. Frontiers in Microbiology 7:73. NRC (National Research Council). 1989. Goldenberry (cape gooseberry). Pp. 240−251 in Lost Crops of the Incas: Little-Known Plants of the Andes with Promise for Worldwide Cultivation. Washington, DC: National Acad- emy Press. Ort, D. R., S. S. Merchant, J. Alric, A. Barkan, R. E. Blankenship, R. Bock, R. Croce, M. R. Hanson, J. M. Hibberd, S. P. Long, T. A. Moore, J. Moroney, K. K. Niyogi, M. A. J. Parry, P. P. Peralta-Yahya, R. C. Prince, K. E. Redding, M. H. Spalding, K. J. van Wijk, W. F. J. Vermaas, S. von Caemmerer, A. P. M. Weber, T. O. Yeates, J. S. Yuan, X. G. Zhu 2015. Redesigning photosynthesis to sustainably meet global food and bioener- gy demand. Proceedings of the National Academy of Sciences of the United States of America 112(28):8529- 8536. Palm, H.W., U. Knaus, S. Appelbaum, S.Goddek, S.M. Strauch, T. Vermeulen, M.H. Jijakli, and B. Kotzen. 2018. Towards commercial aquaponics: a review of systems, designs, scales and nomenclature. Aquacul- ture International 26: 813-842. Pardey, P. G., and J. M. Beddow. 2013. Agricultural Innovation: The United States in a Changing Global Reality. Chicago: Chicago Council on Global Affairs. Available at https://www.thechicagocouncil.org/sites/default/ files/Agricultural_Innovation_Final%281%29.pdf (accessed May 8, 2018). Park, S., F. C. Peterson, A. Mosquna, J. Yao, B. F. Volkman, and S. R. Cutler. 2015. Agrochemical control of plant water use using engineered abscisic acid receptors. Nature 520(7548):545. Parnell, J. J., R. Berka, H. A. Young, J. M. Sturino, Y. Kang, D. M. Barnhart, and M. V. DiLeo. 2016. From the lab to the farm: An industrial perspective of plant beneficial microorganisms. Frontiers in Plant Science 7:1110. Ray, D. K., N. Ramankutty, N. D. Mueller, P. C. West, and J. A. Foley. 2012. Recent patterns of crop yield growth and stagnation. Nature Communications 3:1293. Rockström, J., J. Williams, G. Daily, A. Noble, N. Matthews, L. Gordon, H. Wetterstrand, F. DeClerck, M. Shah, P. Steduto, C. de Fraiture, N. Hatibu, O. Unver, J. Bird, L. Sibanda, and J. Smith 2017. Sustainable intensifica- tion of agriculture for human prosperity and global sustainability. Ambio 46(1):4-17. Rodríguez-Leal, D., Z. H. Lemmon, J. Man, M. E. Bartlett, and Z. B. Lippman. 2017. Engineering quantitative trait variation for crop improvement by genome editing. Cell 171(2):470-480. Savary, S., A. Ficke, J. Aubertot, and C. Hollier. 2012. Crop losses due to diseases and their implications for global food production losses and food security. Food Security 4(4):519-537. Schlatter, D. C., M. G. Bakker, J. M. Bradeen, and L. L. Kinkel. 2015. Plant community richness and microbial in- teractions structure bacterial communities in soil. Ecology. 96(1):134-142. Schuler, M. L., O. Mantegazza, and A. P.M. Weber. 2016. Engineering C4 photosynthesis into C3 chassis in the syn- thetic biology age. Plant Journal 87(1):51-65. Shi, Y., J. A. Thomasson, S. C. Murray, N. A. Pugh, W. L. Rooney, S. Shafian, N. Rajan. G. Rouze, C. L. Morgan, H. L. Neely, A. Rana, M. V. Bagavathiannan, J. Henrickson, E. Bowden, J. Valasek, J. Olsenholler, M. P. Prepublication Copy 33

Science Breakthroughs to Advance Food and Agricultural Research by 2030 Bishop, R. Sheridan, E. B. Putman, S. Popescu, T. Burks, D. Cope, A. Ibrahim, B. F. McCutchen, D. D. Baltensperger, R. V. Avant, M. Vidrine, and C. Yang. 2016. Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PLoS ONE 11(7):e0159781. Steward, D. R., P. J. Bruss, X. Yang, S. A. Staggenborg, S. M. Welch, and M. D. Apley. 2013. Tapping unsustainable groundwater stores for agricultural production in the High Plains Aquifer of Kansas, projections to 2110. Pro- ceedings of the National Academy of Sciences of the United States of America 110(37): E3477-E3486. Thomaier, S. K. Specht, D. Henckel, and A. Dierich. 2015. Farming in and on urban buildings: Present practice and specific novelties of Zero-Acreage Farming (ZFarming). Renew. Agric. Food Syst. 30:43-54. Trijatmiko, K. R., C. Dueñas, N. Tsakirpaloglou, L. Torrizo, F. M. Arines, C. Adeva, J. Balindong, N. Oliva, M. V. Sapasap, J. Borrero, J. Rey, P. Francisco, A. Nelson, H. Nakanishi, E. Lombi, E. Tako, R. P. Glahn, J. Stangoulis, P. Chadha-Mohanty, A. A. T. Johnson, J. Tohme, G. Barry, and I. H. Slamet-Loedin. 2016. Bio- fortified indica rice attains iron and zinc nutrition dietary targets in the field. Scientific Reports 6:19792. UN DESA (United Nations Department of Economic and Social Affairs). 2017. World Population Prospects: The 2017 Revision, Key Findings and Advance Tables. ESA/P/WP/248. Available at https://esa.un.org/unpd/wpp/ publications/Files/WPP2017_KeyFindings.pdf (accessed May 10, 2018). USDA (U.S. Department of Agriculture). 2015. USDA Roadmap for Plant Breeding. Available at https://www. usda.gov/sites/default/files/documents/usda-roadmap-plant-breeding.pdf (accessed May 8, 2018). USDA-ERS (U.S. Department of Agriculture Economic Research Service). 2017. Ag and Food Statistics: Charting the Essentials. October. https://www.ers.usda.gov/webdocs/publications/85463/ap-078.pdf?v=43025 (accessed May 8, 2018). USDA-ERS (U.S. Department of Agriculture Economic Research Service). 2018. Farm Income and Wealth Statistics: Cash Receipts by State. Available at https://data.ers.usda.gov/reports.aspx?ID=17843 (accessed June 18, 2018). USDA-FAS (U.S. Department of Agriculture Foreign Agricultural Service). 2018a. Global Agricultural Trade Sys- tem (GATS) Data. Available at https://apps.fas.usda.gov/gats/detectscreen.aspx?returnpage=default.aspx (ac- cessed May 8, 2018). USDA-FAS. 2018b. World Agricultural Production. Available at https://apps.fas.usda.gov/psdonline/circulars/ production.pdf (accessed May 8, 2018). USTR (Office of the U.S. Trade Representative). 2017. USTR Success Stories: Opening Markets for U.S. Agricul- tural Exports. Available at https://ustr.gov/about-us/policy-offices/press-office/fact-sheets/2017/march/ ustr-success-stories-opening-markets-us (accessed May 8, 2018). Van Eck, J., K. Swartwood, Z. Lemmone, J. Dalrymple, and Z. B. Lippman. 2017. Development of Agrobacterium- mediated transformation of Physalis peruviana and application of CRISPR/Cas9 Genome Editing. In Vitro Cellular & Developmental Biology—Animal 53(Suppl.):S34-S35. Walthall, C. L., J. Hatfield, P. Backlund, L. Lengnick, E. Marshall, M. Walsh, S. Adkins, M. Aillery, E. A. Ains- worth, C. Ammann, et al. 2012. Climate Change and Agriculture in the United States: Effects and Adaptation. USDA Technical Bulletin 1935. Washington, DC: USDA ARS (Agricultural Research Service). Wang, P., R. Khoshravesh, S. Karki, R. Tapia, C. P. Balahadia, A. Bandyopadhyay, W. Paul Quick, R. Furbank, T. L. Sage, and J. A. Langdale. 2017. Recreation of a key step in the evolutionary switch from C3 to C4 leaf anat- omy. Current Biology 27(21):3278-3287. Weber, C.L., and H.S. Matthews. 2008. Food-miles and the relative climate impacts of food choices in the United States. Environ Sci Technol. 42(10):3508-3513. Wei, X., Z. Zhang, P. Shi, P. Wang, Y. Chen, X. Song, and F. Tao. 2015. Is yield increase sufficient to achieve food security in China? PloS ONE 10(2):e0116430. Wong, M.H., J.P. Giraldo, S.-Y. Kwak, V.B. Koman, R. Sinclair, T.T. Salim Lew, G. Bisker, P. Liu, and M.S. Strano. 2017. Nitroaromatic detection and infrared communication from wild-type plants using plant nanobi- onics. Nature Materials 16(2):264-272. Wu, H., N. Tito, and J.P. Giraldo. 2017. Anionic cerium oxide nanoparticles protect plant photosynthesis from abiot- ic stress by scavenging reactive oxygen species. ACS Nano 11(11):11283-11297. Yang, S., B. Vanderbeld, J. Wan, Y. Huang. 2010. Narrowing down the targets: Towards successful genetic engi- neering of drought-tolerant crops. Molecular Plant 3(3):469-490. Yin, X., A. K. Biswal, J. Dionora, K. M. Perdigon, C. P. Balahadia, S. Mazumdar, C. Chater, H.-C. Lin, R. A. Coe, T. Kretzschmar, J. E. Gray, P. W. Quick, A. Bandyopadhyay. 2017. CRISPR-Cas9 and CRISPR-Cpf1 mediat- ed targeting of a stomatal developmental gene EPFL9 in rice. Plant Cell Reports 36(5):745-757. Yu, S., and L. Tian. 2017. Breeding major cereal grains through the lens of nutrition-sensitivity. Molecular Plant 11:23-30. 34 Prepublication Copy

Crops Zhu, C., K. Kobayashi, I. loladze, J. Zhu, Q. Jiang, X. Yu, G. Liu, S. Seneweera, K.L. Ebi, A. Drewnowski, N.K. Fukagawa and L. H. Ziska. 2018a. Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grins with potential health consequences for the poorest rice-dependent countries. Sci. Adv. 4:eaaq1012. Zhu, G., S. Wang, Z. Huang, S. Zhang, Q. Liao, C. Zhang, T. Lin, M. Qin, M. Peng, C. Yang, X. Cao, X. Han, X. Wang, E. van der Knaap, Z. Zhang, X. Cui, H. Klee, A. R. Fernie, and J. Luo. 2018b. Rewiring of the fruit metabolome in tomato breeding. Cell 172(1):249-261. Prepublication Copy 35

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For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate.

More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face.

Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030).

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