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Agricultural markets remain major issue downgrading root and tuber crop farmers who form the mainstream of the agricultural producers in Malawi. Recent evidence however reveals that orange‐fleshed sweet potato (OFSP) (Ipomea batatas) is currently being sold in produce markets along with the non‐orange varieties, sometimes in differentiated form in Malawi. The main objective of this study was to examine factors affecting market participation of sweet potato farmers in southern region of Malawi. Using a double‐hurdle model, this paper analyzed both the factors affecting farmer decision to participate and the extent/intensity of participation in market. The first tier of the double hurdle focused on decision to participate in the market using probit model and the second tier addressed factors affecting intensity of participation using truncated normal regression model. The paper used data collected from 360 farmers in southern districts of Malawi. Out of 360, 146 farmers had grown OFSP in the season preceding the survey. Double hurdle results indicate that farm size, output, age of a farmer (household head), and early maturing trait significantly determined decision to participate in the market. Further, results on intensity of participation indicate that access to market training, farm size, asset value, and output positively determined the intensity and negatively determined by distance to main market and gender of a farmer (household head). Based on the research findings, higher output levels and early maturing trait were found to increase smallholder farmer market participation. It is therefore recommended that strategies aimed at increasing household capacity to produce surplus produce through market tailored extension messages and productivity enhancement technologies could be highly effective in fostering smallholders' participation in commercial markets. Again, enhanced capacity building of research institutions to breed sweet potato varieties based on market demand is pivotal for increased market participation. Furthermore, research suggests that improving smallholder farmers' access to market price information, asset value, and farm size can help increase their intensity in the market. Therefore, it is critical for policymakers to holistically comprehend these socioeconomic factors in order to address the issue of smallholder farm households' decisions about market participation and the degree to which they participate. Core Ideas: Orange fleshed sweet potato is currently being sold along with non‐orange varieties, sometimes in differentiated.Decision to participate in market is significantly influenced by output, farm size, age early maturing attribute.Market intensity is determined by access to training, distance to market, farm size, gender, asset value and output.Breeding programs should integrate both sensory and agronomic traits such as early maturity and good taste. [ABSTRACT FROM AUTHOR]

Limited availability and access to quality seed is a major challenge faced by the Kenyan potato subsector. Smallholder farmers cultivate the bulk of potato mainly planting seed from informal sources without any quality assurance which contributes to low yields. In recent years, private sector businesses have engaged in certified seed potato production with positive impact on the volumes available, relying on minitubers to multiply in the field over three to four generations. Rooted apical cuttings (RACs) provide a productive alternative starter material that can further boost the Kenyan seed systems. Stokman Rozen Kenya Ltd (SRK) is a private sector business that has embraced this technology in 2017. Also, small‐scale nurseries have recently started the commercial production of cuttings. They both sell RACs mainly to seed growers for further bulking, but ware potato farmers can also produce quality seed on‐farm for their own use from RACs when applying good agricultural practices. This paper examines the initial experiences of both SRK and small‐scale nurseries in the production and marketing of RACs as well as their performance during subsequent field multiplications. Producing and selling RACs offers a profitable business opportunity, especially when productivity and sales increase. Compared to other rapid multiplication technologies, RACs also allow to significantly increase the volumes of early generation seed produced. Key recommendations are to create awareness and to develop adequate marketing strategies to promote their uptake, and to ensure RACs are adequately multiplied into commercial seed to improve its availability to smallholder farmers in Kenya. Core Ideas: Rooted apical cuttings are produced from tissue culture plantlets and planted in the field to produce seed tubers.Rooted apical cuttings have the potential to significantly boost the production of quality seed potato in Kenya.Rooted apical cuttings are recognized under Kenya's seed regulations as the same as tissue culture (G0 seed).Key challenges are to create wider awareness of rooted apical cuttings and to develop market demand.Each (seed) potato producer should assess well in advance his/her management capacities of rooted apical cuttings. [ABSTRACT FROM AUTHOR]

The severity of herbicide injury to dormant zoysiagrass (Zoysia spp.) increases with increasing green leaves at treatment time, but injury also occurs following treatment to fully dormant zoysiagrass, especially when treatment precedes rapid shoot emergence. Research was conducted to determine the persistence of radio‐labeled glyphosate or glufosinate on dormant zoysiagrass leaves, to assess how simulated raindrop quantity affects relocation of glyphosate plus colorant to subcanopy areas, and to evaluate the response of post‐dormant zoysiagrass to glyphosate dislodged and relocated from dormant leaves via simulated rainfall, dew, or disturbance during post‐dormancy growth. When dormant zoysiagrass leaves were treated with 14C‐glufosinate or 14C‐glyphosate, 69% and 57%, respectively, of the herbicides were water extractable for 21 days. Increasing the number of simulated raindrops 0.5 cm−2 from 1 to 20 removed >95% of the applied colorant from treated dormant zoysiagrass leaves, with concomitant relocation of residue to underlying filter paper. Maximum exposure of a single subtending green shoot occurred at five simulated raindrops 0.5 cm−2, which would approximate a rainfall of 3.35 mm. Subsequently, glyphosate applied to dormant zoysiagrass plugs followed by 3 mm simulated rainfall or dew and wiping 7–9 days later, when turf had reached 15% green cover, reduced zoysiagrass clipping biomass by 35% and 72%, respectively. Glyphosate applied to dormant zoysiagrass can dislodge and injure newly developing green shoots during transition. This injury can be mitigated by irrigating 1 day after glyphosate treatment to dormant turf or ensuring that the first irrigation or rainfall following treatment is at least 12 mm. [ABSTRACT FROM AUTHOR]

The African Potato Association (APA) is highlighted in the May-June issue of Crop Science for its efforts in promoting research and development in the potato and sweetpotato sectors in Africa. Despite a decrease in government agricultural spending, the APA remains committed to enhancing research dissemination and fostering collaborations among researchers within and beyond Africa. The special section in the journal features 30 papers from the 12th Triennial APA Conference, aiming to connect researchers, practitioners, and public and private sectors for effective product and program development. The introduction to the special section can be accessed through the provided link. [Extracted from the article]

Human activity has created an environmental imbalance, which is reflected in climate change and resulting temperature variations, harmful levels of air quality, and more frequent and more intense meteorological phenomena, thus having significant consequences on the agricultural sector, for example, changes in soil, climate, and water characteristics as well as in available resources for agricultural production. This paper presents an agent‐based model (ABM) to evaluate the behavior of the strawberry's (Fragaria × ananassa) agricultural system in Veracruz, Mexico, to determine the degree of existing vulnerability through a dynamic assessment of agricultural risk. Development of the ABM allows the evaluation of variations in the active entities (critical variables of the model) to determine the factors that present a better crop yield. The research showed that temperature and precipitation are determining factors in strawberry quality, as they have a direct relationship with the growth and different phenological stages of the crop from an early age to a stage of greater maturity from the budding, flowering, and fruiting stages of the strawberry. [ABSTRACT FROM AUTHOR]

Seed increase through manual pollination is a critical part of maize breeding and genetics research to advance generations in breeding programs, to create desired research crosses, and produce hybrid seed for trials. Pollination in the field and in controlled environments relies on the availability of high‐quality pollen at the time that recipient silks are receptive. Generally, pollinations are made by capturing pollen from the tassel in a paper pollinating bag placed on the tassels one day prior to pollination and newly released pollen is then transferred to silks on the target plant. In the field, maize pollen is only viable for one to four hours following dehiscence and the rate of desiccation is influenced by environmental conditions. We have developed a method which increases the lifespan of pollen and allows pollen from a single tassel to be used to pollinate many ears by mixing fresh pollen with a dilutant that can be stored for multiple days. We identified characteristics of the size of suitable substrates and selected a PEEK‐based substrate for regular utilization. We evaluated pollen viability and empirically demonstrated the capability to store pollen up to 9 days when pollen is mixed with a PEEK substrate and stored at 6°C. The pollen storage method was used to make successful pollinations across 24 maize inbred lines tested and was generally equivalent to the standard manual pollination process. This method has the potential to increase the efficiency of breeding operations and may be useful in an array of genetic studies. Core Ideas: Manual pollinations in breeding and genetics research requires pollen available when recipient silks are viable.The method collects and stores maize pollen for at least 5 days and facilitates efficient pollination.Pollen is mixed with polyetheretherketone and uses field‐collected pollen and simple storage conditions.The method can increase the number of pollinations per tassel and generates a reasonable number of viable seeds. [ABSTRACT FROM AUTHOR]

Simulation modeling of perennial fruit tree growth, structure, and physiology over multiple years is particularly difficult and has lagged behind modeling of other crops because fruit trees are indeterminate organisms that grow over several growing seasons, vary widely among individuals, and have their structures modified by variable pruning practices. Nearly 30 yr of research have been devoted to developing a mechanistic, virtual tree model to simulate peach [Prunus persica (L.) Batsch] fruit tree growth, structure, and physiology. Details of much of this work have been published in several research papers in a variety of journals over a couple decades. The goal of this review is to report on the entire project and provide an overview of the approach we took in such an endeavor. This review contains excerpts of numerous previously published papers and some comments and conclusions about the value of the modeling that has occurred. Core Ideas: Modeling tree crops is especially difficult because they are long‐lived and highly variable.L‐systems are ideally suited to deal with the complexity of tree structure and function.Carbon partitioning in trees can be modelled as collections of semi‐autonomous organs.Similar processes can be used to model water relations of trees.Estimates of woody biomass of trees can be used to model annual dynamics of tree carbohydrate storage. [ABSTRACT FROM AUTHOR]

Transgenes have been successfully commercialized for qualitatively inherited insect and herbicide resistance traits that show similar effects across genetic backgrounds. However, for quantitative traits like yield, genetic background may affect the measured transgene value. In this paper, we evaluated whether different genetic backgrounds impact the estimated value of a transgene for grain yield, plant height, and anthesis‐silking interval for maize by developing isogenic pairs of lines with and without a transgene and testing them in hybrid combination with non‐transgenic lines from a complementary heterotic group across eleven environments in the United States. Over all hybrid combinations, the transgene increased yield by 0.2 Mg ha−1. Across multiple non‐transgenic lines of the opposing heterotic group, the transgene effect within a line pair ranged from an increase of 0.8 Mg ha−1 for the NSS4 (non‐stiff stalk) and SS7 (stiff stalk) transgenic lines to a reduction of 0.3 Mg ha−1 for the NSS5 transgenic line when compared to their non‐transgenic isoline. Transgenic hybrids were often taller than non‐transgenic hybrids (p < 0.05). Anthesis to silking interval was reduced by four growing degree days overall, but no transgene × genotype interaction was detected among line pairs. Our results show the importance of testing transgene efficacy across a large sample of elite hybrid pairs to assess the gene's value. By only testing in a specific hybrid background, as may be done for qualitative traits like insect resistance, transgenes could be erroneously advanced or eliminated. Core Ideas: Effective transgenes for complex traits are difficult to identify due to large transgene × germplasm interactions.The effect of a transgene affecting yield under drought stress was positive or negative depending on genotype.Testing transgenes for complex traits in many genetic backgrounds help to quantify their value for breeding. [ABSTRACT FROM AUTHOR]

The editorial board of Crop Science has announced the recipients of the 2023 Editor's Citation for Excellence. These awards recognize the dedication and professional commitment of volunteer reviewers and editors who have contributed to the high standard and quality of papers published in the journal. The recipients were chosen based on their thorough, competent, and timely reviews or editing of manuscripts. Each recipient will receive a certificate of appreciation, an ASA‐CSSA‐SSSA gift certificate, and recognition in CSA News. The recipients include Dr. Gabriela Abeledo, Dr. Brenda Laura Gambin, Dr. Lori Hinze, Dr. Vince Pantalone, Dr. Cristiane Pilon, and Dr. Wei Wu as associate editors, and Dr. Georgia Eizenga, Dr. Jales Mendes Oliveira Fonseca, Dr. Laura Lindsey, Dr. Ntombokulunga Mbuma, Dr. Desalegn Serba, and Prof. Dr. Meiliang Zhou as reviewers. [Extracted from the article]

Mega‐environment (ME) analysis is analysis of multi‐year, multi‐location crop variety trial data conducted in a target region of a crop to understand the magnitude and nature of genotype‐by‐environment interaction (GE) of the crop in the region. If repeatable GE patterns are identified, then the target region must be divided into subregions or MEs. Breeding and utilizing ME‐specific cultivars will convert the repeatable GE into genotypic main effect (G) within ME, thereby improving heritability (selection reliability) and selection gain and maximize regional and overall productivity. If no repeatable GE is found, then the target region must be treated as a single ME and the GE must be accommodated by testing adequately, that is, at a sufficient number of locations in a sufficient number of years. This paper presents a theoretical framework of ME analysis, describes graphical tools to reveal the which‐won‐where patterns in a genotype‐by‐environment dataset, and demonstrates LG (location‐grouping) biplot analysis for revealing repeatable GE patterns and delineating MEs. The concept of G + GE or GGE, that is, GE relative to G, is emphasized. It is the relative GE that is the basis for ME analysis and breeding for specific adaptation; absolute magnitude of GE has little relevance for these purposes. Breeding ME‐specific oat cultivars in Canada is demonstrated with a real‐world example. Core Ideas: Proper mega‐environment analysis is a prerequisite for effective cultivar development.Mega‐environment delineation must be based on repeatable genotype‐by‐environment interaction patterns.Location‐grouping (LG) biplot is an effective graphical too for mega‐environment analysis.Examples were provided for mega‐environment analysis.An example was provided for breeding mega‐environment‐specific oat cultivars. [ABSTRACT FROM AUTHOR]

Parasitic Striga weeds severely damage cereal crops in sub‐Saharan Africa (SSA), leading to yield losses in susceptible varieties. A range of Striga control methods are commonly recommended, including cultural practices, chemical herbicides, biological control agents, and host resistance, either as solo treatments or in combinations of these approaches (i.e., integrated Striga management [ISM]). A limited number of studies compared the relative efficacy of the recommended Striga control methods, or their combinations for ISM, in cereal crop production in SSA. The objective of this paper was to undertake a meta‐analysis and provide a detailed comparison of the Striga control methods in the production of maize, sorghum, and the major millets, as a guide to effective Striga management. The study was conducted as a meta‐analysis of 66 research articles that reported on various control measures. The following agronomic data were collected: grain yield (GY) response of the assessed crops and Striga parameters such as damage rating score (SDR) and emergence count (SEC). Maize varieties possessing Striga‐resistant genes displayed high mean yield values at 2053.00 kg ha−1, varying from 281.00 to 6260.00 kg ha−1, and a mean SDR of 4.70, ranging from 2.00 to 7.00. Likewise, sorghum varieties with Striga resistance genes achieved greater GY with a mean yield response of 1738.00 kg ha−1, ranging from 850.00 to 2162.00 kg ha−1. A relatively low GY was achieved in maize and sorghum production when deploying ISM (e.g., cultural control + host resistance and host resistance + chemical herbicides) and chemical Striga control. Effective ISM and pre‐ and post‐emergent herbicides have not yet been identified for Striga control and yield gains. Striga damage negatively affected GY in maize, as revealed by the significant correlation (r = −0.36, P < 0.001) between GY and SDR. A relatively weak correlation was detected in maize between GY and SEC (r = 0.003, P = 0.96). Sorghum GY was negatively correlated with SEC, although nonsignificantly (r = −0.30, P = 0.36). Few studies have evaluated Striga control methods in pearl millet and finger millet, limiting the opportunity for an effective comparison. The study recommends SDR as the best selection criterion for improving GY performance in maize, while SEC and SDR are the parameters of choice in sorghum selection programs for better GY under Striga infestation. Overall, the meta‐analysis indicates that host resistance is the most effective method for controlling Striga infestation and boosting GY in maize and sorghum. There is an ongoing need for research into the best combinations of the reported control methods as a sound basis for the recommendation of an ISM package across target production environments of common cereals in Africa. Core Ideas: Maize and sorghum varieties that are resistant to Striga displayed high mean yield values under Striga infestation.Effective ISM and pre‐and post‐emergent herbicides have not yet been identified for Striga control and yield gains.Host resistance is the most effective method for controlling Striga and boosting yield in maize and sorghum.There is a need to investigate the best combinations of the reported control methods to recommend an ISM package.Few studies have evaluated Striga control methods in pearl millet and finger millet limiting effective comparison. [ABSTRACT FROM AUTHOR]

This paper presents an extension to a heuristic method for phasing and imputation of genotypes of descendants in biparental populations so that it can phase and impute genotypes of parents that are ungenotyped or partially genotyped. The imputed genotypes of the parent are used to impute low‐density (Ld) genotyped descendants to high density (Hd). The extension was implemented as part of the AlphaPlantImpute software and works in three steps. First, it identifies whether a parent has no or Ld genotypes and identifies its relatives that have Hd genotypes. Second, using the Hd genotypes of relatives, it determines whether the parent is homozygous or heterozygous for a given locus. Third, it phases heterozygous positions of the parent by matching haplotypes to its relatives. We measured the accuracy (correlation between true and imputed genotypes) of imputing parent genotypes in simulated biparental populations from different scenarios. We tested the imputation accuracy of the missing parent's descendants using the true genotype of the parent and compared this with using the imputed genotypes of the parent. Across all scenarios, the imputation accuracy of a parent was >0.98 and did not drop below ∼0.96. The imputation accuracy of a parent was always higher when it was inbred than outbred. Including ancestors of the parent at Hd, increasing the number of crosses and the number of Hd descendants increased the imputation accuracy. The high imputation accuracy achieved for the parent translated to little or no impact on the imputation accuracy of its descendants. Core Ideas: Hd SNP data in plant breeding populations is increasingly valuable for genomic selection.Hd genotyping thousands of candidates is expensive, imputation is a cost‐effective alternative.This paper presents an extension to a heuristic method for phasing and imputation of genotypes.Across all scenarios, imputation accuracy of a parent was >0.98 and did not drop below ∼0.96.High imputation accuracy for the parent translated to no impact on offspring imputation. [ABSTRACT FROM AUTHOR]

Knowledge of water use rates and responses to deficit irrigation practices in cool‐season turfgrasses is important, particularly in climates where irrigation is required to maintain turf quality. This is Part I of two companion papers reviewing cool‐season turfgrass water use and requirements. Part I presents the history of early water conservation and quantification methods in turfgrass and summarizes research on cool‐season turfgrass evapotranspiration (ET) and deficit irrigation. Part II summarizes research on cool‐season turfgrass drought resistance completed since 1980. Summaries of research from > 60 experiments related to ET include: measured ET rates in various climates; comparisons of actual ET to estimated ET; crop coefficients; deficit irrigation; and how plant characteristics and management practices influence ET. Summarized daily evapotranspiration (ETc) rates for Agrostis L. spp., fine fescues (Festuca L. spp.), tall fescue (Festuca arundinacea Schreb.), Lolium spp., and Poa spp. were a weighted average ETc and coefficient of variation (CV) of 6.12 (19.0%), 5.52 (16.8%), 7.79 (14.5%), 5.90 (19.9%), and 5.35 (30.2%) mm d–1, respectively, with an overall ETc of 6.25 mm d–1 (26.9%). Average crop coefficients have ranged from 0.85 to 0.95 (0.91 weighted average across species) and vary slightly during growing months. Minimum deficit irrigation replacement levels for acceptable turf quality have ranged from 59 to 74% of ET under different irrigation intervals. Further study is warranted to investigate differences in crop coefficients among cultivars within species, cultural influences, deficit irrigation replacement levels, and to standardize measurement protocol to improve consistency in crop coefficients across future turfgrass experiments. Core Ideas: A brief history of early water conservation research in turfgrass is presented.Evapotranspiration and deficit irrigation research in cool‐season turfgrasses is summarized.Average cool‐season turfgrass evapotranspiration rates ranged from 5.35 to 7.79 mm d−1.Average cool‐season turfgrass crop coefficient rates ranged from 0.85 to 0.95.Minimum deficit irrigation replacement levels have ranged from 59 to 74% of ET. [ABSTRACT FROM AUTHOR]

Knowledge of drought resistance of cool‐season turfgrasses is important because drought stress can occur wherever they are grown even in humid regions with wet climates. This review is Part II of two companion papers that review water use and requirements in cool‐season turfgrasses. Part I presented the history of early water conservation and quantification methods in turfgrass and then summarized research results since 1980 on cool‐season turfgrass evapotranspiration and deficit irrigation. Part II presents a brief history of drought research and then summarizes studies completed since 1980 on cool‐season turfgrass drought resistance including interspecies and intraspecies differences. This overview of research regarding drought resistance covers >30 field experiments that evaluated drought response to irrigation amounts, length of dry down, and the influence of environmental and management factors. More cool‐season turf research has focused on intraspecies variation in drought resistance of Kentucky bluegrass (Poa pratensis L.) or tall fescue (Festuca arundinacea Schreb.) than any other cool‐season turf species; therefore, more research is needed on other cool‐season turfgrass species, such as perennial ryegrass (Lolium perenne L.), bentgrasses (Agrostis L. ssp.), and fine fescues (Festuca L. spp.). Further study is warranted to investigate differences in drought resistance strategies among plants and management practices, shoot and root responses, subsequent recovery, and inter‐ and intraspecies variation in cool‐season turfgrasses especially in northern climatic regions where cool‐season turf species are adapted. Improvement of drought resistance in cool‐season turfgrasses will require focused breeding efforts with acute drought screening protocols. [ABSTRACT FROM AUTHOR]

Datura stramonium L. (jimsonweed) from the Solanaceae family is widely used in traditional medicine due to its medicinal properties. This paper investigated the effect of three levels of urea fertilizer (60, 120, and 180 kg ha–1) and three levels of planting density (6, 10, and 14 plants m−2) on the grain alkaloids, chlorophylls a and b content, carotenoids, anthocyanins, and grain and biological yields. A factorial experiment as a randomized complete block design was carried out at the Research and Education farm of Isfahan Agricultural and Natural Resources and Training Center in IRAN in 2018 and 2019. Significant differences were detected between urea levels and plant density for leaf chlorophyll content, carotenoids, and anthocyanins at the 1% probability. Also, hyoscyamine alkaloid levels and scopolamine content are affected by the urea levels at the 1% probability. Moreover, the relationship between phytochemical characteristics and alkaloids with the grain and biological yields in D. stramonium is investigated by path analysis. The results showed that grain yield, hyoscyamine alkaloid levels and scopolamine content is significantly improved by 6 plants m−2planting density and 180 kg ha–1 urea. Core Ideas: The effect of plant density and urea levels on the content of tropane alkaloids in Datura stramonium L. was investigated.The effect of physiological traits and tropane alkaloids on grain and biological yields were further studied by path analysis.Grain yield is significantly improved by 6 plants m−2 planting density and 180 kg ha−1 urea. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. Here, we outline a series of two papers by French and Schultz (F&S) on water use efficiency of wheat (Triticum aestivum L.) published in 1984. The insight of F&S was not to draw a regression line across their yield‐evapotranspiration data. Instead they saw an upper limit of 20 kg ha−1 mm−1 that, less than a decade after publication, was widely used by Australian farmers to benchmark their crops and identify causes of yield gaps. Over the last two decades, F&S‐type benchmarks have been expanded beyond wheat and beyond Australia to include sunflower (Helianthus annuus L.) in Argentina, maize (Zea mays L.) and wheat in the United States and China, and millet [Pennisetum glaucum (L.) R. Br.] in West Africa, among others. More recently, the concept of yield gap analysis based on a upper limit of yield per unit resource uptake has been successfully extrapolated to N. The N uptake per millimeter of water required to meet the water‐limited yield potential (0.65 kg N ha−1 mm−1 under their original conditions) is a hidden insight in the work of French and Schultz; it has been recently rediscovered in the context of crop improvement, co‐limitation theory, and drought‐induced N deficit. Perhaps more deeply, French and Schultz shifted farmers mindset from the mildly fatalistic idea of "drought" to the notion that many other factors were typically limiting crop yield, and the quantitative challenge of attaining a plausible benchmark. [ABSTRACT FROM AUTHOR]

Plant breeding is fundamentally comprised of three cyclic activities: (a) intermating lines to generate novel allelic combinations, (b) evaluating the newly created lines in diverse environments, and (c) selecting superior individuals to be used as parents in the next breeding cycle. While digital technologies and tools are commonly utilized for the latter two stages, many plant research programs still rely on manual annotation and paper tags to track the crosses that constitute the basis of a plant breeding program. This presence of analog data is a crack in the foundation of a digital breeding ecosystem and a significant occasion for errors to be introduced that will propagate through the entire breeding process. However, implementing digital cross tracking into breeding programs is difficult due to the nonstandardized workflows that different breeders have adopted. Intercross, an open‐source Android app, aims to provide scientists with a robust and simple solution for planning, tracking, and managing the crosses being made each season and aims to serve as the primary tool to digitize crossing data for breeding programs. The simplicity and flexibility of Intercross allows rapid and broad adoption by diverse breeding programs and will solidify the concepts of a digital breeding ecosystem. Core Ideas: Collecting crossing information is key to maintaining a digital data ecosystem. Intercross is an app that streamlines crossing data and metadata collection. Intercross can be utilized in diverse plant breeding programs. [ABSTRACT FROM AUTHOR]

Breeding programs are increasing efforts towards demand‐led breeding approaches to ensure that cultivars released meet the needs of end users including processors, traders, and consumers, and that they are adopted by farmers. To effectively deploy these approaches, new tools are required to better understand and quantify the degree of preference differences among alternative trait changes competing for measurement and selection effort. The purpose of this study was to present a method of quantifying preferences and developing typologies according to breeding priorities by applying an online trait preference survey approach to cassava (Manihot esculenta Crantz). This paper presents a conjoint analysis based on Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) to help guide breeding programs in understanding trait preferences across value chain roles and social contexts and set breeding priorities that represent diverse interests. Trait preferences were assessed using a comprehensive survey and analysis package incorporating a core adaptive conjoint method (1000minds, 2020). Trait selection was based on a trade‐off of 11 cassava traits carried out with 792 cassava value chain actors in four geopolitical regions in Nigeria. Principal component and cluster analyses revealed three clusters (typologies) of respondents according to their trait preferences. The results demonstrate the usefulness of this methodology that innovates on previous trait preference approaches to address the expanding needs of plant breeding programs within smallholder contexts. Core Ideas: Preference surveys can reflect economic importance of traits.Typologies of trait preferences give insights to understand heterogeneity of trait preferences.Typologies can guide breeding programs in exploring the needs of different market segments. [ABSTRACT FROM AUTHOR]

Combining ability effects for yield related traits can serve as selection criteria to pursue breeding for optimal biomass allocation in wheat (Triticum aestivum). The objective of this paper is to provide information based on a retrospective quantitative genetic analysis on combining ability studies of wheat for yield and yield‐related traits to predict potential genetic gains achievable in improving biomass allocation for drought tolerance and soil carbon storage. The study compares data on the general combining ability and specific combining ability effects of wheat for yield and related traits under optimum and drought stressed conditions from 40 studies around the world. Days to heading (DTH), plant height (PH), number of tillers per plant (TN), kernels per spike (KPS), 1,000‐kernel weight (TKW), shoot biomass (SB), and grain yield (GY) exhibited wide variation for general combining ability (GCA) and specific combining ability effects. Progeny performance increased by 14.30 and 4.04% for SB and GY, respectively, compared with parental values under optimum water conditions. Number of tillers and SB exhibited positive associations with GY (.45 ≤ r ≤.85, p <.05) under both water conditions. Meta effect sizes for drought stress were negative. The highest meta‐effect sizes were calculated for DTH (−4.5) followed by SB (−2.0), whereas KPS (−1.25) had the lowest. The genetic gains for PH, SB, and other yield components showed that divergent crosses involving complementary parents could enhance biomass allocation patterns in wheat. This could be used as a basis for improving biomass allocation to roots. Core Ideas: There is sufficient genetic variation in wheat genotypes for manipulating biomass allocation.The number of kernels per spike is stable under varying moisture conditions.Shoot biomass and grain yield expression are severely confounded by drought.Aboveground traits are important for indirect selection of root traits. [ABSTRACT FROM AUTHOR]

To date, more than 20 clubroot resistance (CR) loci have been reported in the Agenome of Brassica rapa; however, only a few of them has been introgressed into B. napus canola. The introgression of additional CR loci will broaden the genetic base of resistance of this crop. In this paper, we report the genetic basis of CR of B. rapa var. pekinensis cultivar 'Bilko' introgressed into B. napus, mapping this resistance using a recombinant inbred line (RIL) population developed from B. napus × Bilko- CR interspecific cross. Evaluation of the F2 and F3 populations of Bilko revealed that a single gene controls resistance to pathotype 3 in this cultivar. Quantitative trait lociseq approach using whole-genome resequencing identified a genomic region of chromosome A03 associated with this resistance in the RIL population. Single nucleotide polymorphism (SNP)-based allele-specific markers from the TIR-NB-LRR (TNL) gene Bra012688 co-segregated with this resistance, however, with 0.4-0.8% recombination. Bra012688 is located at 23,877,250-23,883,169 bp of B. rapa cultivar Chiifu-401 whole-genome assembly v.3.0, and at 378 bp downstream of another TNL gene Bra012689. Molecular markers, linked to previously reported CR loci of A03, did not co-segregate with the resistance in the RIL population; this demonstrates the need for the development of new markers for the CR loci following introgression into the recipient species. The knowledge and the SNP allele-specific markers developed in this study could be used in breeding for clubroot resistance in B. napus. [ABSTRACT FROM AUTHOR]

Wheat is a staple crop in Nepal and is the third major cereal crop grown across the country. To improve productivity and increase the number of farmers growing wheat, the Nepal Agricultural Research Council (NARC), since 1962, has been releasing new wheat varieties with higher productivity and disease resistance. Accurate identification of the varieties grown in farmer's fields is critical for assessing the adoption levels and the impact of new varieties. This understanding can change the landscape of the wheat market and the overall vulnerability of the crop to diseases and abiotic stresses. Current methods of identification that rely on farmer description and morphological traits have been associated with ambiguity. The objective of this study was to determine the varietal adoption of wheat in the seven wheat‐growing provinces of Nepal using DNA fingerprinting technology. The study revealed that 'Gautam' and 'Vijay' are the most popular wheat varieties planted in the plain areas of Nepal. The area covered in these varieties during the 2018–2019 wheat season was 20.3 and 19.5% respectively. 'WK1204' was popular and mostly planted in the mountainous areas of Nepal during the October–May cropping season. The decommissioned varieties, including 'Lerma Roja‐64', 'Pitic62', 'Kalyansona', 'NL‐30', 'Siddhartha', 'Vaskar', 'Vinayak', 'Annapurna‐2', and 'NL 251' are still in use by 8% of wheat farmers across Nepal. Almost 38% of the varieties currently grown were released 20 yr ago. The varietal adoption was determined using molecular markers through fingerprinting, and its implications are discussed in this paper. Core Ideas: Accurate understanding of varietal adoption is critical for its dissemination and helps frame effective agricultural policies that benefit farmers and consumers.Accurate identification of the varieties in farmer fields is critical for assessing impact.DNA fingerprinting of wheat varieties is a reliable method to asses variety adoption. [ABSTRACT FROM AUTHOR]

Previous results from our laboratory have shown that optical sorter–based indirect selection reduced deoxynivalenol (DON) accumulation in soft red winter wheat (SRWW). In this paper we evaluate the efficacy of optical sorter–augmented genomic selection (OSA‐GS) for lowering DON accumulation at three selection intensities across 2 yr. In total, 758 SRWW breeding lines were genotyped and then phenotyped in an inoculated Fusarium head blight (FHB) nursery. Accumulation of DON was measured on all breeding lines. The proportion of Fusarium‐damaged kernels estimated using an optical sorter (FDKos) was measured on 120 lines; these data were used to train a genomic prediction model. Genomic estimated breeding values (GEBVs) for FDKos were computed for all lines without actual FDKos data. The top 20, 30, and 40% of lines without actual FDKos data were selected based on FDKos GEBVs. The same was done using actual measured DON values. Both strategies lowered DON, but traditional direct phenotypic selection based on actual DON values outperformed OSA‐GS. In other words, phenotypic selection was necessary to achieve the greatest reductions in DON. However, using previously published cost estimates for the price of an optical sorter, DON analysis, and genotyping, we determined that OSA‐GS required less financial investment than phenotypic selection based on measured DON. Taken together, our findings indicate that OSA‐GS is a cost‐effective method for lowering DON accumulation and support the usefulness of an optical sorter as a tool for FHB resistance breeding in SRWW. Core Ideas: Optical sorter–augmented genomic selection reduced DON accumulation in wheat.Phenotypic selection for reduced DON accumulation outperformed genomic selection.Genomic selection required less financial investment than direct phenotypic selection. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by M. Wayne Adams published in 1967 that provided original insights about compensation in the components of seed number and seed yield in determining crop yield. Adams reviewed experimental results in a large number of crop species and discovered a consistent negative correlation between seed number and mean seed mass. He labeled this negative correlation as "component compensation" in the formation of yield. He hypothesized that component compensation resulted from limiting nutrient‐metabolite availability to support developing reproductive structures. Ultimately, the retained seeds would be filled to the extent allowed by the supply of nutrient‐metabolites so that there was compensation between seed number and individual seed mass. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long-range perspective in assessment of the papers. The current article briefly reviews the paper by W.G. Duncan, R.S. Loomis, W.A. Williams, and R. Hanau published in 1967 that provided original concepts about the interception of solar radiation by crop leaf canopies and the estimate of canopy photosynthesis rate based on the intercepted radiation. They developed a geometric description of beam penetration through leaf layers and calculation of canopy CO2 exchange by considering separately leaves in direct-beam radiation and in the shade. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for the selection of papers is that they must have been published at least 20 yr ago to allow for a long-range perspective in assessment of the papers. The current article briefly reviews the paper by George Robertson published in 1968 that provided key concepts used yet today to describe the pace of plant development. Robertson developed the ideas of normalized development rates for each ontogenetic stage, multiplication of temperature and photoperiod responses, and inclusion of base temperature and photoperiod parameters in the response functions. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by M.Y. Siddiqi, A.D.M. Glass, T.J. Ruth, and T.W. Rufty, Jr. published in 1990 that investigated the kinetics of nitrate influx by barley (Hordeum vulgare L.) seedlings. Using 13NO3−, they documented the existence of two influx systems. One was inducible and nitrate influx saturated under low nitrate concentrations. The second was noninducible and expressed a linear increase in nitrate influx over high nitrate concentrations. Key transformative results from this study were the demonstration that both systems were under negative feedback control based on root nitrate concentration. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by H.D. Cooper and D.T. Clarkson published in 1989 that offered an original analysis of internal movement of nitrogen in wheat (Triticum aestivum L.). Using 15NO3− fed to a split‐root system, they found that a large fraction of absorbed nitrogen was rapidly cycled around the plant as a result of exchanges between the xylem and phloem. They concluded that cycling in the plant ensured tissues had access to a common pool of soluble nitrogen from which nitrogen could be removed and incorporated into protein depending on the demands of tissue growth. The cycling pool of nitrogen also provided a possible whole‐plant signaling mechanism that coordinates growth activities with the feedback control system regulating nitrate uptake by the root. [ABSTRACT FROM AUTHOR]

This paper is concerned with the generation of designs for early generation, plant‐breeding experiments that use limited experimental resources as efficiently as possible to maximize the realized genetic gain (RGG) resulting from the selection of lines. A number of authors have demonstrated that partially replicated (p‐rep) designs for such experiments, in which the percentage of lines that are duplicated is p, are likely to be more efficient than grid‐plot designs. Therefore, our aim is to obtain the most efficient p‐rep design for an experiment using one of two distinctly different criteria and employing widely or readily available statistical software packages to search for an optimal design. However, this can be difficult because knowledge of the sources of variation and their magnitudes is required and is often unavailable. To overcome this impediment, a comprehensive simulation experiment was conducted to investigate whether designs that are robust to a wide range of experimental situations can be identified. Designs with p set to 20% and for different experimental situations are generated and the performance of each tested for 24 different variation scenarios. We concluded that for large experiments, the RGG obtained with various optimal designs is indeed not affected by the different variation scenarios and that resolved designs for fixed genetic effects should be generated for robustness. On the other hand, the design assumptions affect the RGG for small p‐rep designs. Even so, an overall recommendation is made. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by J.T. Ritchie published in 1981 that explored the use of extractable soil water as an independent variable for defining plant response to water deficit conditions. Recognizing the difficulty of using leaf water potential in defining plant response, he proposed an independent variable based on volumetric soil water content. Specifically, plant response was based on extractable soil water described as a function of 'fraction of total extractable water in the root zone.' Ritchie proposed a template for sensitivity of plant processes to soil drying based on fraction of total extractable water. Response functions based on this template have now been extensively studied and are key parts of many approaches to describing water use in both experimental and modeling studies. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by C.T. de Wit published in 1958 that explored the relationship between transpiration and crop growth. He organized his analysis data from experiments from a range of environments, many of which were done early in the 20th century. He found that there was a very high correlation within a species between growth and transpiration normalized for pan evaporation over a wide range of conditions, and the slope of the relationship was distinct for each species. He examined possible variation in the slope to growth conditions and found the slope remained essentially constant. Thus, he concluded that there was an intimate, stable dependence for each crop species on the amount of water lost and its growth. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by Harold L. Penman published in 1948 that offered an original analysis of approaches to estimate evaporation from natural surfaces. He developed two approaches: one based on a sink strength model, and the second on an energy balance model. He compared the predictions of these approaches to his experimental observations of evaporation from open water, bare soil, and grass. He found each of the models did well (r ≈ 0.8) in predicting open water evaporation. The evaporation from bare soil and grass was less than that from the open water, and the predicted evaporation amounts were variable even when normalized by open water evaporation. Even though Penman warned that aspects of the approaches were empirical, the energy balance model remains a mainstay in predicting crop water loss. [ABSTRACT FROM AUTHOR]

Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the breeding cycle. Gain can also be increased through higher selection intensities, as the size of the population available for selection can be increased by predicting performance of nonphenotyped, but genotyped, lines. This paper demonstrates the application of genomic prediction in a sorghum [Sorghum bicolor (L.) Moench] breeding program and compares different genomic prediction models incorporating relationship information derived from molecular markers and pedigree information. In cross-validation, the models using marker-based relationships had higher selection accuracy than the selection accuracy for models that used pedigree-based relationships. It was demonstrated that genotypes that have not been included in the trials could be predicted quite accurately using marker information alone. The accuracy of prediction declined as the genomic relationship of the predicted individual to the training population declined. We also demonstrate that the accuracy of genomic breeding values from the prediction error variance derived from the mixed model equations is a useful indicator of the accuracy of prediction. This will be useful to plant breeders, as the accuracy of the genomic predictions can be assessed with confidence before phenotypes are available. Four distinct environments were studied and shown to perform very differently with respect to the accuracy of predictions and the composition of estimated breeding values. This paper shows that there is considerable potential for sorghum breeding programs to benefit from the implementation of genomic selection. [ABSTRACT FROM AUTHOR]

Use of resistant cultivars is one of the most important measures to reduce the risk of Fusarium head blight (FHB, caused by various Fusarium spp.) and mycotoxins in cereals. Research on resistance to FHB has mainly focused on wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) and is very limited in oat (Avena sativa L.). In Norway, routine testing of cultivars and breeding lines has been performed in spawn-inoculated field experiments with Fusarium graminearum Schwabe as part of a concerted research and breeding effort to improve FHB resistance in oat. Data on FHB symptom, days to flowering, and plant height have been collected during the field seasons. Together with the field data, deoxynivalenol (DON) content and germination capacity of harvested kernels are used to score resistance levels of genotypes. In this paper, results are presented from a combined analysis of data from 9 yr of field trials from 2008 to 2016. Consistent and highly significant differences in DON content and germination capacity were documented among the current oat cultivars on the Norwegian market. These two negatively correlated parameters are used as selection criteria in breeding since they are relevant for the different end uses of the grains: DON content for use as food and feed, and germination capacity for seed production. In the paper, we discuss the pros and cons of the various screening methods and parameters used in assessing FHB resistance in oat and present the progress made in resistance breeding based on an established field testing methodology. [ABSTRACT FROM AUTHOR]

The popularity of Tartary buckwheat [Fagopyrum tataricum (L.) Gaertn], as a medicinal and food crop, has been increasing in recent years. However, its low yield seriously restricts its industrial development. Amongst the various studies conducted to enhance the productivity of Tartary buckwheat, the association between yield and main agronomic traits has formed the foundation for the breeding and cultivation of high‐yielding varieties, becoming the primary interest of breeders. The commonly used methods are often restricted by sample size, distribution assumptions and trait properties and confined to the linear relationship. In this paper, the random forest regression model was used to obtain a comprehensive and reliable evaluation. The phenotypic data of 200 Tartary buckwheat landraces with 15 quantitative and two qualitative agronomic traits for two consecutive years were used. Results were compared between planting seasons and with those from classical methods, such as the correlation analyses and the multiple linear regression model. The random forest model distinguished the number of grains per plant, plant height, and 1,000‐grain weight as the most influential agronomic traits in both seasons. The main and interactive effects were explored using the accumulated local effects plot and showed great conformity between the two seasons. The robustness and reliability of the random forest model make it a desirable methodology for breeding new varieties and germplasm innovation of Tartary buckwheat and other crops. [ABSTRACT FROM AUTHOR]

This paper reports a first study exploring genomic prediction for adaptation of sorghum [Sorghum bicolor (L.) Moench] to drought‐stress (D‐ET) and nonstress (W‐ET) environment types. The objective was to evaluate the impact of both modeling genotype × environment interaction (G×E) and accounting for heterogeneous variances of marker effects on genomic prediction of parental breeding values for grain yield within and across environment types (ETs). For this aim, different genetic covariance structures and different weights for individual markers were investigated in best linear unbiased prediction (BLUP)‐based prediction models. The BLUP models used a kinship matrix combining pedigree and genomic information, termed K‐BLUP. The dataset comprised testcross yield performances under D‐ET and W‐ET as well as pedigree and genomic data. In general, modeling G×E increased predictive ability and reduced empirical bias of genomic predictions for broad adaptation across both ETs vs. models that ignored G×E by fitting a main genetic effect only. Genomic predictions for specific adaptation to D‐ET or W‐ET were also improved by K‐BLUP models that explicitly accommodated G×E and used data from both ETs relative to prediction models that used data from the targeted ET exclusively or models that used all the data but assumed no G×E. Allowing for heterogeneous marker variances through weighted K‐BLUP produced clear increments (43–72%) in predictive ability of genomic prediction for grain yield in all adaptation scenarios. We conclude that G×E as well as locus‐specific genetic variances should be accommodated in genomic prediction models to improve adaptability of sorghum to variable environmental conditions. [ABSTRACT FROM AUTHOR]

Water stress is the most significant environmental stress in agriculture worldwide. Potato (Solanum tuberosum L.) is a drought‐susceptible crop. Water stress tolerance is a complex trait of increasing importance in potato. The objective of this work was to evaluate the differential response strategies associated with water stress tolerance in a highly diverse potato panel. Multienvironment trials were assessed, both in field and in glasshouse with contrasting water regimes. The yield, dry matter, and frying ability were measured in the field assays, whereas proline concentration (PrC), relative water content (RWC), and water consumption (WC) were measured in the glasshouse assays. A mixed linear model and ANOVA were performed. The best linear unbiased predictors (BLUPs) of every genotype for each measured variable were estimated. Pearson correlation coefficient (r) and principal component analysis (PCA) assessed the association among traits. The genotypes were ranked by their BLUPs values. The high diversity potato panel showed variability both in the response to water stress and within each water regime. In general, Solanum tuberosum spp. andigena genotypes were associated with the lowest PrC and higher yield, WC, and RWC. By using BLUPs, a panel of genotypes with good performance under water deficit was defined. This paper provides knowledge useful to design breeding strategies to water stress tolerance and new physiological research lines. The utilization of the elite genotypes identified in this study as progenitors constitute a starting point for breeding programs oriented to develop water‐stress‐tolerant varieties. [ABSTRACT FROM AUTHOR]

Over the last three decades, Fusarium infections and related mycotoxin contamination have caused significant economic losses in oats (Avena sativa L.). Breeding for resistance is highly prioritized in oats, but infection processes and resistance components against Fusarium species are not fully identified. In this study, the genetic variation for flowering traits and its impact on mycotoxin accumulation in oats is described. The first experiment of this paper was focused on flowering traits in 50 oat genotypes (Panel 1) to identify cleistogamic oats. Then, two separate Fusarium‐inoculated experiments in three (Panel 2 with 25 genotypes) and two environments (Panel 3 with 16 genotypes) were conducted to assess the relationship between the degree of anther retention (AR) and resistance to Fusarium infestation and mycotoxin accumulation in oats. Panel 2 was inoculated with Fusarium culmorum, F. langsethiae, and F. sporotrichioides, and Panel 3 was inoculated with either F. graminearum or F. culmorum. The assessment of open flowering score and AR displayed a continuous variation from dominating chasmogamy to complete cleistogamy. Significant differences for deoxynivalenol and T‐2 were found, with a modest correlation between both mycotoxins. The lowest mycotoxin levels were found in two old and one modern cultivar, and the highest levels were found in a dwarf oat cultivar. Compared with plant height, AR was a rather ambiguous factor for the mycotoxin content, and it interfered with effects of other traits displaying high ranges such as earliness, lodging, or hull content. To unravel components of resistance to Fusarium in oats more precisely, specific populations with lower ranges in plant height and heading date should be studied. [ABSTRACT FROM AUTHOR]

Physiological and management modifications to increase crop yields require an appreciation of the impact of these changes on a geospatial basis. It is quite possible that the yield response to any modification may vary from positive in one location to negative in another location. Therefore, tools to undertake geospatial analysis are required to assess the overall impact. It is argued that mechanistic models based on the physics and physiology of plant development, growth, and yield formation are required for such tasks. Several criteria in selecting model tools are discussed. First, models that need to be "calibrated" are not suited for geospatial assessments because the calibration processes causes the model to be an empirical representation of the calibration data and limited to the calibration environment. Extreme caution is needed to extrapolate model use beyond the domain of calibration, since geospatial analysis requires the model to be run for a range of geographical locations over a number of growing seasons. Second, to readily understand the output from simulations across space and time, models needs to be compact and transparent so output that seems inconsistent or not intuitively obvious can be tracked to the critical features in the model. Models with a smaller number of parameters are likely to be more transparent. Finally, it is necessary that the robustness of the model has been tested against a range of environmental conditions. In this paper, we discuss the example of the Simple Simulation Model (SSM) as an option that meets these criteria. [ABSTRACT FROM AUTHOR]

We used the Agricultural Production Systems sIMulator (APSIM) to predict and explain maize and soybean yields, phenology, and soil water and nitrogen (N) dynamics during the growing season in Iowa, USA. Historical, current and forecasted weather data were used to drive simulations, which were released in public four weeks after planting. In this paper, we (1) describe the methodology used to perform forecasts; (2) evaluate model prediction accuracy against data collected from 10 locations over four years; and (3) identify inputs that are key in forecasting yields and soil N dynamics. We found that the predicted median yield at planting was a very good indicator of end‐of‐season yields (relative root mean square error [RRMSE] of ∼20%). For reference, the prediction at maturity, when all the weather was known, had a RRMSE of 14%. The good prediction at planting time was explained by the existence of shallow water tables, which decreased model sensitivity to unknown summer precipitation by 50–64%. Model initial conditions and management information accounted for one‐fourth of the variation in maize yield. End of season model evaluations indicated that the model simulated well crop phenology (R2 = 0.88), root depth (R2 = 0.83), biomass production (R2 = 0.93), grain yield (R2 = 0.90), plant N uptake (R2 = 0.87), soil moisture (R2 = 0.42), soil temperature (R2 = 0.93), soil nitrate (R2 = 0.77), and water table depth (R2 = 0.41). We concluded that model set‐up by the user (e.g. inclusion of water table), initial conditions, and early season measurements are very important for accurate predictions of soil water, N and crop yields in this environment. [ABSTRACT FROM AUTHOR]

Biodiversity in and across food and agriculture systems provides tremendous value to present and future generations. However, across the world we are losing genes, species, and ecosystems faster than we can account for them. With one million plant and animal species at risk of extinction, our society is challenged to address the drivers of ecosystem degradation and species loss. Increasingly, the negative impacts of agriculture and food systems on biodiversity are being raised as well as the global risks to health associated with unhealthy diets. Recent efforts in North America to raise awareness of crop diversity and coordinate plant conservation efforts culminated in a symposium with botanic gardens, agricultural researchers, wild land managers, conservation organizations, academics, and government bodies. The gathering focused primarily on production‐side solutions such as crop diversity, crop wild relative conservation, and agricultural education. Although not present at the symposium, chefs were commonly highlighted and discussed as key collaborators in plant conservation through their important role in connecting consumers to agriculture production and new food plants. This paper shares examples of chefs and culinary programs working to impact agriculture, diets, and plant diversity. To critically assess which chef and culinary programs are having the greatest impact future researched is needed, but as we race to save plant species from extinction, it is clear that chefs connect to consumers in unique ways and are important potential allies in cooking up new sustainable consumption and production patterns that support biodiversity in food systems. [ABSTRACT FROM AUTHOR]

Agriculture production in study areas benefits from the use of ridge‐furrow rainwater harvesting (RFRH) to supplement rainfall in the absence of irrigation from imported sources. However, it is necessary to select suitable fodder plants for use with RFRH in this climate. In this paper, 10 treatments (3 ridge widths × 3 ridge‐mulching materials + flat planting [FP] as control) in a complete random design were applied in a 3‐yr field experiment for alfalfa (Medicago sativa L.) and oat (Avena sativa L.) production, respectively. Ridges mulched with plastic film (PF) and ridges mulched with biodegradable film (BF) had positive effects on fodder, grain yields, and water use efficiency (WUE), but ridges with manually compacted soil (MCS) had a negative effect on yield and WUE in the most cases. Fodder, grain yields, and WUE decreased as ridge width increased. For oats, the decrease of WUE of MCS was 1.31 kg ha−1 mm−1, but the increase of WUE of BF and PF was 0.83 and 1.25 kg ha−1 mm−1, respectively, compared with that of FP over 3 yr. For alfalfa, the increase of WUE of MCS, BF, and PF was, respectively, 0.22, 5.62, and 6.33 kg ha−1 mm−1. The RFRH systems, especially PF and BF, produced oat and alfalfa fodders with increased crude protein content and decreased acid and neutral detergent fiber content. The average alfalfa fodder yield was 1.37 times greater than that of oats, whereas the average WUE of alfalfa was 2.62 times greater than that of oats. Alfalfa fodder contained higher crude proteins and lower neutral detergent fiber content than oat fodder and had similar acid detergent fiber. It is more economic to harvest oat fodder than to harvest oat grain, and it is more economic to produce alfalfa than to produce oats. [ABSTRACT FROM AUTHOR]

Crop residue returning (CRR) is known to improve the soil environment and thus increase crop production. However, the impacts of CRR on wheat (Triticum aestivum L.) yield have been contrary at times due to the differences in climatic conditions, soil traits, and management practices. These effects were evaluated using 351 paired observations published in 161 papers comprising studies conducted in 19 provinces (autonomous regions) of China. No publication bias or extreme values were found in the data, indicating that the analysis results are highly reliable. Compared with the practice of no crop residue returning (NCRR), the practice of CRR increased wheat yield significantly, on average by 8.29%, and proved more beneficial in Northwest China and in regions with average annual precipitation of 200 to 400 mm, average annual temperatures >11°C, sandy loam soil, and rotation with legumes (soybean [Glycine max (L.) Merr.]–wheat and pea [Pisum sativum L.]–wheat). The following aspects of CRR and crop management conferred greater benefits in yield: continuing the practice for 3 to 6 yr (compared with 1–2, 7–10, and ≥11 yr), using the residues at 3 to 6 t ha−1 (compared with <3, 6–9, and > 9 t ha−1), chopped straw (compared with intact straw), rainfed conditions (compared with irrigated conditions), and applying N at 200 to 300 kg ha−1 (compared with <100, 100–200, and >300 kg ha−1). The yield increase was significantly higher when the residues were returned in the form of mulch (12.56%) and for spring wheat (11.90%) than plowing them back into soil (4.53%) and for winter wheat (7.09%). The meta‐analysis thus confirms the benefits of CRR in higher wheat yields in China and also suggests that the benefits of CRR are site specific. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by C.M. Donald and J. Hamblin published in 1976 that provided original insights about the role of harvest index (defined by them as the ratio of economic yield to aboveground mass) in influencing crop yield. Donald and Hamblin reviewed experimental results showing that harvest index was relatively stable across variations in plant size, had high heritability, and was associated with high grain yield. Although their observations were confirmed in subsequent tests, inconsistent results in plant selection in breeding programs for high yield based on harvest index has discouraged the use of harvest index as a basis for selection. Nevertheless, high harvest index is now well ingrained as an essential plant characteristic for high crop yields. [ABSTRACT FROM AUTHOR]

Genetic improvement of crop plants is dependent on the availability of genetic variation, which can be present naturally or can be created using mutations. Ethyl methanesulfonate (EMS) mutagenesis provides an attractive tool to create variant alleles of genes of interest in any plant. In the present paper, we report development of an EMS‐mutagenized population in a hard red winter wheat (Triticum aestivum L.) variety Jagger. Jagger has been a leading variety across the United States and has been grown internationally as well, for over two decades now. It possesses many useful traits related to disease resistance, cold tolerance, and milling and baking qualities. Because it is a landmark variety, the genome of Jagger is being sequenced by an international collaborative team, which will speed up gene mapping and cloning efforts in it. The Jagger Targeting Induced Local Lesions In Genome (TILLING) resource developed in this work will be useful for functional validation of these genes. The mutagenized population was developed using EMS and was characterized phenotypically and genotypically. Gene‐wise mutation screening was performed for three genes located on different chromosomes across all the three genomes. The population has an overall mutation frequency of 1/40.7 kb, and we were able to find multiple knockout, missense, and missplicing mutations for each targeted gene. The population will be useful as a forward and reverse genetic screen for a number of valuable traits. [ABSTRACT FROM AUTHOR]

The principal goals of a plant breeding program are to provide breeders with cultivar information for selection purposes and to provide farmers with high‐yielding and stable cultivars. For that reason, multi‐environment trials need to be done to predict future cultivar yield, and a robust statistical procedure is needed to provide reliable information on the tested cultivars. In Sweden, the statistical procedure follows the tradition of modeling cultivar effects as fixed. Moreover, the analysis is performed separately by zone and level of fungicide treatment, and so the factorial information regarding cultivar × zone × fungicide combinations is not explored. Thus, the question arose whether the statistical method could be improved to increase accuracy in zone‐based cultivar prediction, since the cultivar recommendation is zone based. In this paper, the performance of empirical best linear unbiased estimation (E‐BLUE) and empirical best linear unbiased prediction (E‐BLUP) are compared using cross‐validation for winter wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.), in single‐year and multiyear series of trials. Data were obtained from three agricultural zones of Sweden. Several linear mixed models were compared, and model performance was evaluated using the mean squared error of prediction criterion. The E‐BLUP method outperformed the E‐BLUE method in both crops and series. The prediction accuracy for zone‐based yield was improved by using E‐BLUP because the random‐effects assumption for cultivar × zone interaction allows information to be borrowed across zones. We conclude that E‐BLUP should replace the currently used E‐BLUE approach to predict zone‐based cultivar yield. [ABSTRACT FROM AUTHOR]

Extra‐large (XL) hybrid confection sunflower (Helianthus annuus L.) achenes are popular among snack food consumers, but these achenes perform poorly with precision planters; therefore, the option of planting coated seed from XL achenes was evaluated in this study. The objective of this paper was to evaluate the effect of various coating materials and buildup levels on live seed emergence, precision planting, stand establishment, and crop performance under field conditions. Based on the laboratory results on germination and plantability, four coating materials (polymer A, polymer B, zeolite, and lime) at 30 and 35% buildup levels were selected for the field trails at Prosper, ND. A separate smaller field study was conducted at Minot, ND, to verify the performance of coated seed under different growing conditions. At both Prosper and Minot locations, all the coated seed treatments resulted in significantly higher live seed emergence and grain yield than XL achenes. Live seed emergence of all the coated seed (93–99%) was significantly higher than the XL achenes (88%), and similar or higher than the large achenes (94%) at Prosper. Laboratory singulation of all the coated seed was superior to both XL achenes and large achenes, which contributed to uniform seed spacing in the field for the coated seed. Overall, this study showed that coating the hulled seeds substantially increased seed plantability and crop performance compared with XL achenes and even large achenes. A successful outcome of this study may extend this research to other sunflower seed sizes and possibly other crops. [ABSTRACT FROM AUTHOR]

The majority of studies evaluating genomic selection (GS) for plant breeding have used single‐trait, single‐site models that ignore genotype × environment interaction (GEI) effects. However, such studies do not accurately reflect the complexities of many applied breeding programs, and previous papers have found that models that incorporate GEI effects and multiple traits can increase the accuracy of genomic estimated breeding values (GEBVs). This study's goal was to test GS methods for prediction in scenarios that simulate early‐generation yield testing by correcting for field spatial variation, and fitting multienvironment and multitrait models on data for 14 traits of varying heritability evaluated in unbalanced designs across four environments. Corrections for spatial variation increased across‐environment trait heritability by 25%, on average, but had little effect on model predictive ability. Results between all models were generally equivalent when predicting the performance of newly introduced genotypes. However, models incorporating GEI information and multiple traits increased prediction accuracy by up to 9.6% for low‐heritability traits when phenotypic data were sparsely collected across environments. The results suggest that GS models using multiple traits and incorporating GEI effects may best be suited to predicting line performance in new environments when phenotypic data have already been collected across a subset of the total testing environments. [ABSTRACT FROM AUTHOR]

Carbon isotope discrimination (Δ) has been proposed as a method for evaluating transpiration efficiency in C3 plants. It is important to study the association of Δ in different parts with the long-term water use efficiency (WUE). In this paper, plant height, Δ in leaf water soluble carbohydrates (ΔWSC), photosynthetic gas exchange parameters, Δ in aboveground shoot (ΔAGS), stem/leaf weight ratio, aboveground biomass (AGB), evapotranspiration, and WUE were determined in a collection of 10 alfalfa (Medicago sativa L.) genotypes under three water treatments (230 [T1], 460 [T2], and 700 mm irrigation [T3]) in a Ningxia central desert steppe in 2012 and 2013. Significant interactions were found for AGB and WUE among year, treatment, and genotype, whereas significant interactions of year x treatment and year x genotype were only found for ΔAGS but not for ΔWSC. Generally, more water input increased the values of the traits tested except for WUE and single-leaf intrinsic WUE (in Pn/Gs). More irrigated water input resulted in increase in AGB, ΔAGS, and ΔWSC and decrease in Pn/Gs. The greatest WUE was recorded under T2 in 2012. Significant and positive correlations were observed between AGB and ΔAGS (r = 0.588, 0.574, and 0.386 under T1, T2, and T3, respectively). Under T2 and T3, ΔWSC correlated negatively with WUE (r = -0.383 and 0.602, respectively). Ningmu No. 1 was found to have the greatest WUE (18.34 kg ha-1 mm-1) and yield (17.71 Mg ha-1) across water treatments and years. The findings suggest that in the semiarid areas applying irrigation of 230 to 700 mm yr-1, Δ in aboveground shoots or in leaf water-soluble carbohydrates at the flowering stage seems to be a useful indicators reflecting aboveground biomass and integrated WUE for alfalfa. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to clarify the compensation or reduction effect of drought--flood abrupt alternation (DFAA) events on the yield and yield components of rice (Oryza sativa L.). The experiments, conducted in 2016 and 2017, were on three different drought and flood treatments and compared with normal irrigation conditions. Compared with the normal control group, the average yield reduction of the DFAA groups was 12.98% in 2016 and 29.94% in 2017, and the combination of heavy droughts and heavy flooding was the most unfavorable for yield. The reduction in grains per panicle and the total grain number was the main reason for yield reduction under DFAA stress. The damage in terms of the total grain number amounted to 18.84 and 17.82% in 2016 and 2017, respectively. The interannual differences in the thousand- seed mass and seed setting rate increased in 2016 and decreased in 2017. Compared with the drought groups and the flood groups, the flood stress of the DFAA groups reduced the yield under drought conditions, and the decrease in the total grain number and panicles per barrel during the flood period was the main reason. The drought stress of the DFAA groups compensated the yield under flood conditions, mainly because the total grain number and seed setting rate increased during the drought period. Under long-term light drought conditions, the panicles per barrel, grains per panicle, total grain number, thousand-seed mass, and seed setting rate increased. Under long-term heavy drought conditions, the panicles per barrel mainly increased. [ABSTRACT FROM AUTHOR]

Humanity's survival depends on crops-the green line standing between us and calamity. To meet ever expanding human needs, crops must become increasingly more productive, mainly through genetic gains that exploit diverse plant genetic resources (PGR), the raw materials for crop breeding. For millennia, PGR have been conserved by individuals, communities, and organizations. These stewards of our agricultural future have been nearly as diverse as the PGR that they have conserved. Their invaluable roles in underpinning the security of global agriculture have largely been underappreciated. Furthermore, the challenges and complexity of successful PGR stewardship have been inadequately recognized. This paper pays tribute to these stewards' characteristic attributes and their contributions to PGR conservation and sustainable use. It describes the pervasive impacts of PGR on crop agriculture and explains how numerous factors have affected PGR stewardship capacities. Plant genetic resource stewardship involves many different components, which are typically conducted over extended timeframes. Sustained, adequate support for PGR maintenance, a key component, has been the exception rather than the rule. Past and present PGR stewardship successes and challenges furnish numerous lessons for meeting future demands. Such lessons include recognizing the importance to PGR stewardship of: dedicated and diverse PGR stewards, continual and persistent financial support for PGR genebanks and their staffs, protecting crop wild relatives, and safeguarding genebank collections from extreme weather and introduced pests and pathogens. In the future, PGR stewardship might be conducted more frequently and more adequately by multiinstitutional networks enabled by advances in information technology and artificial intelligence. [ABSTRACT FROM AUTHOR]