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Summary: Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops.Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions.The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity.The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates. [ABSTRACT FROM AUTHOR]

Understanding physiological changes in response to long‐term selection for yield can inform breeding decisions and hasten genetic gain. The objective of this study was to characterize changes over time in yield‐relevant physiological traits for hybrids with different years of release for grain sorghum (Sorghum bicolor L. Moench). Field trials were conducted during the 2018 and 2019 seasons in 8 site‐years across the states of Kansas and Texas including 20 commercially available grain sorghum hybrids released by Pioneer between 1963 and 2017. Detailed yield‐related physiological traits were determined in 2 site‐years including grain yield and its components, grain filling, plant biomass, panicle length, and water‐soluble carbohydrates (WSC) during the reproductive period. Consistent with estimates using historical yield data, sorghum yield improvement was 27 kg ha−1 yr−1. For the 2 site‐years with detailed yield‐related physiological traits, no changes in final grain weight, grain‐filling duration, and rate over time were documented. In contrast, grain number increased at a rate of 100 grains m−2 yr−1. Modern hybrids had larger panicle size and showed greater accumulation of WSC during vegetative period (as measured at the start of flowering) and greater remobilization of WSC during the reproductive period (after flowering) to grain, thus, maintaining grain size on the increased grain number per unit area and harvest index. These findings suggest that WSC dynamics play a critical role on past genetic yield gain in sorghum and its potential for future improvements should be considered. Core Ideas: Sorghum yield improvement was 27 kg ha−1 yr−1 over the last six decades in the United States.Grain number increased at 100 grains m−2 yr−1, with also a 0.4% per year gain in harvest index.No changes in grain size, and neither in grain‐filling duration nor in the rate were recorded.Modern hybrids had larger panicle size with greater water‐soluble carbohydrates.Water‐soluble carbohydrates remobilization plays a key role in sustaining grain size with increased grain number. [ABSTRACT FROM AUTHOR]

One of the main challenges of using low plant densities in restrictive and variable environments is to maximize the use of resources in better‐than‐expected years. In this context, tillering could be an alternative to increase reproductive and vegetative plasticity. The objectives of this study were to (a) characterize the correlation between environmental conditions, tiller traits, crop grain yield, and grain yield advantages due to tillers; (b) determine the grain yield response to tillering (i.e., grain yield difference between tillered and nontillered crops) for a wide range of environments; and (c) to evaluate the effect of tiller presence on grain yield of the main shoot, considering its effect on the apical and subapical ears. Tillered and nontillered crops were evaluated under rainfed conditions during two seasons (2018–2019 and 2019–2020). These experiments were carried out at 11 sites in the southern Argentinean Pampas, varying sowing date (22 Oct. to 5 Dec.), plant density (2–3 plants m−2), genotype (AX7784 and AX7761), and soil depth. Grain yield (3.2–11.9 Mg ha−1) was correlated with tillers productivity, mainly explained by postflowering precipitations. The contribution of tillers to grain yield was more proportional than their consequent yield depression at the main shoot. Tillers either increased (3 sites) or maintained (8 sites) grain yield, and their contribution increased as the environment improved without any detrimental effect in the most restrictive environments. Tillering has the potential for increasing resource (radiation, water, nitrogen) use efficiency under low plant density strategies adopted for restrictive environments. Core Ideas: Tillers either increased (3 sites) or maintained (8 sites) crop yield.Grain yield was correlated with tillers productivity, mainly explained by postflowering precipitations.Tiller contribution to grain yield was greater than the consequent yield depression of the main shoot.Tiller contribution to yield increased as the environment improved (high yield).Tillering has the potential for increasing resource use efficiency under low plant density strategies. [ABSTRACT FROM AUTHOR]

Increased soybean (Glycine max L. Merril) seed costs have motivated interest in reduced seeding rates to improve profitability while maintaining or increasing yield. However, little is known about the effect of early-season plant-to-plant spatial uniformity on the yield of modern soybean varieties planted at reduced seeding rates. The objectives of this study were to (i) investigate traditional and devise new metrics for characterizing early-season plant-to-plant spatial uniformity, (ii) identify the best metrics correlating plant-to-plant spatial uniformity and soybean yield, and (iii) evaluate those metrics at different seeding rate (and achieved plant density) levels and yield environments. Soybean trials planted in 2019 and 2020 compared seeding rates of 160, 215, 270, and 321 thousand seeds ha−1 planted with two different planters, Max Emerge and Exact Emerge, in rainfed and irrigated conditions in the United States (US). In addition, trials comparing seeding rates of 100, 230, 360, and 550 thousand seeds ha−1 were conducted in Argentina (Arg) in 2019 and 2020. Achieved plant density, grain yield, and early-season plant-to-plant spacing (and calculated metrics) were measured in all trials. All site-years were separated into low- (2.7 Mg ha−1), medium- (3 Mg ha−1), and high- (4.3 Mg ha−1) yielding environments, and the tested seeding rates were separated into low (< 200 seeds m−2), medium (200–300 seeds m−2), and high (> 300 seeds m−2) levels. Out of the 13 metrics of spatial uniformity, standard deviation (sd) of spacing and of achieved versus targeted evenness index (herein termed as ATEI, observed to theoretical ratio of plant spacing) showed the greatest correlation with soybean yield in US trials (R2 = 0.26 and 0.32, respectively). However, only the ATEI sd, with increases denoting less uniform spacing, exhibited a consistent relationship with yield in both US and Arg trials. The effect of spatial uniformity (ATEI sd) on soybean yield differed by yield environment. Increases in ATEI sd (values > 1) negatively impacted soybean yields in both low- and medium-yield environments, and in achieved plant densities below 200 thousand plants ha−1. High-yielding environments were unaffected by variations in spatial uniformity and plant density levels. Our study provides new insights into the effect of early-season plant-to-plant spatial uniformity on soybean yields, as influenced by yield environments and reduced plant densities. [ABSTRACT FROM AUTHOR]

Abnormal ear development in corn (Zea mays L.) has been reported for more than 100 years. More recently, in 2016, widespread abnormal multiple ears per stalk node (herein termed as multi‐ears), barbell ears, and short husks were reported in cornfields located in the western and central Corn Belt (Illinois, Iowa, Nebraska, and Kansas), Eastern Colorado, and the Texas Panhandle region in the United States. Little was known about the underlying causes of these abnormalities. A literature review examining conditions potentially affecting corn ear formation, yield, and abnormal ears was conducted. Several abnormal ear symptoms appear to be formed by stress conditions such as extreme weather, limited solar radiation, and responses to plant growth regulators. The accumulation of these effects can result in the abortion of primary ears and the development of secondary abnormal ears, which has been a hypothesis for the last 15 years. Whether or not primary ear abortion is one of the factors for abnormal ears remains a valid question. Abnormal ears can be understood as the result of an "expression triangle": susceptible genetics, conducive environmental conditions, and unfavorable management practices. Together, these factors can interact and cause abnormal ears and lower yields. Active knowledge gaps include the environmental and physiological pathways to abnormal ears, their impact on grain quality and yield, their effect on other processes such as dry‐down and harvest ease, and an in‐depth understanding of differing genetics, environment, and management. Core Ideas: Extreme weather, low solar radiation, and growth regulators can be some of the causes.Primary ear abortion has been observed to correlate with the occurrence of abnormal ears.Factors affecting corn ear formation and abnormal ears result in lower yields.Genetic × environment × management interactions affect ear formation, yield, and abnormal ears. [ABSTRACT FROM AUTHOR]

Over the past century of maize (Zea mays L.) breeding, grain yield progress has been the result of improvements in several other intrinsic physiological and morphological traits. In this study, we describe (i) the contribution of kernel weight (KW) to yield genetic gain across multiple agronomic settings and breeding programs, and (ii) the physiological bases for improvements in KW for US hybrids. A global-scale literature review concludes that rates of KW improvement in US hybrids were similar to those of other commercial breeding programs but extended over a longer period of time. There is room for a continued increase of kernel size in maize for most of the genetic materials analysed, but the trade-off between kernel number and KW poses a challenge for future yield progress. Through phenotypic characterization of Pioneer Hi-Bred ERA hybrids in the USA, we determine that improvements in KW have been predominantly related to an extended kernel-filling duration. Likewise, crop improvement has conferred on modern hybrids greater KW plasticity, expressed as a better ability to respond to changes in assimilate availability. Our analysis of past trends and current state of development helps to identify candidate targets for future improvements in maize. [ABSTRACT FROM AUTHOR]

Environmental characterization for defining the target population of environments (TPE) is critical to improve the efficiency of breeding programs in crops, such as sorghum (Sorghum bicolor L.). The aim of this study was to characterize the spatial and temporal variation for a TPE for sorghum within the United States. APSIM-sorghum, included in the Agricultural Production Systems sIMulator software platform, was used to quantify water-deficit and heat patterns for 15 sites in the sorghum belt. Historical weather data (∼35 years) was used to identify water (WSP) and heat (HSP) stress patterns to develop water–heat clusters. Four WSPs were identified with large differences in the timing of onset, intensity, and duration of the stress. In the western region of Kansas, Oklahoma, and Texas, the most frequent WSP (∼35%) was stress during grain filling with late recovery. For northeast Kansas, WSP frequencies were more evenly distributed, suggesting large temporal variation. Three HSPs were defined, with the low HSP being most frequent (∼68%). Field data from Kansas State University sorghum hybrid yield performance trials (2006–2013 period, 6 hybrids, 10 sites, 46 site × year combinations) were classified into the previously defined WSP and HSP clusters. As the intensity of the environmental stress increased, there was a clear reduction on grain yield. Both simulated and observed yield data showed similar yield trends when the level of heat or water stressed increased. Field yield data clearly separated contrasting clusters for both water and heat patterns (with vs. without stress). Thus, the patterns were regrouped into four categories, which account for the observed genotype by environment interaction (GxE) and can be applied in a breeding program. A better definition of TPE to improve predictability of GxE could accelerate genetic gains and help bridge the gap between breeders, agronomists, and farmers. [ABSTRACT FROM AUTHOR]

Intensive study for more than 100 yr has resulted in a good understanding of corn's (Zea mays L.) growth and development. However, abnormal development of ears in corn was reported in several U.S. states, including Texas, Colorado, Kansas, Nebraska, Iowa, and Illinois, during 2016, stretching our understanding. A comprehensive review of the literature was conducted to identify abnormal ears' symptoms, causes, and timing of development. This study aimed to (a) describe and summarize previously reported ear symptoms, (b) document recent widespread symptoms of major concern, and (c) describe our current understanding of the potential cause(s) and expected development timing for abnormal ears. In total, 10 previously reported symptoms of corn ears were found, including tassel, fasciated, arrested, pinched, blunt, silk‐balled, incomplete kernel set, banana‐shaped, zipper, and tipped‐back. Three additional recent widespread symptoms of major concern associated with significant yield reduction across a wide area in 2016 were described: multi‐ears, barbell‐ears, and short‐husk ears. The information available on several of the symptoms was limited, and the specific causes were unknown, highlighting the need for more research in this area. Despite this and based on existing knowledge, possible causal factors and postulated development timing (i.e., when the stress may have occurred) are presented for all symptoms. Abnormal ear development can be seen as the response to complex interactions among genetics, environment, and management practices. Ear abnormalities are detrimental to grain yield and quality, and their mitigation is imperative to efficient corn systems, crop resiliency, and sustainability. Core Ideas: Abnormal ears are a likely response to G × E × M interactions.Ten previously reported abnormality symptoms are discussed.Three recent widespread symptoms of major concern associated with lower yields are included.Abnormal ears can reduce grain yield and quality.The understanding and mitigation of abnormal ears are imperative for sustainable agriculture. [ABSTRACT FROM AUTHOR]

Genomic prediction provides an efficient alternative to conventional phenotypic selection for developing improved cultivars with desirable characteristics. New and improved methods to genomic prediction are continually being developed that attempt to deal with the integration of data types beyond genomic information. Modern automated weather systems offer the opportunity to capture continuous data on a range of environmental parameters at specific field locations. In principle, this information could characterize training and target environments and enhance predictive ability by incorporating weather characteristics as part of the genotype-by-environment (G×E) interaction component in prediction models. We assessed the usefulness of including weather data variables in genomic prediction models using a naïve environmental kinship model across 30 environments comprising the Genomes to Fields (G2F) initiative in 2014 and 2015. Specifically four different prediction scenarios were evaluated (i) tested genotypes in observed environments; (ii) untested genotypes in observed environments; (iii) tested genotypes in unobserved environments; and (iv) untested genotypes in unobserved environments. A set of 1,481 unique hybrids were evaluated for grain yield. Evaluations were conducted using five different models including main effect of environments; general combining ability (GCA) effects of the maternal and paternal parents modeled using the genomic relationship matrix; specific combining ability (SCA) effects between maternal and paternal parents; interactions between genetic (GCA and SCA) effects and environmental effects; and finally interactions between the genetics effects and environmental covariates. Incorporation of the genotype-by-environment interaction term improved predictive ability across all scenarios. However, predictive ability was not improved through inclusion of naive environmental covariates in G×E models. More research should be conducted to link the observed weather conditions with important physiological aspects in plant development to improve predictive ability through the inclusion of weather data. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) grain yield response to plant density is inconsistent, and the mechanisms driving this response are unclear. A better understanding of the factors governing this relationship could improve plant density recommendations according to specific environmental and genetics characteristics. Therefore, the aims of this paper were to: i) execute a synthesis-analysis of existing literature related to yield-plant density relationship to provide an indication of the need for different agronomic optimum plant density (AOPD) in different yield environments (YEs), and ii) explore a data set of field research studies conducted in Kansas (USA) on yield response to plant density to determine the AOPD at different YEs, evaluate the effect of tillering potential (TP) on the AOPD, and explain changes in AOPD via variations in wheat yield components. Major findings of this study are: i) the synthesis-analysis portrayed new insights of differences in AOPD at varying YEs, reducing the AOPD as the attainable yield increases (with AOPD moving from 397 pl m-2 for the low YE to 191 pl m-2 for the high YE); ii) the field dataset confirmed the trend observed in the synthesis-analysis but expanded on the physiological mechanisms underpinning the yield response to plant density for wheat, mainly highlighting the following points: a) high TP reduces the AOPD mainly in high and low YEs, b) at canopy-scale, both final number of heads and kernels per square meter were the main factors improving yield response to plant density under high TP, c) under varying YEs, at per-plant-scale, a compensation between heads per plant and kernels per head was the main factor contributing to yield with different TP. [ABSTRACT FROM AUTHOR]

Record grain yields and increased awareness of climate variability have more producers considering intensive (i.e., high-input) wheat (Triticum aestivum L.) management. This study investigated soft winter wheat response to several agronomic inputs across intensive and traditional (i.e., low-input) management systems. Sulfur (S) deficiency can severely limit maize (Zea mays L.) yield. This deficiency could be predicted by quantifying the S concentration (SC) in the shoot biomass (BM) and by calculating the S nutrition index (SNI = observed SC/critical SC). However, as shoot SC determination is laborious, alternative S diagnostic methods should be developed in maize. Thus, the objectives of our study were to: (i) determine and validate a critical S dilution curve, (ii) quantify the critical SNI, and (iii) explore the use of SC and chlorophyll meter reading (CMR), both determined in the uppermost developed leaf at vegetative growth stages, to predict SNI and for diagnosing S status in maize. Six field studies evaluating fertilizer S rates were executed, collecting maize shoot and uppermost developed leaf samples and determining SC, CMR, yield, and SNI parameters. The main outcomes from our study were: (i) a maize critical S dilution curve was fitted (SC = 2.13BM-0.23) and validated with an independent dataset; (ii) a critical SNI threshold of 0.79 adequately diagnosed S status at ~V6 stage; (iii) at V6, SNI was linearly related to SC (R² = 0.65) and CMR (R² = 0.85). As a result, a threshold value of 2.0 g S kg-1 for SC, 47.5 units for CMR, and 0.94 units for relative CMR can be used to successfully diagnose S deficiencies at early vegetative (~V6) maize stages. Future studies testing S diagnostic tools for maize should be performed in environments with severe S deficiency and nutrient co-limitations. [ABSTRACT FROM AUTHOR]

Identifying an optimal plant density is a critical management decision for corn (Zea mays L.) production. The main objectives of this study were to: (i) investigate the grain yield responses to plant density (yield-density relationship), (ii) identify best fitted yield-density response curves, and (iii) explore genotype (G) x environment (E) interaction effect on yield-density response models. Analysis was conducted on meta-data (124,374 observations) gathered from 22 US states and 2 Canadian provinces, diverse sites (E), for years from 2000-2014 on multiple hybrids (G). Yield data were further grouped into four yield environments (low [LY], <7 Mg ha-1; medium [MY], 7-10 Mg ha-1; high [HY], 10-13 Mg ha-1; and very high [VHY], >13 Mg ha-1 yielding groups). Primary outcomes from this analysis were: (1) strong G x E interaction; (2) a quadratic model best fitted yield-density relationship; (3) four contrasting yield-density responses identified as dominant in each yield productivity environment, i.e., a declining, a constant, an increasing, and ever-increasing type; (4) the yield productivity environment varied for the different corn comparative relative maturity (CRM) groups, i.e., the LY environment for long-maturing hybrids matched with a MY or HY environment for short maturing hybrids; and (5) maximum yielding plant density (MYPD) was lower but maximum yield was greater for long- versus short-maturing hybrids. In summary, optimal plant density should be decided based on detailed G x E analysis of production conditions that include factors such as CRM, yield productivity environment (weather-soil x management practices), and site information. [ABSTRACT FROM AUTHOR]

Twin-row planting systems in maize (Zea mays L.) have been proposed as an alternative spatial arrangement that should theoretically decrease plant-to-plant competition, alleviate crop crowding stress and improve yields. Uncertainty remains, however, as to whether twin rows are a feasible option to increase plant densities and improve grain yields. Three hybrids (DKC62-54, DKC61-19, and DKC57-66) were grown from 2009 to 2011 to evaluate the individual and interacting effects of plant density (PD1 = 69,000; PD2 = 81,000; PD3 = 93,000; and P D 4 = 105,000 plants [pi] ha-1 ) and spatial configuration (conventional single 76-cm row width vs. 20-cm twin rows spaced 76-cm between paired-rows) on dark prairie soil in West- Central Indiana. The primary research objectives were to determine (i) whether the twin-row spatial arrangement permits higher optimum plant densities, (ii) whether hybrids vary in their response to at win-row arrangement, and (iii) diverse morphophysiological trait responses to density and spatial treatments. Twin rows never yielded significantly more than single rows at any plant density or hybrid combination in any year of this study. Furthermore, there was no evidence that grain yield-optimizing plant densities were any higher with twin vs. single rows in any hybrid. Twin rows slightly increased leaf area index (LAI) at silk emergence stage in 2010 (mean LAI = 4.8) and 2011 (mean LAI = 4.0), but not in 2009 (mean LAI = 4.4). Despite higher plant spacing variation, radiation interception was initially favored by earlier canopy closure with twin-row planting, but the relative radiation-interception advantage declined as plant density increased and at a later vegetative stage. [ABSTRACT FROM AUTHOR]

• New synthesis-analysis offers insights on trends in wheat N utilization efficiency. • A nonlinear model explained wheat grain yield as a function of N uptake (i.e. NUtE). • There are greater opportunities to increase NUtE in fall- than winter-sown wheat. • Increases in NUtE originated from dilution of grain protein concentration. • Identifying the determinants of NUtE will increase yield limited by N uptake. Understanding factors underpinning the variability in nitrogen (N) utilization efficiency (NUtE) [i.e. grain yield per unit of N uptake at maturity (Nup MAT)] is critical to direct future improvements in breeding and agronomic management. To our knowledge, no study has summarized changes in wheat NUtE across a wide range of experimental conditions. We performed a synthesis-analysis using published data to provide a global perspective of NUtE trends in wheat by (i) benchmarking against yield limited by Nup MAT , and (ii) assessing factors contributing to the variation in NUtE. The final database encompassed 55 studies (n = 529). A nonlinear model explained yield as a function of Nup MAT. The gap between actual yield and Nup MAT -limited yield was negligible at the lowest range of Nup MAT and increased to ∼2000 kg ha−1 as Nup MAT levels increased. Hence, opportunities to enhance yield through improving NUtE would be more likely at greater-than-average yield and Nup MAT levels. The negative correlation between grain protein concentration and the residuals between NUtE and Nup MAT indicated a challenge to increase yield without penalizing grain protein. Further, there are greater opportunities to increase NUtE in fall- than winter-sown wheat. Identifying the determinants of NUtE will enable to narrow the gap between actual and Nup MAT -limited yields. [ABSTRACT FROM AUTHOR]

The utilization of crop nitrogen (N) status as an in-season diagnosis tool for predicting N needs to maximize grain yield (GY) is a well-established concept in agronomy. However, a cross-species comparison including the characterization of yield components, grain number (GN) and grain weight (GW), to understand the physiological basis behind the GY-crop N status relationship is still missing. The main goal of this study was to perform a cross-species comparison for maize (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) of the relationship between crop N status around anthesis as a GY and GY components prediction diagnosis method. A systematic literature search was carried out for these major field crops, the final dataset (comprising 629 observations) consisted of 15 publications including information on i) shoot biomass and plant N concentration or N nutrition index (NNI) values at anthesis, ii) GY, and iii) GN and/or GW. An analysis was conducted to assess the sensitivity (slope of the linear models) of GY, GN, and GW to changes in crop NNI status at anthesis. Notably, the crop N status at anthesis demonstrated a strong relationship between both GY (R2 between 0.66 and 0.93) and GN (R2 between 0.58 and 0.94) across all crops, with a slightly weaker relationship with GW (R2 between 0.30 and 0.83). Considerable uncertainty was observed on the GY and GN sensitivity (S) to N deficiency across all crops. Maize showed the greatest sensitivity of GY to NNI (S = 964 g m−2), with lowest sensitivity for wheat crop (S = 496 g m−2). Regarding GN, rice showed the greatest sensitivity to NNI (S = 23859 GN m−2), whereas maize was less sensitive (S = 2673 GN m−2). While maize exhibited a positive association between NNI and GW (although with considerable uncertainty), this relationship was less evident for rice and wheat crops. Our findings demonstrated that crop N status at anthesis is a better predictor of GY and GN than GW in maize, rice, and wheat. Maize showed the greatest range in observed values for relative GW relative to NNI, highlighting the impact of crop N status on GW determination. These findings contribute to improving the understanding of the importance of achieving adequate crop N status at anthesis as key aspect for yield formation, with implications for both breeding programs and the optimization of on-farm crop N management. • Crop N status at anthesis showed a strong relationship with grain number. • Maize showed the greatest sensitivity of grain yield to NNI at anthesis. • Rice showed the greatest sensitivity of grain number to NNI at anthesis. • Maize showed the greatest responses of grain weight to crop N status at anthesis. [ABSTRACT FROM AUTHOR]

The photoassimilates and nitrogen (N) allocation in grain crops can be studied via the harvest index (HI) and the N harvest index (NHI). These two variables should be considered in breeding programs seeking more effective use of resources in maize (Zea mays L.) and other grain crops. Molecular biotechnology has emerged as a complement to improve not only maize grain yield but also resource utilization efficiency. A recent study reported a beneficial impact of increasing and extending the expression of a maize MADS-box transcription factor (zmm28) on the NHI. This research aimed to further identify enhancements of C-N partitioning (HI, NHI) in DP202216 maize hybrids recognizing the main physiological and morphological traits associated to the C-N dynamics via in-season intra-canopy measurements. Two DP202216 elite hybrids were evaluated with their respective wild-type (WT) controls during two field growing seasons under two N regimes. The N nutrition index (NNI), as crop N status, was quantified to avoid misinterpretations of the results. The DP202216 trait showed, on average, a ∼6% increase in the HI with a concomitant positive impact of ∼9% in the NHI across hybrids, N regimes, and seasons. Those increases were consistent at different crop NNI. After accounting for the NNI, it was shown that the increases in both HI and NHI were supported by the accumulation of more N in leaves (mainly in both lower and middle sections of the canopy vertical profile) and more water-soluble carbohydrates (WSC) in stems before flowering, combined with more aggressive post-anthesis remobilization. In this study, it was shown an increase in the efficient use of crop resources in DP202216 hybrids with respect to their isogenic WT controls at similar NNI via increments in C and N partitioning (HI and NHI). This physiological and morphological understanding of C- and N-related traits addressed the challenge of optimizing the effective use of resources in maize breeding programs. To better understand traits by management interactions with yield and yield stability, DP202216 hybrid evaluations across a broad range of commercially relevant N scenarios would be valuable. • Zmm28 hybrids increased both the harvest index (HI) and nitrogen HI (NHI). • Zmm28 hybrids displayed more leaf N and stem water-soluble carbohydrates (WSC) accumulation. • The increase in HI and NHI was supported by greater WSC (stem) and N (leaf and stem) remobilization. • This study provides knowledge for optimizing the effective use of resources in grain crops. [ABSTRACT FROM AUTHOR]

A comparative analysis of grain yield performance of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) under different environments constitutes a way to identify restrictions in yield formation between both crop species. However, most of the previous studies on these field crops have been carried out in Mediterranean environments. This study aims to compare the grain yield performance of wheat and barley across a wide range of temperate environmental conditions. Wheat and barley yield databases from the national network of cultivar evaluation of Argentina were assembled. The database included 191 wheat cultivars (with early-, mid- and late-flowering length cycle), 140 barley cultivars, and 44 combinations of sites and years of the Argentine wheat and barley belt region. Average heading date variation among environments and crops was no more than 10 days. Crop grain yield comparisons were carried out using a regression analysis, benchmarking within each site-year the grain yield of each cultivar against the average grain yield of all crop cultivars (i.e., environmental index). There were no differences in grain yield between wheat and barley for all data, but the behavior between crop species changed with the length of the wheat cycle (i.e., early-, mid-, or late-flowering cultivars). Barley portrayed a greater grain yield than early-flowering wheat under low-yielding environments (< 6060 kg ha−1), but this advantage vanished as the yield environment improved. Mid-flowering wheat showed a similar grain yield to barley across temperate environments. Lastly, late-flowering wheat outperformed barley mainly in high-yielding environments (> 6138 kg ha−1). Grain number m−2 was the main numerical component that explained variability in grain yield. The relative contribution of the yield numerical components differed between species, having barley lower grain number m−2 but a greater grain weight than wheat. The comparison of the grain yield performance between species represents a strategy to adjust the rotation system, being a critical factor in considering the variability in the crop growth cycle. • Yield performance offers valuable insights to select the best crop option into the right environment. • Wheat and barley have similar grain yield performance when they have similar cycle duration. • Barley outyielded early-flowering wheat (shorter season) in low-yielding environments (< 6 Mg ha−1). • Late-flowering wheat (longer season) outyielded barley in high-yielding environments (> 6 Mg ha−1). • Yield variations were governed by changes in grain number per unit area for both crop species. [ABSTRACT FROM AUTHOR]

In the temperate-humid region of Argentina, nitrogen (N) fertilisers in maize (Zea mays L.) are mainly applied around sowing, whereas N-splitting is rare and occurs during early vegetative stages. Splitting and late N fertilisation, even up to silking (R 1), effects on yield have been recently studied. However, to the extent of our knowledge, these studies have mainly focused on the effect of these strategies on maize yield, but less on the crop N economy. The aims were to study the mechanisms explaining the effect of i) splitting N and ii) additional N application at R 1 on yield, post-flowering N uptake, kernel weight, N uptake efficiency, and the relationship of these variables with the N nutrition index (NNI). Seven experiments were carried out throughout the humid temperate region of Argentina, evaluating seven treatments: a control without N fertilisation, N rate entirely applied at sowing or split between sowing, eight leaf (V 8), and R 1 , an additional N rate at R 1 , and an N sufficiency treatment. The scenario with split N application had no adverse effect on either yield or N uptake at maturity (P > 0.05), with less pre-flowering N uptake compensated with more post-flowering N uptake in late N applications. In turn, increases in both yield and kernel weight were related to increases in post-flowering N uptake. Positive yield responses to N-splitting (plateauing at 450 kg ha-1) were obtained with yield responses to N greater than 3107 kg ha-1. Likewise, yield responses to additional N at R 1 (plateauing at 1107 kg ha-1) were evident with yield responses greater than 2943 kg ha-1. The NNI at R 1 accounted for variations in post-flowering N uptake and yield, as well as yield responses to additional N at R 1 and their impact on kernel weight. Results show that N-splitting and late N fertilisation are promising strategies that, combined with crop N status monitoring, could lead to improvements in both maize yield and N economy. • Split and late N fertilisations were evaluated for maize in the humid-temperate region of Argentina. • Grain yield (GY) responses to N-splitting and to additional N at R 1 were recorded. • GY responses to N-splitting and to additional N at R 1 were higher for the most responsive sites. • N-splitting did not reduce GY and increased N uptake efficiency. • GY response to additional N at R 1 was negatively associated with crop N status at R 1. [ABSTRACT FROM AUTHOR]

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics. [ABSTRACT FROM AUTHOR]

Pearl millet (Pennisetum glaucum R. Br.) water-limited yield gap in Senegal is estimated at 2.2 Mg ha-1. Proper variety and management selection are critical to the sustainable intensification of millet systems. The objectives of this study were to assess the effect of two pearl millet varieties and different crop management (plant density-nutrient rates) treatments on i) biomass yield, ii) grain yield, and iii) farm profit magnitude and responsiveness. The study was conducted on three sites during the 2017, 2018, and 2019 growing seasons with a total of nine site-years. Two varieties, Souna 3 (traditional) and Thialack 2 (dual-purpose), and 48 management treatments including two plant densities (37–74 × 1000 plants ha-1) and 24 different levels of nutrient combinations ranging from 0 to 149 kg ha-1 nitrogen (N, as urea), 0–67 kg ha-1 phosphorus (P 2 O 5 , as double super phosphate), 0–33 kg ha-1 potassium (K 2 O, as potassium chloride) and 0–14 987 kg ha-1 cow manure (M), were tested in all site-years. Thialack 2 presented greater biomass yield in three and grain yield in four site-years (out of nine site-years) relative to Souna 3. Management treatments with greatest magnitude and responsiveness produced on average 4.6 Mg ha-1 biomass yield with averaged nutrient rates of 102–37–26 NPK, 2 Mg ha-1 grain yield with averaged nutrient rates of 91–32–24 NPK, 682 USD ha-1 profit at low biomass and grain prices with averaged nutrient rates of 72–22–21 NPK, and 1183 USD ha-1 profit at high biomass and grain prices with averaged nutrient rates of 83–29–22 NPK, all at 74 thousand plants ha-1, regardless of variety used. Five to seven management practices were able to concurrently optimized biomass yield, grain yield, and farmer profit. Sustainably intensifying pearl millet systems by using improved variety and management practices have great potential to promote greater yields and farm profitability in Senegal. • New pearl millet varieties can be used for biomass and grain production. • Yield response and magnitude is driven by environmental conditions. • Greater plant density and nutrient application rates improve pearl millet yield. • Farm profit can be optimized with greater plant density and modest nutrient rates. • Pearl millet in Senegal has potential to be profitably intensified. [ABSTRACT FROM AUTHOR]

Delayed sowing date of maize (Zea mays L.) has become a broadly adopted practice in the Pampas region of Argentina, because late-sown crops frequently experience a more favorable water balance around flowering and a reduction in the year-to-year yield variation. However, breeding efforts in this region have been focused on early sowing date environments. In addition, there has been no research on genetic progress of grain yield and the underlying attributes under late-sowing conditions. The aim of this study was to compare genetic progress in grain yield and secondary traits for hybrids released between 1980 and 2016 when grown in early- versus late sowing environments in the central Pampas region. Grain yield, its components (kernel number and kernel weight), and its physiological determinants (total shoot biomass and harvest index) were assessed in two contrasting sowing dates during three years. Biomass at silking (B R1) and during the post-silking period (B R1-R6), plant growth rate and source-sink ratios during the critical and the effective kernel-filling periods were also analyzed. Grain yield genetic progress was similar for early (0.9% y-1) relative to late sowing dates (0.8% y-1). Kernel number increase with the year of release (YOR) was more important in early (0.6% y-1) than in late (0.4% y-1) sowings, whereas the opposite trend was documented for kernel weight (0.2% and 0.3% y-1, respectively). Newer hybrids showed greater biomass production in both sowing dates (0.8% y-1 for early, 0.6% y-1 for late) and a slight increase in harvest index in late sowings (0.2% y-1). Breeding effects on shoot biomass production were exclusively attributed to the post-silking period (1.2% y-1 for early and 0.9% y-1 for late), as B R1 remained unchanged with YOR. Assimilate availability per kernel during the effective kernel filling increased with YOR in both sowing dates (1.0% y-1 for early and 0.9% y-1 for late), promoting a longer kernel filling duration. Results demonstrated that breeding efforts focused on early sowings as the main target environment, have also impacted yield gains in late sowings. However, the enhanced importance of kernel weight on grain yield determination among late- than among early sowings will demand future breeding strategies to pay special attention to unfavorable photothermal conditions during kernel filling. • Grain yield genetic progress was similar for early and late sowing dates. • The relative importance of kernel number and kernel weight on yield gains varied with sowing date. • Newer hybrids showed greater post-silking biomass production in both environments. • Post-silking source-sink ratio increased with year of release, promoting a longer kernel filling. [ABSTRACT FROM AUTHOR]

Nitrogen (N) metabolism is a major research target for increasing productivity in crop plants. In maize (Zea mays L.), yield gain over the last few decades has been associated with increased N absorption and utilization efficiency (i.e. grain biomass per unit of N absorbed). However, a dynamical framework is still needed to unravel the role of internal processes such as uptake, allocation, and translocation of N in these adaptations. This study aimed to 1) characterize how genetic enhancement in N efficiency conceals changes in allocation and translocation of N, and 2) quantify internal fluxes behind grain N sources in two historical genotypes under high and low N supply. The genotypes 3394 and P1197, landmark hybrids representing key eras of genetic improvement (1990s and 2010s), were grown under high and low N supply in a two-year field study. Using stable isotope 15N labelling, post-silking nitrogen fluxes were modeled through Bayesian estimation by considering the external N (exogenous-N) and the pre-existing N (endogenous-N) supply across plant organs. Regardless of N availability, P1197 exhibited greater exogenous-N accumulated in leaves and cob-husks. This response was translated to a larger amount of N mobilized to grains (as endogenous-N) during grain-filling in this genotype. Furthermore, the enhanced N supply to leaves in P1197 was associated with increased post-silking carbon accumulation. The overall findings suggest that increased N utilization efficiency over time in maize genotypes was associated with an increased allocation of N to leaves and subsequent translocation to the grains. • Bayesian modelling and 15N analysis were combined to estimate N allocation in maize. • Modern maize plants evidenced an improved post-silking N partitioning to leaves. • Greater N allocation to leaves resulted in an increased post-silking carbon fixation. • Internal translocation to the grains was improved due to larger supply from leaves. [ABSTRACT FROM AUTHOR]

• Attainable maize yield drives the agronomic optimum of initial N availability (AONav). • Soil texture modifies the curvature of the response models but not the AONav. • For yield environments from 9 to 14 Mg ha-1, the AONav increases by 21 kg N Mg-1. • Fine- and coarse-textured soils show the greatest and the lowest response rates to N. • We could maintain high N use efficiencies by correctly identifying yield environment. The most widely used approach for prescribing fertilizer nitrogen (N) recommendations in maize (Zea Mays L.) in Argentina is based on the relationship between grain yield and the available N (kg N ha−1), calculated as the sum of pre-plant soil NO 3 --N at 0−60 cm depth (PPNT) plus fertilizer N (N f). However, combining covariates related to crop N demand and soil N supply at a large national scale remains unexplored for this model. The aim of this work was to identify yield response patterns associated to yield environment (crop N demand driver) and soil texture (soil N supply driver). A database of 788 experiments (1980−2016) was gathered and analyzed combining quadratic-plateau regression models with bootstrapping to address expected values and variability on response parameters and derived quantities. The database was divided into three groups according to soil texture (fine, medium and coarse) and five groups based on the empirical distribution of maximum observed yields (from Very-Low = <8.5 Mg ha−1 to Very-High = >13.1 Mg ha−1) resulting in fifteen groups. The best model included both, attainable yield environment and soil texture. The yield environment mainly modified the agronomic optimum available N (AON av), with an expected increase rate of ca. 21.4 kg N Mg attainable yield−1, regardless of the soil texture. In Very-Low yield environments, AON av was characterized by a high level of uncertainty, related to a poor fit of the N response model. To a lesser extent, soil texture modified the response curvature but not the AON av , mainly by modifying the response rate to N (Fine > Medium > Coarse), and the N use efficiencies. Considering hypothetical PPNT levels from 40 to 120 kg N ha−1, the expected agronomic efficiency (AEN f) at the AON av varied from 7 to 31, and 9–29 kg yield response kg fertilizer N (N f)−1, for Low and Very-High yield environments, respectively. Similarly, the expected partial factor productivity (PFPN f) at the AON av ranged from 62 to 158, and 55–99 kg yield kg N f −1, for the same yield environments. These results highlight the importance of combining attainable yield environment and soil texture metadata for refining N fertilizer recommendations. Acknowledging the still low N fertilizer use in Argentina, space exists to safely increasing N fertilizer rates, steering the historical soil N mining profile to a more sustainable agro-environmental scenario in the Pampas. [ABSTRACT FROM AUTHOR]

• Inconsistent L N fertilization responses were observed across experiments. • Post-silking N uptake (NU Post-Silking) is suggested as an indicator for differential responses to L N. • Nitrogen nutrition index (NNI SILKING) was related with NU Post-Silking changes. • Nitrogen recovery efficiency was enhanced by the utilization of L N fertilization, when properly adopted. Late-season fertilizer N applications in maize (Zea mays L.) is a tactical agronomic practice that seeks to improve the synchrony between plant N demand and soil N supply. While this management practice can increase yield and limit unintended environmental impacts, a quantitative synthesis of the effects of late N applications on grain yield and resource use efficiency is lacking. A meta-analysis was conducted to identify patterns of yield response to late-N fertilization (post tenth-leaf, V10) across site-years studies. The goals of this study were to: 1) quantify the effect of late-season N fertilization on maize yield; and 2) identify an indicator for decision support of late-N fertilization. Published and unpublished sources from 1983 until 2018 were included in the meta-analysis (14 studies; n = 625 treatment means). Early-season (E N , ≈ 100% of fertilizer applied prior to the sixth-leaf, V6) and late-season (L N , < 50% N applied before V10) N fertilization were compared to determine the effect of application timing on yield, N uptake, and N recovery efficiency (REN, N uptake increase per unit of N applied). Across studies, the timing of application of N was not associated with a quantifiable change in maize yield. Due to significant heterogeneity across experiments (I2 = 48%), there is an opportunity to explore plausible effects of the practice when N is limiting (L N improved yield) on yield and effective use of N. Increased post-silking N uptake (>28% of N uptake at maturity occurring after silking) was positively related with yield increases for L N (+577 kg ha−1), and the contrast in REN between L N and E N was 0.04 kg kg−1. Environments prone to a greater N uptake during reproductive stages are proposed to be more suitable for late N applications. Prediction algorithms to inform tactical N management that can both increase productivity and sustainability could be developed provided adequate links between late-season N uptake and growing-season indicators could be established. [ABSTRACT FROM AUTHOR]