Quadratic Plateau Research Articles

Climate change induced heat and drought stress hamper climate change mitigation in German cereal production

ContextAgricultural production and climate change strongly influence each other and there are significant efforts to minimize negative impacts in both directions. In particular, breeding progress has succeeded in reducing the carbon footprint (CFP) of cereals over time. However, there is widespread certainty that climate change-related weather extremes have led to stagnation of cereal yields in many global production regions. Research questionWe assume that climate change-related yield stagnation is also evident in variety trials in Germany, which has to date only been shown for on-farm yields. Furthermore, we expect that the stagnation in yields also leads to a stagnation in the downward trend of CFP, and that heat and drought stress in particular increase the CFP of cereals. In addition, we hypothesize that the site-specific soil quality largely determines stress induced increases in CFP. MethodsWe conduct a partial life cycle assessment (LCA) with German variety trial data from 1993 to 2021 and determine the greenhouse gas emissions per unit of land (GHGL), as well as the CFP of winter wheat, winter rye, and winter barley. Further, we evaluate the time trends of yield, GHGL, and CFP using linear and quadratic plateau models. In addition, we calculate spatio-dynamic weather indices (WIs) for moderate, severe and extreme heat and drought stress. Using mixed models, we estimate the explanatory power and effect size of heat and drought WIs on the CFP. Finally, we present the spatial differences of heat and drought on the CFP at different soil qualities. ResultsWe show yield plateaus in all crops and stagnating GHGL trends, resulting in a stagnation of the downward trend of CFP, especially for rye and barley. We highlight that heat and drought increase the CFP of all crops. However, the impact of heat and drought on the CFP varies greatly with soil quality across all crops. ConclusionsWe conclude that climate change-induced weather extremes are major challenges not only for cereal production and food security but also for climate change mitigation in the agricultural sector, highlighting the importance of high-yield locations, alongside variety selection and resource-efficient management, for climate change mitigation. SignificanceThis study is the first that proves significant yield stagnation in German variety trials. Moreover, this study is the first to analyze the impact of heat and drought stress on cereal CFP, with novel results that proof that climate adaptation will become a crucial aspect of climate change mitigation in field crops.

A new scenario framework for equitable and climate-compatible futures

ABSTRACT This paper demonstrates a modelling approach and scenario framework for global burden-sharing, that foregrounds questions of climate and energy justice. We classify 134 countries into four development categories based on thirteen indicators. Using the quadratic plateau model, we estimate that an energy threshold of 94 GJ and an income threshold of USD 28,500 are necessary for meeting sustained levels of development in health, education, and infrastructure. We construct baseline scenarios for convergence to these and other threshold values drawn from the literature. Emissions constraints are then imposed in the form of the remaining carbon budget corresponding to the temperature targets of the Paris Agreement to assess the degree of energy-emissions and energy-GDP decoupling required to meet them. Our results show that limiting warming to 1.5°C requires higher effort across all regions, with the global effort remaining similar across scenarios. However, the distribution of the global effort across development categories varies significantly, depending on whether energy and climate equity are considered. The mitigation burden for the highest development category is almost six times higher if climate equity is considered. In contrast, the effort required by the least developed category is doubled if climate equity is compromised.

Models and sufficiency interpretation for estimating critical soil test values for the Fertilizer Recommendation Support Tool

AbstractSoil test correlation determines whether a soil test can be used to predict the need for fertilization based on the critical soil test value (CSTV). Our objectives were to compare the CSTV estimated from five combinations of correlation models and yield sufficiency interpretations and to select one method for soil test correlation performed with the Fertilizer Recommendation Support Tool (FRST). Four models were fit to three datasets with strong (Mehlich‐1 K), moderate (Mehlich‐3 K), or weak (Olsen P) correlations between soil test P or K and crop relative yield. We tested the arcsine‐log calibration curve (ALCC), exponential (EXP), linear plateau (LP), and quadratic plateau (QP) models. The CSTV was defined as 95% of the maximum predicted yield for the ALCC and EXP methods, the join point for LP, and both the join point and 95% of the maximum for the QP providing five CSTV predictions. The five CSTVs ranged from 46 to 66 mg kg−1 for the Mehlich‐1 K dataset, 115 to 165 mg kg−1 for the Mehlich‐3 K dataset, and 7 to 16 mg kg−1 for the Olsen P dataset. Ten pairwise comparisons showed the estimated CSTV was numerically and sometimes statistically influenced by the model and sufficiency level interpretation. Despite differences among CSTVs, the frequency of significant yield responses above and below the predicted CSTV was generally comparable among the methods, with false‐negative errors occurring at 0%–18% of sites for a given dataset. The QP model with a CSTV at 95% of the predicted maximum was selected as the modeling approach for FRST.

Soil biological and physical measurements did not improve the predictability of corn response to phosphorus fertilization

AbstractIncluding soil health and physical measurements with traditional soil fertility measurements has the potential to improve corn (Zea mays L.) P fertilizer recommendations. The objectives for this study were to (1) evaluate the accuracy of current South Dakota corn P recommendations in predicting yield increases and (2) determine if the predictability of yield response to P fertilization improves by including selected soil biological, physical, and chemical measurements. This project was conducted in central and eastern South Dakota from 2019 to 2022 at 117 experimental sites that varied in management, landform, and soil type. A treatment of 48.9 kg P2O5‐P ha−1 was compared to a control with no P fertilizer. Soil samples (0–15 cm) collected before fertilization were analyzed for selected soil physical, chemical, and biological parameters. Analysis suggested that the current critical P value of 16 mg Olsen‐P kg−1 was still accurate as it was still within the 68% confidence interval for the linear (12–19 mg kg−1) and quadratic plateau (16–26 mg kg−1) models. Using the critical value of 16 mg Olsen‐P kg−1, we correctly predicted P responsiveness 70% of the time. The accuracy of predicting P responsiveness was not further improved by considering selected enzymes, permanganate oxidizable C, soil respiration, total C, or total N, but was improved by considering pH, soil organic matter, and apparent cation exchange capacity. Therefore, the use of typical soil fertility measurements without soil physical and biological measurements is currently the best option for predicting the responsiveness of corn to P fertilization in South Dakota.

From a point to a range of optimum estimates for maize plant density and nitrogen rate recommendations

AbstractThe interaction between nitrogen (N) rate, plant density, and hybrid on net return to seed and fertilizer cost remains unknown but important to be addressed given the multi‐input decision process corn growers make every year. We collected grain yield from a factorial experiment with five N rates (0–291 kg N ha−1), five plant densities (3.7–11.4 plants m−2), and four hybrids (old vs. new) over 2 years in Iowa. Data were sufficiently modeled with a quadratic plateau model with continuous covariate terms to include N × plant density interactions (R2 = 0.925, n = 387). We found a wide range of plant densities (6.7–8.4 plants m−2) and N rate (150–212 kg N ha−1) combinations to achieve 99% of the maximum net revenue. The economic optimum N rate increased with increasing plant density from 4 to 7 plants m−2. The fundamental relationships between grain yield response to N fertilizer and plant density were similar across old and new hybrids; however, the absolute values were different, with newer hybrids having 20% higher economic optimum N rate and 23% higher yield than the older hybrids. We concluded that by accounting for two inputs into the revenue equation, a larger range of combinations was found to achieve 99% of the maximum net revenue. Our study offers new insights into N rate by plant density by hybrid interaction to assist future research.

Nitrogen fertilizer and pronitridine rates for corn production in the Midwest U.S.

ContextReducing nitrogen (N) losses can be accomplished by applying recommended N rates and using nitrification inhibitors (NI). In some agricultural systems, managing N application rate or using a NI could improve N use efficiency and increase crop yields. ObjectiveThe objectives of this 13 site-year study were to determine the agronomic optimum N rate (AONR) application rate using linear plateau and quadratic plateau models, determine the optimum pronitridine rate when applied with 70 % of the recommended N amount, and evaluate the effect of nitrapyrin and pronitridine on corn (Zea mays L.) yield. MethodsIn this experiment, pronitridine and nitrapyrin were used as NIs and were applied in the fall and spring. This research was conducted in the US in Illinois (IL), Missouri (MO), and Nebraska (NE) from 2016 to 2019. ResultsThe AONR varied from 176 to 291 kg ha-1 in different site-years. The optimal pronitridine rate was predicted using the generalized additive model (GAM) for each site. A pronitridine rate of 5.6 g kg-1 N and 8.2 g kg-1 N was recommended for well drained (NE) and poorly drained (MO and IL) sites, respectively. The pronitridine application at an average rate of 5.6 g kg-1 N increased corn grain yield 4 % compared to the non-treated control. Economic analysis showed an increase in gross margin returns of 32–67 $ ha-1 in poorly drained soils (MO & IL) when applied at 8 g kg-1 with fall and spring N application. Whereas 10–30 $ ha-1 higher gross margins were observed in well-drained soils (NE) with an application of 4 g kg-1 of pronitridine for fall and spring application timings. ConclusionThe differences in AONR and pronitridine rate prediction observed in this study emphasize the variability caused by factors such as the soil, environment, and their interaction with the N cycle. When we evaluated pronitridine and nitrapyrin with all site years combined, no differences between the two NIs were observed in terms of corn yield production. SignificanceOur findings are the first to quantify corn yield response for pronitridine applications at different locations and multiple rates in the Midwest U.S. The results of this study highlight the optimum pronitridine optimum rate for improved corn yield in poorly drained and well-drained soils in the Midwest U.S. Profitability of pronitridine can be improved by applying an optimum rate based on N requirements and soil conditions.

Using post‐season tissue nitrogen concentrations to predict adequacy of in‐season nitrogen management

AbstractHigh‐yielding mechanized rice production requires large amounts of nitrogen (N) fertilizer, which can be particularly costly to producers when applied in excess. The development of a tissue test to detect overapplication of N to rice is needed. Nitrogen response trials arranged in a randomized complete block design were established to identify a critical concentration threshold for a tissue test to detect excess N availability. Rice stalk samples were collected from 0 to 20 cm above the soil within 5 days of harvest and analyzed for NO3−‐N concentration. Two models were fit to the data to represent rice grain yield as a function of N concentration: the linear plateau model and the quadratic plateau model. The data were well represented by both models; however, the linear plateau model more accurately described the data with a normalized root mean square error of 0.128 for linear plateau and 0.131 for quadratic plateau and a significant F‐test (p < 0.0001). The join point of the linear response region and the plateau region of the model serves as a critical value that separates the responsive (N deficient) and non‐responsive (N optimum or excessive) regions. The 95% confidence interval of the join point (2.1 mg NO3−‐N kg−1) was selected as a practical, agronomic critical concentration threshold to reduce false positive errors. The data presented here further supports the use of a post‐season tissue test in rice to detect overfertilization and establish a critical concentration threshold for this tissue test.

Need to revisit potassium soil test methods: ammonium acetate method does not correlate with tuber yield and potassium uptake in potato

The study was driven by concerns regarding lack of response to K applied as per existing soil test based fertilizer recommendations in case of the potato crop in northwest India. Geo-tagged surface soil (0-15 cm) samples 180 were collected from three (60 each) different fields (named A, B and C) followed by pot experiment involving potato planted to 30 different surface (0-15 cm) soils using two K levels (0 and 60 kg K2O ha−1). Cate-Nelson (CN) model, and non-linear segmented linear-plateau (LP) and quadratic-plateau (QP) models were used to compute critical K levels by relating relative yield with soil test K using five different methods: 1 M ammonium acetate (AA K), ammonium bicarbonate-diethylenetriamine pentaacetic acid (AB-DTPA), Mehlich-3, sodium tetraphenylboron (STPB) and 1 M boiling nitric acid. These were validated by conducting fertilizer response trials (six K fertilizer levels- 0, 15, 30, 45, 60 and 90 kg K2O ha−1) at four sites. AA K correlated with other soil K extractants in the order: AB-DTPA (r = 0.93**, 0.27* and 0.67**)> STPB K (r = 0.71**, 0.27* and 0.39**) whereas AA K generally did not show any correlation with HNO3 K. AAK method was poorly correlated with yield and plant K uptake (r = 0.15, 0.24, respectively) in comparison to AB-DTPA (r = 0.75**, 0.64**), Mehlich-3 (r = 0.78**, 0.72**), STPB (0.58**, 0.76**) and nitric acid method (0.55**, 0.44*). Thus, multi-nutrient extractants like AB-DTPA and Mehlich-3 are better (than AAK) indices of plant available K.

Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes

In this study, we aimed to evaluate the feasibility of digital image analysis (DIA) as a substitute for standard analysis (SA) in assessing corn ear traits in agrotechnical field trials. Accurate and timely prediction of corn yield through corn ear traits can lead to precise agricultural management recommendations for the improvement of production. Four replications with 10 plots each were subjected to different fertilization regimes and analyzed using DIA and SA to determine the kernel number per ear (KN), ear length (EL), and ear diameter (ED). For both methods, the results showed that only nitrogen doses had a significant effect on the examined corn ear traits, and the correlation matrix revealed a strong and significant relationship between yield and corn ear traits. The post-hoc test showed no discrepancy in cases between the two methods for KN and EL, with a 6.7% discrepancy for ED. For both methods, a linear plateau was the best fit for KN and EL with increasing nitrogen doses, whereas a quadratic plateau was the best fit for ED. The regression equations for both methods provided similar recommendations regarding nitrogen requirements. The findings suggest that DIA can be used as a substitute for SA of corn ear traits obtained from different fertilization variants and can provide nitrogen fertilization recommendations for optimal corn yields.

Discrepancy between the crop yield goal rate and the optimum nitrogen rates for maize production in Mississippi

AbstractThe varying influence of the environment on N supply and demand dictates the need for annually updated fertilizer N recommendations. Currently, crop yield goal (CYG) methods are used by 34 land grant universities, including Mississippi State University, these do not consider environmental variations. This research tested the efficacy of CYG by determining the agronomic optimum N rate (AONR) and the economic optimum N rate for Mississippi corn (Zea mays L.) production. In total, 12 treatments in 2020 and 11 in 2021 were replicated four times over four locations in a randomized complete block design. The optimum N rates were calculated by fitting linear, quadratic, linear plateau, and quadratic plateau models by means of three different goodness of fit measures. Furthermore, differences between the CYG rate calculated from the Mississippi yield goal equation and AONR were compared at different management levels (14 comparisons) (all data combined, both years combined, sites combined by year, and individual sites). Overall, AONR varied from 134 to 301 kg N ha–1 at different management levels. When we compared the AONR to the CYG rate, the CYG rate over‐recommended N in 12 of the 14 possible comparisons, with differences ranging from 69 kg N ha–1 less to 110 kg N ha–1 greater than the AONR. These differences between AONR values highlight variability caused by factors such as the soil, environment, and their interaction with N supply and demand, which are unaccounted for by the CYG method.

Impact of Macronutrient Fertility on Mineral Uptake and Growth of Lactuca sativa ‘Salanova Green’ in a Hydroponic System

Lactuca sativa (commonly referred to as lettuce) is one of the most popular grown hydroponic crops. While other fertilizer rate work has been conducted on lettuce, the impact of each element has not been evaluated independently or by determining adequate foliar tissue concentrations when all nutrients are plant-available. This study explores the impact that macronutrients have on the growth and yield of lettuce at different stages of the production cycle. Additionally, this study explores the adequate nutrient rates by regressing nutrient curves to find the concentration of each element that corresponds to optimal growth. Plants were grown under varying macronutrient concentrations (0, 8, 16, 32, 64, and 100%) utilizing the concentrations of a modified Hoagland’s solution based on 150 mg·L−1 N. Lettuce plants were grown in a silica sand culture and received a nutrient solution in which a single element was altered. Visual symptomology was documented, and leaf tissue mineral nutrient concentrations and biomass were measured at Weeks 3, 6, and 8 after transplant. Optimal elemental leaf tissue concentration and biomass varied by macronutrient rates and weeks of growth. Nitrogen rate produced a linear increase in total plant dry weight, but foliar N followed a quadratic plateau pattern. Other elements, such as phosphorus, potassium, and magnesium, produced distinct total plant dry weight plateaus despite increasing fertility concentrations. These results demonstrate that fertility recommendation can be lowered for nutrients where higher rates do not result in higher plant biomass or foliar nutrient concentrations.

Growth trajectories of wild Assamese macaques (Macaca assamensis) determined from parallel laser photogrammetry

Socioecological factors are associated with life-history patterns and growth trajectories among primates. Under certain conditions, selection may favor a temporal decoupling of growth and major life-history events such as sexual maturation or natal dispersal. Yet, empirical tests of these associations in wild populations remain scarce owing to the lack of non-invasive methods to capture growth trajectories. In this study, we first compared two non-invasive methods of digital photogrammetry. Then, we used parallel laser photogrammetry to investigate forearm growth of wild Assamese macaque males and females in their natural habitat at Phu Khieo Wildlife Sanctuary, Thailand to test life-history and socio-ecological hypotheses. Across 48 males and 44 females, we estimated growth trajectories and pseudo-velocity curves by applying quadratic plateau models and non-parametric LOESS regressions. We assessed the development of sexual dimorphism by comparing the sexes at five different ages. Females had completed 96% of their growth at the age at first birth (5.9 years) and ceased growing at 7.1 years of age. Males, in contrast, grew until well after their average age of natal dispersal: they reached 81% of their size at the age of natal dispersal (4.0 years), and ceased growing only at 9.0 years of age, much later than females. Sexual dimorphism in forearm length was driven by an extended growth period in males, which is expected for males dispersing between multimale and multifemale groups and not facing the risk of being ousted by other larger males. Our results contradict the neonatal investment hypothesis that predicts a desynchronization of investment in growth and reproduction only in female baboons, but not other papionins producing cheaper neonates. Furthermore, male Assamese macaques do not delay natal dispersal until they are fully grown, in accordance with predictions of the male-career-framework for species with low to medium level of direct competition.

Dietary effect of energy levels on growth performance and carcass characteristics of White Pekin duck over 21 days.

This experiment was conducted to determine the maximum dietary energy levels on growth performance and carcass characteristics of White Pekin duck. the Six dietary treatments were formulated based on their apparent metabolizable energy (AME) concentrations from 2,700 to 3,200 kcal/kg with a 100 kcal/kg gap to evaluate the accurate dietary AME requirement to address current knowledge and further issues for fulfilling the genetic potential of meat-type white Pekin ducklings. A total of 432 one-day-old male White Pekin ducklings were randomly allocated into one of six dietary treatments with six replicates (12 birds per pen). The diets were formulated as corn-soybean meal-based diets to meet or exceed the Nutrient Requirement of Poultry specification for meat-type ducks. Growth performance indices (i.e. average daily gain [ADG], average daily feed intake, feed conversion ratio) were measured weekly. Medium body weight (BW) ducklings from each pen were sacrificed to analyze the carcass traits and abdominal fat content on day 21. Obtained data were analyzed to estimate significant effect using the one-way ANOVA of IBM SPSS Statistics (Version, 25). If the p-value of the results were significant, differences in means among treatments were separated by Tukey’s post hoc test. Significant differences were then analyzed with a linear and quadratic broken model to estimate the accurate concentration of AME. Ducklings fed higher dietary AME diets increased (p < 0.05) BW, ADG. Ducklings fed higher AME than 2,900 kcal/kg diets increased abdominal fat accumulation and leg meat portion. The estimated requirement by linear plateau method showed from 3,000.00 kcal/kg to 3,173.03 kcal/kg whereas the requirement by quadratic plateau method indicated from 3,100.00 kcal/kg to 3,306.26 kcal/kg. Collectively, estimated dietary requirements exhibit diverse results based on the measured traits and analysis methods. All the estimated requirements in this experiment present higher than previous research, the maximum requirement for the next diet formulation should be selected by the purpose of the diet.

Nutrient Response Functions of Sorghum for Miesso District Central Rift Valley of Ethiopia

This study was executed to offer the basis for optimized profit from fertilizer use for sorghum yield and to determine robust crop nutrient response function and economic rate for the production of sorghum at Miesso Central Rift Valley of Ethiopia. Trails were conducted at six experimental sites, sorghum yield response to N and P fertilizers application and economically optimum rates of nitrogen (EONR) and phosphorus (EOPR) were evaluated on a vertisols within the semi-arid Miesso districts west Hararge zone of Oromia region. The nutrient rates in 2014 cropping season four levels of Nitrogen (N) alone, these levels with 20 kg·ha−1 Phosphorus (P) and without N, 69 kg·ha−1 N with three levels of P treatments including the zero control were evaluated. In 2015, cropping season similar rates of N alone, the same rate N with 20 kg·ha−1 P, 92 kg·ha−1 N with three rates of P including the zero control were evaluated. The treatments were arranged in a randomized complete block with three replications in factorial design. Nutrient responses of sorghum were determined using asymptotic quadratic plateau functions. The significantly highest nitrogen rate was 46 kg·ha−1 alone in 2014 season, which gave grain yield of 2.56 Mg·ha−1 with a maximum yield advantage of 43%. P rates in both seasons and combined (sites + seasons) were not significantly influenced sorghum yield. Nitrogen agronomic and partial factor productivity peaked at 23 kg N ha−1 but declined with increasing N rate. The EONR combined (sites + seasons) were 37, 45, 52 and 60 kg·ha−1 and for the profit to cost ratio (PCR) were 2.43, 3.65, 4.86 and 5.79 at difference cost to grain price ratios (CP) = 3.6, 2.3, 1.6 and 1.2 respectively at Miesso Ethiopia. Nitrogen application had economically profitable than P. The study concluded that the application of N at 37 or 60 kg N ha−1 to sorghum production could be economically profitable for those economically constrained farmers or economically not constrained farmers. Validation should be farther conducted on farmers’ fields for refining the results obtained.

Yield and Quality of Carrot Cultivars with Eight Nitrogen Rates and Best Management Practices

Carrot (Daucus carota) production has increased in North Florida and South Georgia since 2015. Deep sandy soils, moderate winter climate, availability of irrigation water, and proximity to eastern markets are favorable for carrot production in the region. Nitrogen (N) is required for successful carrot production, and the current recommended N application rate in Florida is 196 kg·ha−1. The objective of this study was to verify the recommended N rate for the sandy soils of North Florida using current industry standard cultivars and practices. Carrot cultivars for the whole carrot fresh market, Choctaw and Maverick, and cultivars for the cut-and-peel market, Triton and Uppercut 25, were direct seeded on 102-cm-wide pressed bed tops on 29 Oct. 2016 and 2 Nov. 2017 in Live Oak, FL. Eight N application rates (56, 112, 168, 224, 280, 336, 392, and 448 kg·ha−1) were tested, and all N applications were placed on the bed top. N rates were split and timed to increase N use efficiency. Regression analyses were used to determine the optimal N rate for carrots in North Florida. A quadratic plateau regression for both seasons combined indicated 206 kg·ha−1 N was the optimal rate for carrots, with marketable yield of 71.3 Mg·ha−1, regardless of cultivar. All four cultivars attained acceptable yield including Uppercut 25, which exhibited significant foliage damage following freezing temperatures. This study resulted in updated information on best management practices for carrot production in Florida, especially nutrient stewardship.

Potato Yield, Net Revenue and Specific Gravity Responses to Nitrogen Fertilizer under Different Canadian Agroecozones

Applying higher nitrogen (N) rates than required for optimum potato (Solanum tuberosum L.) growth leads to economic and environmental losses. The extent to which the N rate associated with maximum potato yields differs from that maximizing net revenue (NR) or potato specific gravity is not fully understood. The objectives of this three-year study (2013–2015) conducted at five sites in three Canadian provinces (MB-1; MB-2; QC-1; QC-2; PEI) (15 site-years) were to: (i) assess potato marketable yield, NR, and specific gravity responses to increasing N application; (ii) calculate the N rate maximizing marketable (Nmax) yield and NR using different statistical models. The year, N fertilizer, and their interaction were significant on marketable yield and NR except at the MB-1 site where no significant effect of N was observed. No significant yield increases were observed at a N rate above 60 kg N ha−1 at four site-years and above 120 kg N ha−1 at five site-years, implying that the current recommended N rate could be reduced. All models fitted the marketable and NR data equally based on R2, mean bias error or root mean square error and resulted in comparable predicted yield and NR values. However, Nmax values were different depending on the model with higher values being predicted by the quadratic- (161.4 to 191.9 kg N ha−1) and the quadratic plateau models (60 to 191.9 kg N ha−1), while lower Nmax values were obtained with linear plateau- (60.6 to 129.8 kg N ha−1) and Mitscherlich–Baule plateau models (60.9 to 130. 9 kg N ha−1). Nitrogen rate maximizing NR was on average 4% lower than the N rate maximizing marketable yields, except at one site where it was higher by 26 kg N ha−1 when the quadratic plus plateau model was used. Specific gravity tended to decrease with the N rate. Our study confirms trade-offs between the N rate maximizing yields or NR with that maximizing specific gravity. Nitrogen rate maximizing marketable yield and NR varies depending on the selected model.

Short communication: Development and evaluation of equations to predict growth of Holstein dairy heifers in a tropical climate

The objective of this study was to develop and validate equations for estimating growth of dairy heifers using measures of withers height, body weight (BW), and age. Measures of BW and withers height of 207 Holstein heifers raised in a tropical climate were taken from birth to calving, totaling to 2,047 observations. To be included in the database, the heifer had to have at least 4 measures recorded. After that, 4 models were built and evaluated as follows: (1) a linear model of BW as function of age (BW~A), (2) a linear model of the BW-to-height ratio as function of age (BW:H~A), (3) a quadratic model, adjusted for a defined plateau, to describe height as function of age (H~A), and (4) an exponential growth model of BW as function of height (BW~H). A cross-validation procedure was performed to evaluate accuracy and precision of the models. The linear relationship of BW~A and BW:H~A were estimated, respectively, by the equations: BW = 42.65 + 0.62 × A and BW:H = 0.70 + 0.0041 × A, where BW is in kilograms, BW:H = BW-to-height ratio (kg/cm), and A = age (d). Using the quadratic plateau for the model H~A, a critical "x" value of ~806 d and a height plateau of 138.6 cm were identified. Therefore, the following equations for estimating the height of animals younger and older than 806 d, respectively, were developed: H = 78.15 + 0.150 × A - 0.00009 × A2 and H = 78.15 + 0.150 × cvx - 0.00009 × cvx2, where H = height (cm) and cvx = 806 (critical "x" value; given in days). Additionally, the exponential model of W~H was estimated by the following equation: BW = 4.25 × exp(0.034 ×H), where BW is in kilograms and H = height (cm). A cross validation demonstrated that all equations had very high accuracy and precision. Overall, these models demonstrated that BW and BW-to-height ratio increase linearly as a function of age, while BW follows an exponential growth pattern as a function of height. Additionally, the H~A model predicted that heifers achieve a maximum height of 138.6 cm at 806 d of age.

Canopy Indices: a Model to Estimate the Nitrogen Rate for Barley and Wheat

The objectives were to calibrate the Soil Plant Analysis Development (SPAD) and Green Seeker (GS) as tools to determine the differential of the economic optimum nitrogen rate (dEONR) at different growth stages of barley and to evaluate if a single SPAD or GS calibration model can be used for two cereal crops: barley and spring wheat. Fourteen field experiments were conducted (2016–2018) evaluating five N rates. Relative canopy indices were determined using a SPAD-502 (rSPAD) and a GS sensor (rNDVI) at Z24, Z31, and Z39 growth stages. The relationship between sensor indices and dEONR was evaluated by fitting quadratic-plateau (QP) regression models. Data from a previous study was used to evaluate if a unique QP model could predict dEONR from canopy indices for barley and wheat. Statistically significant QP models were determined for rSPAD and rNDVI at all evaluated growth stages. The sensitivity of these models was greater for rSPAD (0.0006 on average) than for rNDVI (0.0004 on average). A single QP model was developed to predict dEONR from rSPAD at Z31 and Z39 barley growth stages (R2 = 0.68). Also, a unique model was developed to predict dEONR from rSPAD at Z31 and Z39, but not only for barley but also for wheat (R2 = 0.64). A single model could be used to determine variable in-season N rates for barley and wheat, increasing the N use efficiency and limiting possible negative economic and environmental impacts of fertilization over the agroecosystems.

Seeding rate effects on organic rice growth, yield, and economic returns

AbstractSeeding rate is an important factor in optimizing yield components and thus grain yield of conventional rice (Oryza sativa L.), yet limited information on its effect on organic rice production is available. A field study was conducted under organic management over 2 yr to comprehensively evaluate the effects of seeding rate (108, 161, 215, 269, 323, 376, and 431 seeds m−2) and rice cultivar (Presidio [inbred] and XP753 [hybrid]) on yield components, grain yield, milling quality, weed density, and economic returns. Seeding rate had significant effects on seedling stand density and dry biomass with positive linear correlations. Yield linearly increased with increasing seeding rate with the greatest yields of 3,462 kg ha−1 for Presidio and 7,508 kg ha−1 for XP753 at the highest seeding rate tested. Panicle number was positively correlated with seeding rate, while milling quality was not affected by seeding rate. The linear‐plateau (LP) model fit best for Presidio and the quadratic‐plateau (QP) model fit best for XP753 to estimate the ex ante economic optimum seeding rate (EOSR). The EOSR was 87 kg ha−1 (340 seeds m−2) for Presidio and 48 kg ha−1 (192 seeds m−2) for XP753. Using the EOSR, producers could expect a yield of 3053 kg ha−1 and an economic return of US$1,288−$1,346 ha−1 for Presidio, and a yield of 5,835−6,092 kg ha−1 and an economic return of $1,986−$2,686 ha−1 for XP753.

Optimum seeding rate and stand assessment of soft red winter wheat

AbstractCultivar selection and seeding rate influence soft red winter wheat (Triticum aestivum L) grain yield. Re‐evaluating optimum seeding rate for crops is necessary as modern cultivars may show a greater yield advantage when planted at a higher plant population compared with older cultivars. Furthermore, the relationship between wheat stem population density and yield needs to be understood to help producers make informed estimates of yield potential. The objectives of this research were to determine: (a) the agronomic and economic optimum seeding rate (AOSR and EOSR, respectively) of soft red winter wheat, and (b) the relationship of wheat stem population density and grain yield. Trials were established during two growing seasons at two locations in Ohio with four wheat cultivars and four seeding rates ranging from 1.85 to 6.18 million seeds ha−1. Among the four cultivars, the quadratic plateau model resulted in an average AOSR of 4.20 million seeds ha−1 and an average EOSR of 3.13 million seeds ha−1. The AOSR was 10–33% greater than the previous recommendation of 2.96 to 3.95 million seeds ha−1. This increase may be due to modern wheat cultivars having a higher tolerance to increased plant density as the previous recommendation, which is over 30‐yr old. Wheat stem number was linearly related to grain yield and explained 31% of the variability in yield. Planting the optimum number of wheat seeds followed by wheat stand evaluation in the spring should result in maximum economic return and informed decisions regarding wheat yield potential.