Yield Potential Of Maize Research Articles

Improving the yield potential in maize by constructing the ideal plant type and optimizing the maize canopy structure

AbstractUnderstanding the impact of changes in the crop canopy on yield is important in order to meet future food demands. We designed a field experiment to investigate the relationships between crop‐related factors and yield gaps in maize to enhance crop yields from 2010 to 2018 in Qitai, China. Maize grain yields (n = 247) were divided into four yield ranges: <15 Mg ha−1 (n = 30), 15–18 Mg ha−1 (n = 79), 18–21 Mg ha−1 (n = 114), and >21 Mg ha−1 (n = 24). The characteristics of the maize canopy structure as well as the light interception, photosynthetic potential, and radiation utilization efficiency in these four yield ranges were analyzed. The canopy structure of treated fields with yields >21 Mg ha−1 had a higher leaf area index (7.2), lower ear ratio (0.39), longer internodes above the ear (20.1 cm), larger leaf orientation value (LOV) above the ear (48.6), smaller leaf angle above the ear (18°), and smaller LOV below the ear (36.0) when compared to the other treatments. These findings suggested that the yield gap is dependent on canopy structure, and the evolutionary trend also accounted for significant increases in post‐LAD (p < 0.01), changes in crop growth rate (CGR; p < 0.01), net assimilation rate (NAR; p < 0.05), and radiation utilization efficiency. The radiation utilization efficiencies in the 15–18, 18–21, and >21 Mg ha−1 treatments (1.23, 1.28, and 1.38 g MJ−1, respectively) were higher than for the <15 Mg ha−1 treatment (1.10 g MJ−1). Furthermore, there are opportunities to narrow the yield gaps by optimizing the canopy structure to make full use of the solar radiation resources. Our results will help breeders choose an ideal canopy structure to improve yield. In addition, our results may serve as a general guide for other maize growing regions.

Future climate change will accelerate maize phenological development and increase yield in the Nemoral climate

Climate change will bring warmer and wetter conditions and more frequent extreme events in the Nemoral climate zone. These changes are expected to affect maize growth and yields. In this study, we applied the AgroC model to assess climate change impact on changes in growing environmental conditions, growing season length, yield and potential yield losses due to multiple abiotic stresses. The model was calibrated and validated using data from dedicated field experiments conducted in Lithuania during four meteorologically contrasting years (2015, 2016, 2017 and 2019). We simulated the climate impacts on rainfed maize for long-term future climate conditions from 2020 to 2100 under the RCP2.6 (low), RCP4.5 (medium) and RCP8.5 (high) emission scenarios. As a result, we found that air temperature, sum of growing degree days and amount of precipitation during the growing season of maize will increase, especially under medium and higher emission scenarios (RCP4.5 and RCP8.5), with significantly positive effect on yields. The simulation results showed that average maize grain yield will increase under RCP2.6 by 69 kg ha−1 per decade, under RCP4.5 by 197 kg ha−1 per decade and under RCP8.5 by 304 kg ha−1 per decade. The future potential maize yield reveals a progressive increase with a surplus of +10.2% under RCP4.5 and +14.4% under RCP8.5, while under RCP2.6 the increase of potential yield during the same period will be statistically not significant. The yield gap under RCP2.6 and RCP4.5 will fluctuate within a rather narrow range and under RCP8.5, it will decrease.

Identification of high yielding inbred lines resistant to late wilt disease caused by Harpophora maydis in maize

Diseases are the major constraints in realizing the yield potential of maize. Late wilt disease (LWD) caused by Harpophora maydisis one of the recently reported and widely spreading diseases across the world. Identification of LWD resistant source is an economical and eco-friendly approach. An experiment was conducted to identify LWD resistant inbred lines by subjecting 290 inbred lines to artificial screening. The same set of lines were evaluated for yield and yield attributing traits separately. Inbred lines were subjected to screening by inoculating Harpophora maydis spore suspension to stalks. Disease severity and intensity were recorded in split opened stalks using a 1 - 9 scale. Estimates of yield and yield attributing traits were also recorded and 14 inbred lines with the disease score ≤4 were identified as resistant/tolerant. Two inbred lines namely, 78 and 32589 are both tolerant to LWD and best yielding lines which can serve as potential parents for developing hybrids.

Evaluation of AquaCrop model for estimating of changes process of soil moisture, evapotranspiration and yield of maize under salinity and fertility stresses

IntroductionIn the presence of environmental stresses such as salinity and fertility stresses, water and nutrients less absorbed by the plant. Despite the stresses of salinity and nitrogen deficiency (fertility stress), the determination of the actual water requirement of plants with the AquaCrop model, will be important. Therefore, the aim of this research was to evaluate the AquaCrop model for estimating the soil moisture, evapotranspiration and yield of maize, under the salinity and fertility stresses.Materials and methodsIn this research, two treatments of water salinity and nitrogen deficity in four levels and three replications, with a control plot, were implemented as a factorial experiment in a randomized complete of block design. The studied plant was maize with cultivar of 704 Sc and was planted in plots with dimensions of 3 × 3 meters and 1.5 meters apart. In this plan, fertility stress was in the form of nitrogen fertilizer consumption and at four levels. Treatments of N_0، N_1، N_2 and N_3consisted of consumption of 100, 75, 50 and 25% of nitrogen fertilizer based on fertilizer recommendation, respectively. Salinity stress has been applied by irrigation of the plant with saline water. Water salinity treatments were selected based on yield potential of maize at four levels of 100, 90, 75 and 50% (3). According to the above four performance levels, treatments of S_0، S_1، S_2 and S_3 were included; irrigation water with electric conductivity of 0.5, 1.2, 3.5 and 7.5 (ds/m) respectively. Determining the irrigation time, was the same as the moisture content reached the RAW (Readily Available Water) level. Between the two irrigation intervals, the stomatal resistance of maize leaf, was measured by the AP4 prometer device. At the same time as increasing stomatal resistance, RAW was calculated and plots were irrigated. In the days of between two irrigation, was measured the soil moisture content of the plots at the depth of root development. The daily evapotranspiration of the plant, was calculated based on the amount of daily water depletion. For optimal calibration of parameters in the AquaCrop model, was used the method of Generalized Likelihood Uncertainty Estimation (GLUE). Among 16 treatments, 8 treatments were randomly selected for calibration and the rest were selected for validation. Results and discussionResults were obtained for evaluating the AquaCrop model at the validation stage. The root mean square error (RMSE) of soil moisture simulation, varied from 1.43 to 2.6%. The normalized error value (NRMSE) ranged from 4 to 6 percent. The AquaCrop model showed a similar trend in the evapotranspiration simulation. The root mean square error (RMSE) of evapotranspiration simulation, varied from 1.85 to 2.35 mm. The normalized error value (NRMSE) ranged from 3.5 to 4.5 percent. For yield simulation, RMSE was 0.34 ton. ha-1 and NRMSE was 0.65%. The value of the R^2, EF, and d statistics showed a good correlation between the data and the optimal efficiency of the modeling. Therefore, the results showed that the performance of the model was good in estimating the parameters. ConclusionsEvaluating the capability of the models is a great help to the agricultural sector planners, in estimation the parameters. In this research, evaluated the estimation of soil moisture content, evapotranspiration and yield of maize, under salinity and fertility stresses with AquaCrop model. The purpose of the model calibration was to nearing the simulated data to the real data (measured in the region). The obtained amounts for NRMSE and R^2 were less than 10% and greater than 0.9, respectively, which indicated the optimal performance of the model in this regard.

Effect of uniconazole and nitrogen level on lodging resistance and yield potential of maize under medium and high plant density.

Lodging in maize results in grain yield reduction. This experiment investigated the effects of different application rates of the growth retardant, uniconazole (UCZ), and nitrogen (N) on medium and high maize population densities on lodging resistance and yield. UCZ was applied to maize seeds at concentrations of 0 (U0 ) and 25 (U25 ) mg kg-1 , and three different N application rates, 0 (N0 ), 150 (N150 ) and 225 (N225 ) kg ha-1 , at plant densities of 75,000 (D1 ) and 105,000 plants ha-1 (D2 ). UCZ application, different N rates and plant population density affected the lodging resistance and yield attributes of maize. The diameter, plumpness, cortex penetration and bending strengths of the internodes were enhanced with UCZ and N application at medium and high plant density, where maximum values were obtained with U25 N150 D1 . Internode length increased in the high-density population and higher N rate, whereas UCZ reduced internode length, where maximum internode length was obtained with U0 N225 D2 . Plant height, centre of gravity height, ear and height above ear-bearing node were higher with the high N rate, while UCZ reduced it significantly. UCZ, N rate and plant density enhanced lignin accumulation in the third internode and ear-bearing internode, where maximum values were obtained with U25 N150 D1 . Yield and yield attributes were also improved by UCZ, N rate and population density. Treatment with U25 N150 D2 significantly improved grain yield of maize compared with the other treatments.

Differences of yield and nitrogen use efficiency under different applications of slow release fertilizer in spring maize

Excessive or insufficient application of fertilizer has raised broader concerns regarding soil and environmental degradation. One-time application of slow release fertilizer (SF) has been widely used to reduce yield gap with potential maize yield and improve nitrogen use efficiency (NUE). A 2-year field experiment (2018–2019) was conducted to evaluate the effects of SF rates from 0 to 405 kg N ha–1 (named F0, SF225, SF270, SF315, SF360, and SF405) and 405 kg N ha–1 of common fertilizer (CF405) on the grain yield, biomass and N accumulation, enzymatic activities related with carbon–nitrogen metabolism, NUE and economic analysis. Results indicated that the highest grain yields, NUEs and economic returns were achieved at SF360 in both varieties. The enzymatic activities related with carbon–nitrogen metabolism, pre- and post-silking accumulation of biomass and N increased with increasing SF rate, and they were the highest at SF360 and SF405. The grain yield at SF360 had no significant difference with that at SF405. However, the N partial factor productivity, N agronomic efficiency and N recovery efficiency at SF360 were 9.8, 6.6 and 8.9% higher than that at SF405. The results also indicated that the average grain yields, NUE and economic benefit at SF405 were 5.2, 12.3 and 18.1% higher than that at CF405. In conclusion, decreasing N rate from 405 kg ha–1 (CF) to 360 kg ha–1 (SF) could effectively reduce the yield gap between realized and potential maize yields. The N decreased by 11.1%, but the yield, NUE and economic benefit increased by 3.2, 22.2 and 17.5%, which created a simple, efficient and business-friendly system for spring maize production in Jiangsu Province, China.

Cultivar selection can increase yield potential and resource use efficiency of spring maize to adapt to climate change in Northeast China

Northeast China (NEC) is one of the major maize production areas in China. Agro-climatic resources have obviously changed, which will seriously affect crop growth and development in this region. It is important to investigate the contribution of climate change adaptation measures to the yield and resource use efficiency to improve our understanding of how we can effectively ensure high yield and high efficiency in the future. In this study, we divided the study area into five accumulated temperature zones (ATZs) based on growing degree days (GDD). Based on the meteorological data, maize data (from agro-meteorological stations) and the validated APSIM-Maize Model, we first investigated the spatial distributions and temporal trends of maize potential yield of actual planted cultivars, and revealed the radiation use efficiency (RUE) and heat resource use efficiency (HUE) from 1981 to 2017. Then according to the potential growing seasons and actual growing seasons, we identified the utilization percentages of radiation (PR) resource and heat resource (PH) for each ATZ under potential production from 1981 to 2017. Finally, we quantified the contributions of cultivar changings to yield, PR and PH of maize. The results showed that during the past 37 years, the estimated mean potential yield of actual planted cultivars was 13 649 kg ha–1, ranged from 11 205 to 15 257 kg ha–1, and increased by 140 kg ha–1 per decade. For potential production, the mean values of RUE and HUE for the actual planted maize cultivars were 1.22 g MJ–1 and 8.58 kg (°C d)–1 ha–1. RUE showed an increasing tendency, while HUE showed a decreasing tendency. The lengths of the potential growing season and actual growing season were 158 and 123 d, and increased by 2 and 1 d per decade. PR and PH under potential production were 82 and 86%, respectively and showed a decreasing tendency during the past 37 years. This indicates that actual planted cultivars failed to make full use of climate resources. However, results from the adaptation assessments indicate that, adoption of cultivars with growing season increased by 2–11 d among ATZs caused increase in yield, PR and PH of 0.6–1.7%, 1.1–7.6% and 1.5–8.9%, respectively. Therefore, introduction of cultivars with longer growing season can effectively increase the radiation and heat utilization percentages and potential yield.

Simulating Land-Use Changes and Predicting Maize Potential Yields in Northeast China for 2050.

Crop potential yields in cropland are the essential reflection of the utilization of cropland resources. The changes of the quantity, quality, and spatial distribution of cropland will directly affect the crop potential yields, so it is very crucial to simulate future cropland distribution and predict crop potential yields to ensure the future food security. In the present study, the Cellular Automata (CA)-Markov model was employed to simulate land-use changes in Northeast China during 2015–2050. Then, the Global Agro-ecological Zones (GAEZ) model was used to predict maize potential yields in Northeast China in 2050, and the spatio-temporal changes of maize potential yields during 2015–2050 were explored. The results were the following. (1) The woodland and grassland decreased by 5.13 million ha and 1.74 million ha respectively in Northeast China from 2015 to 2050, which were mainly converted into unused land. Most of the dryland was converted to paddy field and built-up land. (2) In 2050, the total maize potential production and average potential yield in Northeast China were 218.09 million tonnes and 6880.59 kg/ha. Thirteen prefecture-level cities had maize potential production of more than 7 million tonnes, and 11 cities had maize potential yields of more than 8000 kg/ha. (3) During 2015–2050, the total maize potential production and average yield decreased by around 23 million tonnes and 700 kg/ha in Northeast China, respectively. (4) The maize potential production increased in 15 cities located in the plain areas over the 35 years. The potential yields increased in only nine cities, which were mainly located in the Sanjiang Plain and the southeastern regions. The results highlight the importance of coping with the future land-use changes actively, maintaining the balance of farmland occupation and compensation, improving the cropland quality, and ensuring food security in Northeast China.

Effect of different nitrogen level on the growth and yield of different varieties of hybrid maize

When grown under optimum management practises, maize hybrids yield could be low.The high yield potential of hybrid Maize is unlocked using advanced variants and optimum nitrogen fertiliser application practises. In order to assess the effect of varieties and nitrogen fertiliser rates on yield and yield compounds of maize, an experiment on the farm fields was conducted.in two cropping seasons. It is laid out with randomized complete block design in factorial arrangement with three replications. Five maize varieties (BH-540, BH-543, BH-661, BH-660, and BH-140) as main factor and two levels of nitrogen (55 and 110 Kg N ha−1) as sub factor were used with one maize variety (BH-543) without fertilizer as control. The application of nitrogen fertiliser rates affected considerably the area of the leaf and maize varieties leaf surface index. All maize yield and yield components were significantly impacted with the interaction of maize varieties with nitrogen fertiliser rates. Using half and full nitrogen fertilisers, the average grain yield benefits over management were 31 percent and 41 percent. Therefore, application of half and full recommended nitrogen fertilizer for improved maize varieties has significantly improved grain yield and recommended for Hybrid maize production.

English

Maize is highly responsive to nitrogen fertilizer rates and plant spacing. Continuous efforts have been carried out to improve the yield potential of maize by modifying their architecture through breeding methods with aim of increasing maize yield through increasing number of plants ha-1. Hybrid BH-546 is the recently released variety for this purpose but its optimum nitrogen rate and spacing has not been determined yet. Thus, a field experiment was conducted at Bako research farm in the year 2017 to determine the optimum rate of nitrogen fertilization and intra-row spacing. The experiment was laid out in a randomized complete block design in factorial arrangement with three replications. Three intra-row spacing viz., 75 cm × 40 cm, 75 cm × 30 cm and 75 cm × 20 cm accommodating 33,333, 44,444 and 66,666 plants ha-1, respectively, with six nitrogen levels viz., 0, 23, 46, 69, 92 and 115 kg ha-1, were assigned to the experimental plot by factorial combinations. Based on the results, the maximum grain yield (10,208 kgha-1) was obtained when the hybrid was sown at the closest intra-row spacing (20 cm) with application of the highest rate of nitrogen (115 kg ha-1). This result showed 8.9% yield advantages compared to the standard check. However, statistically similar grain yield (9887 kgha-1) was also obtained under application of 92 kg N ha-1 in the same intra-spacing (20 cm). Moreover, since this experiment was conducted for one season and in one location, the comprehensive recommendation could be drawn by investigating more locations over years for this maize hybrid. Key words: BH 546, plant density, yield, yield components.

Bio-efficacy of Pre-emergent Herbicides for Weed Control in Maize: A Review on Weed Dynamics Evaluation

Maize has high yield potential due to its C4 metabolism and physiological characteristics; however, the excessive occurrence of weeds in maize field limits the full expression of the yield potential of this crop. Weeds constitute one of the major economically important problems for maize growers and if not uncontrolled, it can reduce its yield up to 86 per cent. The magnitude of losses largely depends upon the composition of weed flora, period of crop-weed competition and its intensity. In order to realize the yield potential of maize, weed management becomes indispensable. Describing the various aspects of the topic, especially the influence of using pre-emergent use of herbicides on associated weeds revealed that the use of atrazine and pendimetheline are highly important component of today’s weed management systems for maize with higher weed control efficiency, lowest weed density and dry weight. Atrazin @ 1.2 kg active ingredient per ha and pendimmethline @ 1.0 a.i. kg per ha are important in reducing weed emergence in early growth stages of maize.

Effect of Next Generation Fertilizers on Growth and Yield Potential of Maize (Zea mays L.)

To reduce the existing yield gap of maize crop between research and farmer’s field, the experiment was carried out during the period from March, 2014 to June, 2014 at the experimental field of Sher-e-Bangla Agricultural University, Sher-e-Bangla Nagar, Dhaka, Bangladesh. The experiments were laid out in RCBD method with three replications and eight treatments including control viz. Treatment0 = control (no fertilizer), Treatment1=recommended dose N250 P50 K100 S25 Zn2 B1 kg ha-1, Treatment 2=American NPK+N250 P50 K100 S25 Zn2 B1, Treatment3=Bio-forge+N250 P50 K100 S25 Zn2 B1 , Treatment4=Wuxal+N250 P50 K100 S25 Zn2 B1, Treatment5=Peak+N250P50K100S25Zn2B1, Treatment6=Root Feed+N250 P50 K100 S25 Zn2 B1 and Treatment7=Nitro Plus+N250 P50 K100 S25 Zn2 B1 and three maize varieties namely Variety1=BARI Hybrid Bhutta-5, Variety2=BARI Hybrid Bhutta-6 and Variety3=BARI Hybrid Bhutta-9. Growth and yield contributing characters mainly plant height, cob length, cob weight, 100-kernel weight and kernel yield of maize crop were significantly influenced by the next generation fertilizers. Bio-forge along with other recommended fertilizers performed the best compared to other treatments of the study in aspect of kernel yield (5.95 t ha1) and statistically similar result showed by Root Feed along with other recommended fertilizers and produced 5.12 t ha1 kernel yield.

Solar dimming decreased maize yield potential on the North China Plain

AbstractSolar dimming has been increasing in rapidly developing regions (China and India) and threatening food security. Although previous studies have summarized the effects of climate change‐associated increases in temperature on agriculture, few have examined the effects due to solar dimming. Here, we analyzed the effects of solar dimming on maize on the North China Plain (NCP). It is reported that solar dimming intensified and maize yield potential decreased since the 1960s. The total decrease in solar radiation for the whole maize growing season of this period was 17%, and solar dimming explained 87% of the decrease in yield potential. Meanwhile, solar dimming was closely related to the level of anthropogenic fine particulate matter such as PM2.5. The PM2.5 concentration in the NCP averaged 56 μg/m3 in 2014 and 2015, which was approximately three times greater than the global mean. Our results suggested that a 10 µg/m3 increase of PM2.5 concentration in this region was together with a 55 MJ/m2 decrease in solar radiation. Solar dimming threatened food security in the NCP and probably in other areas of the world and has profound implications for ongoing and future efforts such as Clean Air Action and other measures.

Predicting in-season maize (Zea mays L.) yield potential using crop sensors and climatological data

The environment randomly influences nitrogen (N) response, demand, and optimum N rates. Field experiments were conducted at Lake Carl Blackwell (LCB) and Efaw Agronomy Research Station (Efaw) from 2015 to 2018 in Oklahoma, USA. Fourteen site years of data were used from two different trials, namely Regional Corn (Regional) and Optimum N rate (Optimum N). Three algorithms developed by Oklahoma State University (OSU) to predict yield potential were tested on both trials. Furthermore, three new models for predicting potential yield using optical crop sensors and climatological data were developed for maize in rain-fed conditions. The models were trained/built using Regional and were then validated/tested on the Optimum N trial. Out of three models, one model was developed using all of the Regional trial (combined model), and the other two were prepared from each location LCB and Efaw model. Of the three current algorithms; one worked best at predicting final grain yield at LCB location only. The coefficient of determination R2 = 0.15 and 0.16 between actual grain yield and predicted grain yield was observed for Regional and Optimum N rate trials, respectively. The results further indicated that the new models were better at predicting final grain yield except for Efaw model (R2 = 0.04) when tested on optimum N trial. Grain yield prediction for the combined model had an R2 = 0.31. The best yield prediction was obtained at LCB with an R2 = 0.52. Including climatological data significantly improved the ability to predict final grain yield along with using mid-season sensor data.

Maize plants have different strategies to protect their developing seeds against cadmium toxicity

This work aimed to quantify the concentration of soluble amino acids, nitrogen (N) and Cd in the developing seeds of maize plants that were grown in Cd-contaminated soil from seed sowing to the reproductive stages. The specific activities and feedback inhibition properties of lysine (Lys) metabolic enzymes were also determined in developing seeds. The potential maize yield was depressed by Cd exposure. Cadmium concentration in plant organs followed the decreasing order: roots > stems = leaves > developing seeds (37.04, 1.95, 1.46 and 0.22 mg kg−1 Cd, respectively). The relatively low Cd concentration in the remained developing seeds was a result from root- and ear-mediated reductions of the Cd translocation in plants. Plants under Cd exposure presented developing seeds with an increased N concentration (up to 7%) when compared to control plants. Furthermore, the level of soluble amino acids (particularly histidine, glycine, tyrosine, methionine, isoleucine and valine) was increased in the developing seeds of Cd-treated plants. In addition, changes in the feedback properties of dihydrodipicolinate synthase (DHDPS), an enzyme from lysine metabolism, were observed in developing seeds. In conclusion, the current study showed that maternal plant exposure to Cd can alter the concentration of soluble amino acids and the behavior of Lys metabolic enzymes in developing seeds. This study provided not only new information about the influence of the long-term Cd exposure on plants, but also data about protective plant strategies against Cd toxicity.

Yield potential of green maize from partially inbred lines in top crosses

Selecting potential progenies in early inbred generations is an essential step towards the success of breeding programs. Given this, the use of top crosses assists breeders in selecting progenies to generate lines with the potential for hybrid yield. Thus, the purpose of this study was to assess the behavior of partially inbred progenies (S1) of maize with potential for green maize yield in top crosses and to evaluate the hybrid performance. Seventy-five top cross hybrids were generated from the cross between 75 S1 progenies and the F2 generation of the hybrid AG 1051. The 75 hybrids, the male tester (F2 generation of the hybrid AG 1051 as a broad genetic base tester), and the hybrid AG 1051 were sown in a block design with four replicates. The following traits were evaluated: husked ear yield; commercial ear yield; flowering; plant height; strawing; mean weight of grain mass in green maize stage; tassel branch number; ear row number; ear length; and ear diameter. The analysis of variance was performed estimating the general combining ability, and, from the means, the Scott & Knott test was conducted. The top cross hybrids that were prominent for commercial ear yield were those composed of partially inbred progenies 19, 48, 6, 28, and 42 with high GCA, suggesting a potential for the production of open pollination population or synthetic production as well.

Study on Water Saving Potential and Net Profit of Zea mays L.: The Role of Surface Mulching with Micro-Spray Irrigation

Water shortage threatens agricultural sustainability in Horqin Sandy Land, northeast China. To explore the effects of various surface mulching patterns with micro-spray irrigation on the yield, water consumption (ETc), and water-saving potential of maize (Zea mays L.), we used three treatments: straw mulching (JG), organic fertilizer mulching (NF), and no mulching (WG; control). In each treatment, plants were supplied with 500 mm of total water (irrigation plus precipitation) during the entire growing season and were irrigated with the amount of total water supply minus precipitation. Yield and water use efficiency (WUE) showed a significant negative correlation with water saving potential per unit yield (Py) and water saving potential per unit area (Sp), which were also consistent with their relationships in the function model. Meanwhile, a remarkably positive correlation occurred between yield, WUE, and net economic profit, respectively. The JG treatment, which was mainly affected by light and temperature production potential (Yc), grain yield, and ETc, showed the lowest Py (0.16 m3 kg−1) and Sp (2572.31 m3 hm−2), and the maximum increase in yield, WUE, and net economic profit, extending to 16,178.40 kg hm−2, 3.25 kg m−3, 17,610.09 yuan hm−2, respectively, which were significantly higher than those in NF and WG, (p <0.05). Thus, straw mulching with micro-spray irrigation was the best treatment for maximizing yield and WUE. Organic manure mulching and no mulching need further investigation, as these showed high Py and Sp, which were together responsible for lower WUE.

Assessing the impact of climate changes on the potential yields of maize and paddy rice in Northeast China by 2050

Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed.

Estimation of Maize (Zea mays L.) Yield Per Harvest Area: Appropriate Methods

Standardization of crop yield estimation methods at various levels of farming helps to obtain accurate agricultural statistics as well as assessing the suitability of agricultural practices under various production conditions. The current paper reviews various maize yield estimation methods, taking into account available yield parameters, and it also analyses the yield gap between maize potential and attainable yield. The easiest and more reliable methods of yield estimation are based on yield parameters collected from the field. However, farmer estimation methods are cheaper and faster compared to any other method of yield estimation from farmers’ fields. This paper also elaborates on the importance of the use of more complex methods for yield estimation, such as remote sensing and crop modelling. These complex methods are more accurate and can predict yield before field harvest with less deviation from the exact harvest yield. However, they are very expensive and not efficient for small plots of land (less than 1 ha). Factors that contribute to the gap between potential and actual yield include poor implementation of agricultural policies, strict regulation of fertilizer inputs, vulnerability of smallholder cropping systems to adverse climatic conditions, occurrence of biotic and abiotic constraints, as well as unavailability of seeds and labor.

Intercomparison and Performance of Maize Crop Models and Their Ensemble for Yield Simulations in Brazil

Maize yield prediction is of extreme importance for both identifying those locations with high potential for this crop and determining the yield gaps of the crop where it is currently produced. The most feasible way to estimate crop yields is with the use of crop simulation models, since well calibrated and evaluated. Even though, these estimations have uncertainties once the crop models are not complete. Recent studies have shown that crop models´ uncertainties can be reduced when several models are used together, in an ensemble. Considering that, this study aimed to calibrate and evaluate three crop simulation models (AEZ-FAO; DSSAT-CERES-Maize and APSIM-Maize) to estimate maize potential and attainable yields and to assess the performance of different ensemble strategies to reduce their uncertainties for maize yield prediction. Weather, soil and maize yield data from 79 experimental sites in Brazil were used for calibrating and evaluating these models. After that, the models showed only a good performance, with mean absolute errors (MAE) between 727 and 1376 kg ha−1, R2 between 0.49 and 0.79, d index between 0.78 and 0.94, and C index from 0.54 to 0.84. When the ensemble was applied, using the combination of two models (DSSAT-CERES-Maize and APSIM-Maize), the results showed a better performance than each single model or even the average of them, with MAE = 799 kg ha−1, R2 = 0.79, d = 0.94 and C = 0.84, allowing us to conclude that the ensemble of simulated maize yields is a good strategy to reduce uncertainties on simulations.