Growth Stages Of Maize Research Articles

Effects of Foliar Applications of Boron at the Early Vegetative Stages on Plant Growth Parameters of Maize

Boron is an important micronutrient for growth and development of crop plants. Plant species differ in their requirement of boron for growth. This study was conducted to determine the effect of boron application on the plant characteristics of maize during early leaf stages. The experiments were conducted in Tel – Kaliş agricultural research area at the Mustafa Kemal University in 2015 and 2016 growing seasons. The field experiments were arranged in a split plot design with three replications. Four boron dosages (control, 4, 6 and 8 mg/m2) were applied at three growing stages (V2, V4 and V2V4 (at V2 and V4 stages in two equal parts) as foliar spray. The results revealed that the effects of foliar application of B were positive but statistically insignificant on plant characteristics. Further researches should be conducted for suitable boron application time at different growth stages of maize.

Root trait plasticity and plant nutrient acquisition in phosphorus limited soil

AbstractTo overcome soil nutrient limitation, many plants have developed complex nutrient acquisition strategies including altering root morphology, root hair formation or colonization by arbuscular mycorrhizal fungi (AMF). The interactions of these strategies and their plasticity are, however, affected by soil nutrient status throughout plant growth. Such plasticity is decisive for plant phosphorus (P) acquisition in P‐limited soils. We investigated the P acquisition strategies and their plasticity of two maize genotypes characterized by the presence or absence of root hairs. We hypothesized that in the absence of root hairs plant growth is facilitated by traits with complementary functions, e.g., by higher root mycorrhizal colonization. This dependence on complementary traits will decrease in P fertilized soils. At early growth stages, root hairs are of little benefit for nutrient uptake. Regardless of the presence or absence of root hairs, plants produced average root biomass of 0.14 g per plant and exhibited 23% root mycorrhizal colonization. At later growth stages of maize, contrasting mechanisms with functional complementarity explained similar plant biomass production under P limitation: the presence of root hairs versus higher root mycorrhizal colonization (67%) favored by increased fine root diameter in absence of root hairs. P fertilization decreased the dependence of plant on specific root traits for nutrient acquisition. Through root trait plasticity, plants can minimize trade‐offs for developing and maintaining functional traits, while increasing the benefit in terms of nutrient acquisition and plant growth. The present study highlights the plasticity of functional root traits for efficient nutrient acquisition strategies in agricultural systems with low nutrient availability.

Significance of disposable presowing irrigation in wheat in increasing water use efficiency and maintaining high yield under winter wheat-summer maize rotation in the North China Plain

Water scarcity in the North China Plain (NCP) is threatening irrigation of predominant winter wheat-summer maize rotation and thus rotation yield. To maximally reduce irrigation input while maintaining relatively high yield is urgently needed and an enduring challenge. Here we present an innovative practice that considers the water use of the entire rotation system, i.e., application of presowing irrigation to reach 85% of the field capacity for wheat (W0) compared with the common practice of applying twice more irrigation with each 750 m3 ha−1 during the wheat season (W2). After sowing maize, 750 m3 ha−1 irrigation was applied for both practices. The main hypothesis was that reducing wheat irrigation would lead to lower water content in the soil, which would in turn preserve more rain in the maize season, and that earlier maturity of wheat caused by reduced irrigation would advance earlier maize-sowing to utilize more radiation and thermal inputs resulting in higher maize yield which would compensate for decreased wheat yield. From 2012 to 2016, the 0–200 cm soil water contents, as well the yield and its components, were monitored at key growth stages of wheat and maize. There was consistently lower water content under W0 than under W2 from flowering to maturity of wheat making 4–5 days earlier maturity under the W0 practice, and led to a higher accumulated temperature of maize relative to the W2 practice. The grain yields of wheat, maize and rotation were 6694 to 9218 kg ha−1, 7284 to 12,843 kg ha−1, 16,336 to 20,605 kg ha−1, respectively. The temperature accumulated after silking well explained the interannual variation in maize yield. In contrast to temperature, rainfall during the maize season explained the yield difference between two practices. The maize yield was 6.4% higher under the W0 practice than under the W2 practice, in a year with sufficient rainfall, above 451 mm, and this trend was unpronounced under rare drought stress, below 250 mm of rainfall, leading to a 7.5% lower yield. The average yield of the four rotation rounds under W0 was equal to that under W2. Nevertheless, the W0 practice significantly increased the water use efficiency under rotation by 12.9%. On average, the irrigated amount in each rotation under W0 was significantly reduced by 1126 m3 ha−1 relative to W2. Therefore, the W0 practice is a simple and promising water management strategy for addressing shortages of water and labor while maintaining relatively high rotation yield in the NCP.

Irrigation scheduling of maize based on plant and soil indices with surface drip irrigation subjected to different irrigation regimes

A study was conducted on a research farm at Urmia University under drip irrigation in order to schedule the irrigation of maize based on plant indices: crop water stress index (CWSI) and relative water content (RWC) and soil indices: soil water (SW) and soil penetration resistance (Q) in climatic conditions of Urmia region in Iran. This study was conducted in the form of randomized complete block design with four irrigation levels including two levels of deficit irrigation (I1) (Crop water requirement (CWR) of 0.5) and I2 (0.75CWR), a full-irrigation level of I3 (1.0CWR) and an over-irrigation level of I4 (1.25CWR) with three replications. I4 treatment for air-filled porosity was considered in the soil. For irrigation scheduling, lower and upper baseline and CWSI equations for I1, I2 and I3 treatments were calculated during plant growth period. Using the extracted baselines, the mean CWSI values during maize growth season for I1, I2 and I3 treatments were calculated to be 0.53, 0.44 and 0.28 respectively. The threshold limit of water stress index of I3 treatment was the basis of irrigation scheduling. Then, relationships were provided for determining the irrigation time using CWSI in Urmia climate for three maize growth stages. In addition, among soil and plant indices which were simultaneously measured at maximum stress hour were used as a complementary indicator to eliminate CWSI constraints. Using the regression relationships extracted between the indices, the water status of plant can be determined by only measuring the canopy temperature (Tc) without measuring the RWC, SW and Q. It should be noted that in the region of Urmia, the critical values of the difference between the Tc and the air temperature, Q and SW for maize were respectively 1.5 °C, 3.6 MPa and 0.27 cm3 cm−3 (matric potential of 8900 hPa).

Estimating leaf nitrogen concentration considering unsynchronized maize growth stages with canopy hyperspectral technique

Abstract Accurate monitoring of the leaf nitrogen concentration (LNC) in maize can provide a fundamental basis for effective N management. In recent decades, many spectral indices and algorithms can accurately estimate the crop N status during different growth stages of maize. However, the effect of unsynchronized maize growth stages on these spectral models is rarely considered. The objectives of this study were to verify the predictive ability of the published vegetation indices (VIs), the partial least squares (PLS) regression and the two-band optimal combinations algorithms, and to determine the most accurate method for assessing the LNC of unsynchronized growth stages in maize. Canopy raw and first-derivative reflectance (FDR) spectra, and destructive measurements of the maize LNC were collected in 2016–2018 in different ecological areas, unsynchronized growth stages, cultivars, plant densities, and N rates. The published VIs and new 2-band VIs and their band combinations varied across different growth stages and were not affected by unsynchronized growth stages. The red-edge chlorophyll index (CIred edge), which was identified across growth stages, performed quite well for LNC estimation, but performed unsatisfactorily when compared to the new 2-band VIs that were developed in this study. The best spectral index of the green or red and red-edge or near-infrared band combination based on FDR spectra had a good diagnostic effect for LNC of maize across the four growth stages, in which the novel normalized difference spectral indices (NDSI) effect was optimal in the V9 (9-leaf stage), VT (tasseling stage) and R1 (silking stage) stage and the novel ratio spectral indices (RSI) was the best in the R3 (milk stage) stage. Compared to PLS regression based on raw full-range hyperspectral data, the PLS regression for estimating LNC across four growth stages based on FDR full-range hyperspectral data showed a higher accuracy, with an average coefficient of determination (rval2) of 0.87 and average root mean square error (RMSEval) of 0.18. In addition, the average rval2 for the PLS regression based on selected FDR wavelengths increased by 2.40% and the average RMSEval decreased by 14.8%, compared with the best performing VIs during the four growth stages. It is concluded that the best 2-band VIs and the PLS regression based on selected FDR wavelengths provide a useful explorative tool for estimating LNC of maize across years, ecological areas, and unsynchronized growth stages.

Characteristics of nitrogen loss in sloping farmland with purple soil in southwestern China during maize (Zea mays L.) growth stages

Nitrogen (N) loss from agricultural nonpoint source pollution results in eutrophication. In this study, the characteristics of N loss were explored using simulated rainfall conditions during different maize growth stages (seedling, elongation, tasseling, and maturity) under different slope gradients (10°, 15°, and 20°), from May to August 2016. The surface runoff and sediment yield increased with increasing rainfall duration. As the slope gradient increased, surface runoff and sediment yield also increased, and N loss accelerated during the maize seedling stage. Interflow and N loss decreased as the slope gradient increased, and the maximum interflow and N loss were found during the tasseling and elongation stages of maize. Similarly, maximum average N losses were recorded during the maize seedling stage for both surface runoff and sediment yield (35.01 mg m−2 and 5.63 mg m−2, respectively), while the maximum interflow (163.91 mg m−2) was recorded during the elongation stage. The surface runoff and interflow accounted for 9.27%–45.90% and 50.79%–89.35%, respectively, of the average total nitrogen (TN) loss under different slope gradients and during different maize growth stages. Thus, we concluded that interflow was the main pathway for N loss. Surface runoff and interflow mainly contained dissolved total nitrogen (DTN), while nitrate nitrogen (NO3N) was the primary form of DTN during the different maize growth stages. Path coefficients and contribution rates of slope gradients were the highest for DTN loss in surface runoff and for ammonium nitrogen (NH4N) loss in interflow. The path coefficients and contribution rates of surface runoff, interflow, and sediment yield were the highest for TN, NO3N, NH4N, TN, DTN, NO3N, and TN loss, respectively. We concluded that surface runoff, interflow, and sediment yield were the main factors affecting N loss at our study site in the purple soil region of southwest China, followed by slope gradient and vegetation coverage.

Effect of planting density on deep soil water and maize yield on the Loess Plateau of China

Dryland farmers tend to increase maize plant density with drought and density stress tolerance hybrids to achieve higher grain yield in recent years. However, could this strategy improve yield or water use efficiency (WUE) and be sustainable without decreasing deep soil water in drought-prone environments is not clear. A 4-year of successive field study was carried out with three different drought and density stress tolerance maize hybrids and four plant density arrange from 52,500 to 97,500 plants ha−1. To quantify the responses of grain yield formation and WUE to increasing plant density under various rainfall condition and evaluate the effect on deep soil water balance. Results showed that using of drought and density stress tolerance hybrids could achieve higher grain yield and WUE with higher plant density in normal years, which was associated with an increase in kernels number per square meter. But in dry year, as fewer water was available during reproductive growth stage in higher plant density, grain yield and WUE was gradually decreased with increasing plant density, especially in density stress sensitive hybrid. Soil water balance at 0 to 200 cm depth was not broken by high plant density from the perspective of same water availability at sowing in each year, despite of the lower soil water content during maize growth stage. However, high plant density tended to consume more deep soil water which was hardly been replenished by precipitation, especially in high density tolerance hybrids. Hence, higher density that exceed 60000 plants ha−1 couple with drought and density stress tolerance hybrids is a potential way to improve maize production in dryland, but it increases the risk of deep soil desiccation.

Effect of nitrogen supply method on root growth and grain yield of maize under alternate partial root-zone irrigation

A field experiment was carried out to investigate effect of nitrogen (N) supply method on root growth and its correlation with the above-ground parts in maize (Zea mays L.) under alternate partial root-zone irrigation (APRI) at Wuwei, northwest China in 2012 and 2014. The treatments included alternate N supply, conventional N supply and fixed N supply under APRI (designated AN, CN and FN, respectively), with an additional CN fertilizer treatment coupled with conventional irrigation (CK). Ridges were built in a west-east direction. Root weight density (RWD) in the 0–100 cm soil layer and shoot biomass at the V6, V12, VT, R2 and R6 stages, and grain yield and yield components at the R6 were determined. Results showed that RWD around the plant (i.e. under the plant, south and north of the plant) in the 0–40 cm soil layer varied among different treatments at the VT, R2 and R6 stages. The RWD north and south the plant were comparable during maize growth stages for AN, CN and CK, while FN significantly decreased the RWD of its no N supply side at the three stages and markedly decreased the RWD of its N supply side at the VT. AN and CN significantly increased the RWD, shoot biomass at the three stages, and grain yield compared with FN and CK. Grain yield was positively correlated with RWD in the 0–40 cm soil layer at the three stages. These results suggested that AN and CN produced a relatively uniform distribution of roots and a greater root biomass, which contributed to the enhanced shoot biomass and grain yield of maize under APRI.

Integrating transcriptomic and proteomic analyses of photoperiod-sensitive in near isogenic maize line under long-day conditions

As a short-day plant species, maize requires an optimal photoperiod for inducing reproductive growth. However, there is a lack of information regarding photoperiod-induced changes in maize mRNA and protein levels. In this study, a photoperiod-insensitive maize inbred line and its near isogenic photoperiod-sensitive line were used. By integrating RNA-based transcriptomic and iTRAQ LC-MS/MS-based proteomic approaches, we generated a comprehensive inventory of the transcripts and proteins with altered abundances in response to a long photoperiod (LP) during growth stage transitions. We detected 22 000 transcripts in RNA-sequence runs and 5 259 proteins from an iTRAQ-based analysis. A weak correlation between mRNA- and protein-level changes was observed, suggesting the LP-induced transition between maize growth stages is largely regulated post-transcriptionally. Differentially expressed genes influenced by LP conditions were associated with several regulatory processes in both maize inbred lines, especially phosphate ion transport and the circadian rhythm. Additionally, 31 transcripts and six proteins related to photoperiodic flowering in maize were identified by comparing transcriptomic and proteomic data. This transcriptomic and proteomic analysis represents the first comprehensive and comparative study of gene/protein-level changes occurring in photoperiod-sensitive and -insensitive maize inbred lines during growth stage transitions under LP conditions.

Phosphorus losses under heavy rain from the sloping farmlands in the purple hilly region of Southwestern China

Phosphorus (P) and sediment loss through runoffs to surface and ground water represent a risk to human and environmental health. The objective of this work was to understand the mechanisms of P loss under heavy rain from the purple soil of sloping farmlands. The work was carried out with simulated rainfall experiment at different maize growth stages. The combination of three factors was studied: tillage methods (flat planting, longitudinal ridge, and cross-ridge), slope gradients (10°, 15°, and 20°), and maize growth stages (seedling stage, elongation stage, tasseling stage, and maturity stage). Surface runoff, subsurface runoff, sediment, P content in runoff, and sediment were determined. The rate of sediment yield was positively and non-linearly correlated with the runoff shear force and increased quickly when using the longitudinal ridge tillage method. Longitudinal ridge and 20° slope croplands showed greater erodibility, which resulted in higher runoff, sediment yield, and associated P loss. Total phosphorus (TP) and available phosphorus (AP) losses during the entire growth period were 17.58 mg m−2 and 32.86 mg m−2, in the longitudinal ride on 20° slope. Cross-ridge treatment can effectively prevent the loss of P. The P loss occurred violently on 20° slope, and there was little difference in the P loss between 10° and 15° slopes. Dissolved total phosphorus (DTP) loss dominated the TP loss in runoff, accounting for more than 55.58% of the DTP losses in all the treatments. These results indicate the application of flat planting and cross-ridge tillage in croplands with less than 20° slope, as these will minimize the pollution of soil and water resources by reducing P loss in runoff and sediment.

Green manure and phosphorus fertilization affect weed community composition and crop/weed competition in organic maize

AbstractGreen manure and compost-enriched in phosphorus can promote the sustainability of cropping systems by increasing soil fertility over the long term. They can also be used to manage crop/weed interactions, a key element in guaranteeing an appropriate level of satisfactory crop yields. We studied how green manuring with hairy vetch (Vicia villosaRoth.) and the application of different types of phosphorous-enriched compost affect weed/maize (Zea maysL.) interactions in an organic stockless Mediterranean agroecosystem for two consecutive dry years. Green manure stimulated the expression of maize traits related to a higher competitive ability against weeds, such as early growth, height and leaf area index, while the effect of compost was less clear. Regarding crop/weed competition, both green manuring and a phosphorus-enriched compost application gave a significant advantage to maize. Neither green manure nor compost increased total weed density and biomass compared to the control. Green manuring significantly affected the weed community composition. The relative density of ruderal and competitive-ruderal species (according to Grime's classification) was higher in plots where the green manure was applied. The use of green manure, together with novel composting techniques, significantly affected crop/weed competitive interactions, favoring maize, but also creating favorable conditions for unwanted weed species such as competitive-ruderals. Increasing nitrogen availability in the early growth stages of maize through green manuring can increase crop competitive ability. However, this may not suffice to preserve the system from future weed problems, should potentially detrimental species be selected. Dedicated strategies for the control of emerging weed species may thus be needed.

Monitoring maize growth conditions by training a BP neural network with remotely sensed vegetation temperature condition index and leaf area index

Crop water stress and vegetation status are critical parameters and should be proposed as input variables of an integrated model for crop productivity and yield estimation. In this study, to improve the monitoring of the regional maize growth conditions in the North China Plain, PR China, the remotely sensed vegetation temperature condition index (VTCI) and leaf area index (LAI) at five growth stages of maize (the seeding, jointing, heading, milk and mature stages) during 2010–2015 were generated as inputs of three-layer back propagation (BP) artificial neural networks (ANNs) with different numbers of nodes in the hidden layer to estimate the crop growth. Among these BP ANN models, an architecture with 12 nodes in the hidden layer provided the best training (RMSE = 755.7 kg/ha, MSE = 0.023) and testing (RMSE = 644.3 kg/ha, MSE = 0.037) performance and was selected to simulate values of the integrated growth monitoring index of maize (IGMIM) and to map the regional maize growth conditions pixel by pixel in the North China Plain during 2010–2018. The spatiotemporal characteristics displayed by the maize growth maps based on the IGMIM showed that the best year was 2016, the worst year was 2015, and maize growth in different parts of the plain varied accordingly with variations in the meteorological conditions. Thus, the information reflected by the IGMIM was in good agreement with the actual results. To further validate the accuracy of the integrated index, the correlations between the values of the IGMIM and several growth-related variables, including the measured yield, planting density, plant height and relative soil humidity at the 0–10 cm layer, at thirteen meteorological stations from 2010 to 2012 were analyzed, and the results were meaningful and presented a significant linear relationship. Thus, the BP ANN-based model has the ability to integrate information reflected by multiple maize growth-related factors at each growth stage and provides a better quantification of the monitoring results of regional maize growth conditions.

Monitoring of soil microbial inoculants and their impact on maize (Zea mays L.) rhizosphere using T-RFLP molecular fingerprint method

Plant Growth Promoting Rhizobacteria (PGPR) are commonly applied in agricultural systems as biofertilizers due to their beneficial effects on plant productivity and crop yield. Considering the growing nutritional needs of the human population, PGPR inoculants adapted to deteriorated soil conditions offer a sustainable way for crop production. The objective of this study was to detect the presence and estimate the relative abundance of the PGPR members of ‘stress-tolerant’ bacterial inocula, and to investigate their effect on the indigenous bacterial community structure of the maize rhizosphere. The acid stress tolerant bacterial inocula were compared to inocula used in mildly alkaline soil, during the 112-day growth period of maize. The Terminal Restriction Fragment Length Polymorphism (T-RFLP) molecular fingerprint method offered a possibility for monitoring the applied bacteria. Two different restriction endonucleases were selected in silico and tested in vitro for specific detection of the inoculated PGPR. The developed T-RFLP model system indicated a clear positive effect of inoculants on the relative abundance of Azospirillum species in mildly alkaline (pH 7.3) and acid (pH 5.35) plot between days 14 and 21, and also on that of Agreia pratensis in acid plot in the period between days 35 and 56. In case of Azospirillum and acid soil the positive effect proved to be statistically significant (2–5 times higher relative abundances compared to the control). Similarly, the abundances of the monitored PGPR species and the maize yield were more positively influenced in acid soil than in mildly alkaline soil treated by the inocula developed. In the case of acid soil treatments resulted in significant growth of cob number (1.29–1.44 times of the control). The bacterial community structure of the rhizosphere significantly differed depending on soil type and maize growth stage.

A drought index for Rainfed agriculture: The Standardized Precipitation Crop Evapotranspiration Index (SPCEI)

AbstractA drought index is one of the main methods used for measuring drought and represents the basis of drought monitoring, early warning, and classification. On the basis of an analysis of the advantages and limitations of the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Crop Evapotranspiration Index (SPCEI), which is a drought index of rainfed agriculture, was constructed in this study. The applicable conditions of the SPCEI were then investigated, and the results showed that the SPCEI was suitable for dryland crops under non‐irrigated conditions in arid and semi‐arid areas. The difference between the SPEI and SPCEI is analysed. Compared with the SPEI, the SPCEI considers crop evapotranspiration and the crop growth stage and was found to be more suitable for monitoring agricultural drought. Qigihar, which is located in a semi‐arid area in western Heilongjiang Province, China, was then analysed as an example. The characteristics of the spatial and temporal variability of regional agricultural drought were analysed based on maize and soybean in dryland areas. The results for the different growth stages of maize and soybean showed that drought intensity is more serious in the initial stage in the middle part. In crop development, mid‐season and late season stage, the drought conditions gradually increased from north to south. The drought degree of the two crops at the initial stage gradually increased, and the drought degree at the crop development stage gradually decreased. The main reason is that precipitation gradually increases during the crop development stage.

Significance of P influx and Root Growth in P Acquisition at Different Growth Stages of Maize, Wheat and Groundnut Grown in a P-Deficient Alfisol

Crop species differ in their phosphorus (P) efficiency i.e. their ability to grow well in low P supplying soils. To test this hypothesis, field experiments were carried out in a low P soil to study P efficiency of wheat (Triticum aestium L.), maize (Zea mays L.) and groundnut (Arachis hypogaea L.) during the whole growing season and the possible reasons of variation in P efficiency of these crops. Treatments replicated four times consisted of P-0 (no P), P-50 (50 mg P kg−1 soil) and P-400 (400 mg P kg−1 soil). Four harvests were made to cover whole growing season of all the crops. At each harvest, different soil and plant parameters were determined. Plot size varied from 10 m2 for the first three harvests and 16 m2 for the last harvest (at maturity). Taking the relative yield as measure of P efficiency (expressed by the yield at P-0 relative to the yield at P-400), maize was most efficient, yielding more than 80%, followed by groundnut, 75%, and wheat, 65% of their maximum yields. Total P uptake of maize was twice to those of wheat and groundnut. The variation in uptake efficiency was not related to size of root systems but mainly to the P influx. At P-0, although the root system of groundnut was only 50% of that of wheat, P uptake was the same; and maize had the same root length as wheat but P uptake was twice. Wheat was of intermediate P efficiency during the whole growing season while maize was inefficient in early growth stages and very efficient later. In contrast, groundnut was very efficient at the beginning and less efficient later. The efficiency of wheat was mainly based on its root system whereas maize and groundnut relied on a large P influx. The P influx was the major factor determining differences in P efficiency among the species as well as for the same species during the growing season under field conditions. To separate the influence of root and soil properties, model calculation of P influx were carried out by employing the nutrient uptake model. Measured influx was much higher than the calculated influx at low P level. Sensitivity analysis shows that at low P level the CLi (initial soil solutions P concentration) was the most sensitive parameter for all the three crops. Among the physiological parameters Imax and Km was found to play negligible role in P uptake at low P level. But at higher P level (P-400) Imax was the most sensitive parameters followed by r0 for P uptake of three crop species. The higher measured than calculated influx indicated that plant possesses mechanisms that enhance P transport to the root from soil. Possible reason for this enhanced transport may be through root exudates that increase P solubility in the rhizosphere or mycorrhizae symbiosis.

Nutrients uptake and water use efficiency of drip irrigated maize under deficit irrigation

Little is known about nutrient uptake during different growth stages of drip irrigated maize under deficit irrigation. A 2-year field study in the semi-arid region of Upper Egypt was carried out in a randomized complete block design with five replications during the summer of 2016 and 2017. Maize plants were irrigated with 100, 80, or 60% of water requirements. Maize growth was negatively affected by the lower water supply. Total uptake of nitrogen (N), phosphorus (P), and potassium (K) by maize irrigated with I100 increased by 21, 25, and 21% compared to that irrigated with I60. I80 reduced the grain and straw yield by 8 and 17% compared to I100. Under deficit irrigation water was used efficiently more than full water supply. NPK requirements of drip irrigated maize under deficit irrigation are less than those irrigated by full water supply thus help to sustain the environmental ecosystem and increased the economic returns.

Future increases in irrigation water requirement challenge the water-food nexus in the northeast farming region of China

Northeast Farming Region of China (NFR) produces about one-third of the national maize output. Shortage of crop irrigation water is one of the main threat to the stable level of maize production in the NFR. Previous studies on the sensitivity of maize production to drought are typically based on field experiments and treat the maize growing season as a whole, with rare attention to the varying impacts of drought across different maize growth stages. Given the importance of NFR on China’s food security, it is crucial to optimize the irrigation schedule to mitigate the adverse effects of drought. In this study, we employ Agro-ecological Zone (AEZ) model to investigate how climate change affects irrigation water requirement (IWR) of maize during different growth stages and under different climate change scenarios. Results indicate that the NFR would experience a substantial increase in the probability of extremely shortage of crop irrigation water under future climate change. The ensemble simulation under future climate projections indicates more frequent demands for irrigation with substantially increased amount in the mid-season stage (G3) when maize is more sensitive to water deficit compared with other stages. These findings indicate that earlier planning of irrigation infrastructure and development of more efficient irrigation scheme and technologies is of great importance to secure maize production in the region.

The changing dynamics of rill erosion on sloping farmland during the different growth stages of a maize crop

AbstractRill erosion is a serious concern in the hilly region of China with purple soil, and maize is extensively cultivated in this region. Evaluations of the dynamic mechanisms of rill erosion in sloping farmland areas are particularly important during the maize growing season to determine whether rill erosion can occur. A new ridge tillage (RT) system was designed using local agricultural methods in China. Twelve artificial rainfall experiments were conducted in three 1 × 2 m experimental plots with a slope of 15°, which is a typical slope in the study area. The rainfall intensities were designated as 1.0, 1.5, and 2.0 mm min−1. The rainfall experiments were performed in the field to determine the characteristics of run‐off and sediment transport related to rill erosion processes during different stages of maize growth and to analyse how hydraulic parameters and the sediment yield of the rill erosion process are related. The results showed that rill flow patterns were mainly classified as subcritical transition flow during all the growth stages of maize. The effects of hydrodynamic parameters on the sediment yield were ordered as follows: Reynolds number > stream power > Froude number > shear stress. The total sediment yield varied by stage as follows: seedling stage > jointing stage > mature stage > tasseling stage. The sediment yield and run‐off rate exhibited a linear relationship that was well described at the hillslope scale. To initiate soil loss in sloping farmland areas with purple soil during the maize growing season, the critical hydrodynamic shear stress and stream power must be at least 46.505 Pa and 1.541 N m−1 s−1, respectively.

Clustering Field-Based Maize Phenotyping of Plant-Height Growth and Canopy Spectral Dynamics Using a UAV Remote-Sensing Approach.

Phenotyping under field environmental conditions is often considered as a bottleneck in crop breeding. Unmanned aerial vehicle high throughput phenotypic platform (UAV-HTPP) mounted with multi-sensors offers an efficiency, non-invasive, flexible and low-cost solution in large-scale breeding programs compared to ground investigation, especially where measurements are time-sensitive. This study was conducted at the research station of the Xiao Tangshan National Precision Agriculture Research Center of China. Using the UAV-HTPP, RGB and multispectral images were acquired during four critical growth stages of maize. We present a method of extracting plant height (PH) at the plot scale using UAV-HTPP based on the spatial structure of the maize canopy. The core steps of this method are segmentation and spatial Kriging interpolation based on multiple neighboring maximum pixels from multiple plants in a plot. Then, the relationships between the PH extracted from imagery collected using UAV-HTPP and the ground truth were examined. We developed a semi-automated pipeline for extracting, analyzing and evaluating multiple phenotypic traits: canopy cover (CC), normalized vegetation index (NDVI), PH, average growth rate of plant height (AGRPH), and contribution rate of plant height (CRPH). For these traits, we identify genotypic differences and analyze and evaluate dynamics and development trends during different maize growth stages. Furthermore, we introduce a time series data clustering analysis method into breeding programs as a tool to obtain a novel representative trait: typical curve. We classified and named nine types of typical curves of these traits based on curve morphological features. We found that typical curves can detect differences in the genetic background of traits. For the best results, the recognition rate of an NDVI typical curve is 59%, far less than the 82.3% of the CRPH typical curve. Our study provides evidence that the PH trait is among the most heritable and the NDVI trait is among the most easily affected by the external environment in maize.

Green Manuring Effect on Changes of Soil Nitrogen Fractions, Maize Growth, and Nutrient Uptake

Green manure is a promising, at least partial, substitution for chemical fertilizer in agriculture, especially for nitrogen (N), which in soil can be radically changed by exogenous input. However, it is not well understood how, after green manure incorporation, soil N changes coordinate with crop N uptake and consequently contribute to fertilizer reduction in a maize–green manure rotation. A four-year field study was performed consisting of (1) control, no fertilization; (2) F100, recommended inorganic fertilization alone; (3) G, green manure incorporation alone; (4) F70 + G (70% of F100 plus G); (5) F85 + G; and (6) F100 + G. The results show that treatments with 15–30% reduction of inorganic fertilizer (i.e., F70 + G and F85 + G) had similar grain yield, dry matter (DM) accumulation, and N uptake as F100 treatment. F100 + G maize had 17% greater DM and 15% more N uptake at maturity relative to F100. Of the five soil N fractions examined, dissolved organic N (DON) and mineral N (Nmin) explained over 70% of the variation of maize DM and N accumulation. Partial least squares path modeling further revealed that soil N fractions had positive indirect effects on DM production through N uptake, which might be coordinated with improved DON and Nmin status at both early and mid-late stages of maize growth. Overall, the results highlight enhanced maize production with reduced fertilizer inputs based on green manure incorporation in temperate regions.