Growth Stages Of Maize Research Articles

Assessing spatiotemporal characteristics of drought and its effects on climate-induced yield of maize in Northeast China

It is important to investigate the potential impacts of global climate change on crop yield especially there have been limited relevant studies conducted in the cold regions such as Northeast China. This study investigated the spatiotemporal characteristics of droughts on different growth stages of maize over Northeast China during 1960–2016 and the effects of droughts on the climate-induced yield of maize separated by the logistic regression model using standardized precipitation evapotranspiration index (SPEI), trend analysis methods, rotated empirical orthogonal function, wavelet method, and Hurst exponent. The results indicated that: 1) the spatiotemporal patterns of drought were identified at different growth stages and the changes in dryness/wetness condition presented significant periodic oscillation on different time scales. 2) The patterns of dryness/wetness conditions and the changing characteristics of each sub-region at the early growth (EG) and middle growth (MG) stages were similar. 3) The future drought trends in most stations would be consistent with the past trends. In addition to the wetting trend in the eastern and southern parts at the EG stage, the whole study area would show a drying trend in future at other growth stages. 4) The cross wavelet transform (XWT) was used to develop the changing relationships between climate-induced yield of maize and the dryness/wetness condition at different growth stages with obvious inter-annual periodicities. 5) For Northeast China, climatic factors that can affect the climate-induced yield of maize are firstly temperature, next precipitation, and thirdly dryness/wetness conditions.

Shade stress decreased maize grain yield, dry matter, and nitrogen accumulation

AbstractShade stress severely limits plant growth and crop productivity. This study investigated the relationship between shade stress and nitrogen (N) accumulation in maize at different growth stages. Field experiments were conducted in 2015 and 2016 with three shading treatments: from emergence stage (VE) to physiological maturity (R6) (whole‐season shade), from six‐leaf (V6) to tassel stage (VT) (midseason shade), and from VT to R6 (late‐season shade). Ambient sunlight was used as control (CK). Two hybrids, Zhengdan958 (ZD958) and Denghai 605 (DH605), were used. This study focused on accumulation and partition of dry matter (DM) and N based on the above treatments. Shading reduced DM and N accumulation of maize, which decreased yield. In addition, 15N stable isotope tracing revealed that shading disrupted N accumulation, partitioning, and remobilization in different organs. The contents of grain 15N in whole‐season shade, midseason shade, and late‐season shade from ZD958 decreased by 60, 28, and 50%, respectively, compared with those in CK, and DH605 decreased by 70, 32, and 51%, respectively. Our results indicate that yield decline can be mainly attributed to DM and that N accumulation and remobilization were disrupted by shading at different maize growth stages. Shading during the vegetative stage and reproductive stage reduced N accumulation, and shading during the reproductive stage mainly promoted N transport from other organs to grain, which mitigated some of the effects of reduced N absorption.

Effect of split nitrogen application on growth parameters of maize

A field experiment was designed to study the Effect of split nitrogen application on growth parameters of maize on research field of agricultural development trust, Baramati for two consecutive years during rainy season in 2017and 2018. An experiment was laid out in randomized complete block design with four replications. Four splits application of recommended dose of N were applied as 50% N at basal and 50% N at knee high stage (T1), 50% N at basal, 25% N 30 days after sowing and 25% N at tasseling stage (T2), 50% N at basal and remaining nitrogen as per Leaf Colour Chart (T3) and 30% N at basal, 30% N at 30 days after sowing and 30% N at tasseling stage (T4). Results showed that all studied parameters were significantly affected by application time of nitrogen. Experimental results exhibited that application of 50% N at basal and remaining nitrogen as per Leaf Colour Chart (LCC) has produced maximum plant height, number of leaves per plant and cob length. Results of these studies revealed that, application of N fertilizers based on leaf colour chart, would be more economical to minimize N losses from the soil and efficient use of N at critical growth and development stages of maize.

The Responses of Maize Yield and Water Use to Growth Stage-Based Irrigation on the Loess Plateau in China

Water scarcity is the major limiting factor to crop production in arid and semi-arid regions. Better understanding the response of crops to the time and intensity of water stress at different growth stages is helpful to optimize irrigation scheduling under water limited conditions. A 4-year (2013–2016) field experiment was conducted at Yangling on the Loess Plateau, to quantify the effects of timing and intensity of water stress on yield, actual evapotranspiration (ETa) and water use efficiency (WUE) of summer maize, and to identify the most sensitive stage of maize to water stress. Two deficit irrigation levels, i.e. 70 mm and 110 mm, were considered. For each irrigation level, irrigation was applied for any three of four key growth stages of maize: seedling (D1), jointing (D2), tasseling (D3) and grain filling (D4). The results showed that: (1) water stress at vegetative growth stages had higher yield response factors than that at reproductive growth stages, indicating the former tended to have greater effects on maize yield; (2) although maize yield increased linearly with ETa, the variations of yield and WUE with changed ETa were not synchronous. Low-level irrigation should be applied in the regions with severe water shortage to obtain the maximum WUE, while in regions with more water a crop can be irrigated based on sufficient irrigation scheduling; (3) the contour map of Yield-ETa-WUE indicated a greater effect of yield on WUE than that of ETa on WUE. When irrigation water is limited, high WUE can be achieved if it is applied at vegetative growth stages, while high yield can be achieved if more available water is applied at tasseling stage. Therefore, in order to develop a sustainable irrigation scheduling on the Loess Plateau, water availability and agriculture production goals (high WUE or high yield) should be taken into account together.

Improving CERES-Maize for simulating maize growth and yield under water stress conditions

• The CERES-Maize simulations were poor under the water stress conditions, especially with the seedling stage water stress. • The soil water conductivity coefficients were modified to improve maize growth simulations under water stress conditions. • The severe water stress during the seedling stage damaged the photosynthetic membrane and reduced RUE of maize. • A RUE factor was applied to the optimal RUE in the model to reflect the membrane damages on the maize growth. Water stress in different maize growth stages has different effects on maize growth and development. Accurately simulating these effects with a maize model are important to agriculture water management and savings. The objective of this study was to improve the performance of the Crop-Environment Resource Synthesis Maize (CERES-Maize) model for simulating maize (Zea mays L.) growth and yield under water stress conditions. The model was evaluated based on the measurements of phenology date, leaf area index (LAI), aboveground biomass, kernel weight, yield, and soil water content. Those data were collected from the planting to maturity of maize under both water stress and full irrigation conditions in the Guanzhong Plain, China from 2013 to 2015. Our results found that the model simulated those variables realistically under the full irrigation condition, while the simulations were poor under the water stress conditions, especially with the seedling stage water stress treatments. In this study, we included the water stress factor in the phenology calculation and modified the soil water conductivity coefficients to increase root water uptake and improve maize growth and yield simulations under the water stress conditions. In addition, we found the severe water stress during the seedling stage damaged the photosynthetic membrane and reduced the chlorophyll content in the leaf based on observations, significantly affecting the radiation use efficiency (RUE) during the later stages of maize growth without water stress. A linearly regressed RUE factor was applied to the optimal RUE in the CERES-Maize model to reflect such damages on the maize growth and yield. Our simulations of the aboveground biomass and yield were further improved by considering such a factor. Additional data were used to validate our modified model, and the simulated biomass and yield were also improved when compared to those generated by the original model. The results from this study provide strong insights into better maize growth and yield simulations in the water limited regions.

Estimating Plant Nitrogen Concentration of Maize Using a Leaf Fluorescence Sensor across Growth Stages

Nitrogen (N) is one of the most essential nutrients that can significantly affect crop grain yield and quality. The implementation of proximal and remote sensing technologies in precision agriculture has provided new opportunities for non-destructive and real-time diagnosis of crop N status and precision N management. Notably, leaf fluorescence sensors have shown high potential in the accurate estimation of plant N status. However, most studies using leaf fluorescence sensors have mainly focused on the estimation of leaf N concentration (LNC) rather than plant N concentration (PNC). The objectives of this study were to (1) determine the relationship of maize (Zea mays L.) LNC and PNC, (2) evaluate the main factors influencing the variations of leaf fluorescence sensor parameters, and (3) establish a general model to estimate PNC directly across growth stages. A leaf fluorescence sensor, Dualex 4, was used to test maize leaves with three different positions across four growth stages in two fields with different soil types, planting densities, and N application rates in Northeast China in 2016 and 2017. The results indicated that the total leaf N concentration (TLNC) and PNC had a strong correlation (R2 = 0.91 to 0.98) with the single leaf N concentration (SLNC). The TLNC and PNC were affected by maize growth stage and N application rate but not the soil type. When used in combination with the days after sowing (DAS) parameter, modified Dualex 4 indices showed strong relationships with TLNC and PNC across growth stages. Both modified chlorophyll concentration (mChl) and modified N balance index (mNBI) were reliable predictors of PNC. Good results could be achieved by using information obtained only from the newly fully expanded leaves before the tasseling stage (VT) and the leaves above panicle at the VT stage to estimate PNC. It is concluded that when used together with DAS, the leaf fluorescence sensor (Dualex 4) can be used to reliably estimate maize PNC across growth stages.

Response of Soil Temperature, Moisture, and Spring Maize (Zea mays L.) Root/Shoot Growth to Different Mulching Materials in Semi-Arid Areas of Northwest China

Adaptive highly efficient mulching technologies for use on dryland agricultural ecosystems are crucial to improving crop productivity and water-use efficiency (WUE) under climate change. Little information is available on the effect of using different types of mulch on soil water thermal conditions, or on root/shoot trait, leaf area index (LAI), leaf area duration (LAD), yield, and WUE of spring maize. Hence, in this study, white transparent plastic film (WF), black plastic film (BF), and maize straw (MS) was used, and the results were compared with a non-mulched control (CK). The results showed that the mean soil temperature throughout the whole growth period of maize at the 5–15 cm depth under WF and BF was higher than under MS and CK, but under BF, it was 0.6 °C lower than WF. Compared with CK, the average soil water storage (0–200 cm) over the whole growth period of maize was significantly increased under WF, BF, and MS. WF and BF increased the soil water and temperature during the early growth stages of maize and significantly increased root/shoot biomass, root volume, LAI, LAD, and yield compared with MS. Higher soil temperatures under WF obviously reduced the duration of maize reproductive growth and accelerated root and leaf senescence, leading to small root/shoot biomass accumulation post-tasseling and to losses in yield compared with BF

Prediction of maize growth stages based on deep learning

An accurate forecast of daily meteorological factors throughout the year is not only of great significance for the study of climate trends in a certain area but also enables the prediction of crop growth stages. Moreover, the prediction of crop growth stages is related to the scheduling of planting and tillage, the determination of machine harvest time, and the prediction of crop yield. However, highly complex dynamics cause large volatility in meteorological factors, so it is very challenging to predict the crop growth stage accurately, based on weather data. To solve this problem, we propose a data-driven encoder-decoder model, using long short-term memory (LSTM) and convolutional LSTM (ConvLSTM), which can be applied to forecast daily sunshine duration, cumulative precipitation, and average temperature for the coming year. To further test the performance of the ConvLSTM-based model, it is compared with the conventional LSTM encoder-decoder model and the convolutional neural network (CNN)-LSTM encoder-decoder model. The results demonstrate that, the ConvLSTM-based model is more accurate than the others for forecasting temperature (MAE = 2.602 °C, RMSE = 3.456 °C), precipitation (MAE = 3.878 mm, RMSE = 10.503 mm), andsunshine hours (MAE = 3.445 h, RMSE = 4.172 h) in 2014–2016. Furthermore, precise forecasting of meteorological factors allows us to develop a hybrid model and a data-driven model for the prediction of each growth stage separately. The hybrid model combines the ConvLSTM encoder-decoder model with empirical models, whereas the data-driven model comprises the ConvLSTM encoder-decoder model and traditional neural network structures. Finally, we compared the two types of models on a real-world dataset from Dandong, and concluded that the data-driven model is more accurate than the hybrid model for prediction of maize growth stages, with R2 in the range of 0.755–0.883, MAE 0.588–2.205 days, and RMSE 0.978–2.729 days. In the future, these models can also be used to predict the growth stages of other crops.

Development of critical nitrogen dilution curve based on leaf dry matter for maize under drip irrigation

To provide a theoretical reference to nitrogen fertilizer management for maize and eco-enviromental protection in the irrigated area of Ningxia, we established the critical nitrogen concentration (Nc) dilution curve of maize under drip-irrigated condition. The nitrogen nutrition index (NNI) was deduced from the established Nc curve model, to diagnose feasibility of nitrogen nutrition. Six levels of nitrogen application rates including 0, 90, 180, 270, 360 and 450 kg·hm-2 were conducted in field with maize variety 'Tianci 19'. During two-year field study, the Nc dilution curve and NNI model of maize were established based on leaf dry matter (LDM). The results showed that: 1) There was a negative power function relationship between LDM and Nc, which presented as two parts, if LDM<1.15 t·hm-2, Nc=3.2%, while if LDM≥1.15 t·hm-2, Nc=3.29LDM-0.29. 2) The root mean square error (RMSE) and standardized root mean square error (n-RMSE) of the model were 0.203 and 8.0%, respectively, with fine stability among years. 3) The NNI ranged from 0.47 to 1.44 with different nitrogen application rates. In addition, NNI was positively correlated with yield and negatively correlated with agronomic utilization efficiency of nitrogen fertilizer at different growth stages of maize. Therefore, NNI could be used to explain maize yield changes with and without nitrogen limit under drip-irrigated system. In conclusion, the critical nitrogen dilution curve established from leaf dry matter could be applied to accurately estimate nitrogen nutrition status throughout the whole growing stages from the jointing stage to silking stage of maize under drip irrigated system.

English

The African maize stem borer (Busseola fusca) is one of the important biotic constraints for maize production in sub-Saharan African. This study determined the spatial distribution and sampling sizes for African maize stem borer in Southern Ethiopia. Twenty four maize farms were visited in 12 localities at three growth stage of maize. Data were collected on the number of infested and not-infested plants, and the number of larvae and pupae. There were variations in the levels of infestations and population density of B. fusca in the study areas and years. Percent infestation at mid-whorl stage of maize ranged from 13.6 to 25.9% and 19.5 to 41.4% in 2015 and 2016, respectively. Infestation increased through time and at harvesting stage reached ranges of 36.8 to 68.8% in 2015 and 65.5 to 80.7% in 2016. The optimal sample size for four fixed precision levels of 0.10, 0.15, 0.20 and 0.25 were estimated with Iwao&rsquo;s regression coefficients. The distribution pattern of B. fusca varied between maize growth stages, locations and years. At mid-whorl stage of maize, B. fusca infested plants were aggregated but in both at silking and harvesting stage uniformly distributed. At mid-whorl as well as silking stage of maize B. fusca larvae were aggregated. But, larvae at harvesting stage and pupae in both silking and harvesting stages of maize were randomly distributed. For 10% infestation, which is considered as action threshold level for stem borers management on maize, 22 sampling units (660 plants) at the precision of 20% are required. Key words: Busseola fusca, maize, spatial distribution, sample size, precision level.

Hyperspectral monitoring of maize leaves under copper stress at different growth stages

ABSTRACTUsing hyperspectral remote sensing technology to identify spectral changes of crop leaves under heavy metal pollution is an important way to ensure food security. Discrete Fourier transform (DFT) and discrete wavelet transform (DWT) are used to rapid screen the spectral characteristics of maize growth status under copper (Cu) stress, and a zero-crossing rate (ZCR) was proposed to quantify the results. The experiment of maize under different Cu stress treatment was carried out, and the spectra of maize leaves at seedling, jointing and heading stages were measured. Analysis of frequency spectrum and amplitude spectrum of the maize leaves spectra under copper stress showed that the growth stages of maize could be effectively determined according to the phase of leaves spectra. The approximate coefficient (CA) and detail coefficient (CD) were obtainedat heading stage. It was found that the wavelength corresponding to the peak value of the acquired variable of CA (ca) in the range of 690–710 nm was moving in the direction of shortwave. In addition, the degree of copper stress in maize could be divided according to the peak deviation of ca. The characteristic wavebands could be detected according to the CD variable (cd) .

Changes in landscape composition influence the abundance of insects on maize: The role of fruit orchards and alfalfa crops

The traditional agricultural landscape of Ebro Basin (NE Spain), which is mainly composed of alfalfa and cereal crops, has undergone changes in recent years, mainly consisting of an increase in the area occupied by intensively managed irrigated orchards. Recently, it has been reported that the presence of a higher proportion of orchards in the landscape and their management negatively affect the abundance and diversity of natural enemies. Two hypotheses are tested in this study: (1) the increased orchard surface has led to a reduction in natural enemies in neighbouring maize crops, and (2) the higher alfalfa proportion of agricultural land enhances the predatory fauna on maize. Maize fields were selected across a landscape gradient created by orchards and field crops (alfalfa and maize) in a buffer of 500 m. The abundance of 17 insect taxa in each maize field was estimated by means of 3 yellow sticky traps per season over three years. The insect abundance was related to the landscape structure (proportions of landscape elements and landscape diversity) and local variables (maize phenology, perimeter/area, weed diversity of the maize edges and abundance of the potential predators or potential prey). Our results show that the proportion of orchards in the landscape had negative effects on the main predators, and alfalfa had positive effects on herbivores and their predators. Semi-natural habitats (non-crop habitats and forest) and landscape diversity had low effects on insect abundance. However, variables at the local level included more significant effects than landscape structure; maize growth stages and abundance of potential prey or predators on the crop were the most influential variables at a local level. Here we show the interplay between different land uses types and local management and their impact on natural enemies and herbivores in maize crops in the Mediterranean area.

Phenotyping analysis of maize stem using micro-computed tomography at the elongation and tasseling stages

BackgroundMicro-computed tomography (μCT) bring a new opportunity to accurately quantify micro phenotypic traits of maize stem, also provide comparable benchmark to evaluate its dynamic development at the different growth stages. The progressive accumulation of stem biomass brings manifest structure changes of maize stem and vascular bundles, which are closely related with maize varietal characteristics and growth stages. Thus, micro-phenotyping (μPhenotyping) of maize stems is not only valuable to evaluate bio-mechanics and water-transport performance of maize, but also yield growth-based traits for quantitative traits loci (QTL) and functional genes location in molecular breeding.ResultIn this study, maize stems of 20 maize cultivars and two growth stages were imaged using μCT scanning technology. According to the observable differences of maize stems from the elongation and tasseling stages, function zones of maize stem were firstly defined to describe the substance accumulation of maize stems. And then a set of image-based μPhenotyping pipelines were implemented to quantify maize stem and vascular bundles at the two stages. The coefficient of determination (R2) of counting vascular bundles was higher than 0.95. Based on the uniform contour representation, intensity-related, geometry-related and distribution-related traits of vascular bundles were respectively evaluated in function zones and structure layers. And growth-related traits of the slice, epidermis, periphery and inner zones were also used to describe the dynamic growth of maize stem. Statistical analysis demonstrated the presented method was suitable to the phenotyping analysis of maize stem for multiple growth stages.ConclusionsThe novel descriptors of function zones provide effective phenotypic references to quantify the differences between growth stages; and the detection and identification of vascular bundles based on function zones are more robust to determine the adaptive image analysis pipeline. Developing robust and effective image-based phenotyping method to assess the traits of stem and vascular bundles, is highly relevant for understanding the relationship between maize phenomics and genomics.

Soil water dynamics and yield in maize and Brachiaria ruziziensis intercropping

ABSTRACT In intercropping systems, a high plant density can delay the biomass accumulation and affect the water availability to plants. This study aimed to evaluate the soil water dynamics and the crop yield performance in maize and Brachiaria ruziziensis intercropping under different sowing densities of the forage grass. The experiment was conducted in a randomized block design, with treatments associated to the sowing densities (2 kg ha-1, 4 kg ha-1, 6 kg ha-1 and 8 kg ha-1) and the single cropping for both species as controls. The maize plants were evaluated for grain yield and B. ruziziensis for number of plants per hectare and shoot fresh and dry matter. The intercropping performance was evaluated using the land-use efficiency index. The soil water dynamics was monitored in two soil depths (0-0.3 m and 0.3-0.6 m) by using the time domain reflectometry method. The evaluation of soil water storage was carried out from plots with four of the crop systems (single maize or B. ruziziensis, and intercropping with the extreme sowing densities), at four different times. The increase in the sowing density of B. ruziziensis decreased the grain yield of the intercropped maize by 30.8 %. The intercropping system using 2 kg ha-1 of the grass seeds resulted in the best land-use efficiency (23 %). In addition, the intercropping treatments promoted a higher extraction of water from the soil, mainly at the maize growth stages with higher hydric demand (e.g., flowering and grain filling). These systems stimulate the extraction of water from deeper soil layers, when compared to maize in single cropping.

Effects of slow-release urea combined with common urea application layered in different soil depths on soil nitrogen, enzyme activity, and maize yield

We examined the effects of a combination of slow-release urea (PCU) and common urea (PU) applied at different soil depths (0-30 cm soil layer) on inorganic nitrogen content, enzyme activity, and crop yield during two years (2017-2018) in a field experiment. There were eight treatments: CK (without N fertilizer); PU1(common urea applied at 5-10 cm deep soil layer); PU2(common urea applied at 5-10 cm deep soil layer, 60% seed fertilizer + 40% topdressing); PU3(20% common urea at 5-10 cm soil depth, 30% common urea at 15-20 cm soil depth, 50% common urea at 25-30 cm soil depth); PCU1(20% total nitrogen application rate at 5-10 cm soil depth, 30% total nitrogen application rate at 15-20 cm soil depth, 50% total nitrogen application rate at 25-30 cm soil depth), the N fertilizer at 5-10 cm was common urea, but, at 15-20 and 25-30 cm, it was a combination of PCU and PU at ratios of 3:7 and 3:7; PCU2 was as PCU1 but the ratio of PCU and PU was 5:5 at 15-20 cm and 5:5 at 25-30 cm; in PCU3, the ratio of PCU and PU was 3:7 at 15-20 cm and 5:5 at 25-30 cm; in PCU4, the ratio of PCU and PU was 5:5 at 15-20 cm and 3:7 at 25-30 cm. The results showed that PU1 could meet nitrogen demand at the 0-10 cm layer in the early growth stage compared with CK. PU2 and PU3 could meet nitrogen demand for 10-30 cm soil layer in the early stage of maize development. The combined application of slow release urea and common urea could meet nitrogen demand for the whole growth period of maize. In the filling and maturing period, combined application of slow release and common urea significantly increased not only NO3--N, NH4+-N, and alkali-hydrolyzed nitrogen contents but also urease and protease activities in the 10-20 cm and 20-30 cm soil layers compared with PU1-PU3. Compared with PU3, maize yield increased by 2.3%-24.6% and 1.3%-16.5% in the PCU1-PCU4 treatments in 2017 and 2018, respectively. PCU4 had the highest yield, with 13899 and 12439 kg·hm-2, respectively. Therefore, the combined application of slow-release and common urea at different soil layers could meet nitrogen demand in the early growth stage of maize and increase the content of inorganic nitrogen and enzyme activities in the 10-30 cm soil layers in the later growth period, which promoted the growth and increased the yield of maize. Among all the treatments PCU4 treatment was the most effective.

Carbon and nitrogen fractions in soil during maize growth under long-term fertilizer management practices to maize-wheat cropping

A field experiment was conducted to study the effect of long-term fertilizer management (viz. control, 100% N, 100% NP, 100% NPK and 100% NPK+FYM) on the carbon (C) and nitrogen (N) fractions in soils under maize-wheat cropping. Soil samples were collected from on-going experiment (started in 1971) during maize growing season in kharif 2011 to discern long-term effect of field treatments on changes in different pools of C and N viz. soil organic C (SOC), water soluble C (WSC) and KMnO₄ oxidizable C (KMnO₄-C) and ammonical-N (NH₄⁺-N) and nitrate-N (NO₃⁻-N) content. Soil samples were analyzed after 1, 3, 5, 7 and 9 weeks interval during maize growth period. The SOC, NO₃⁻-N and NH₄⁺-N concentration increased significantly with combined application of NPK+FYM as compared to the control. The concentration of SOC increased after 3 weeks, and was reached the highest at harvesting. However, the WSC and KMnO₄-C concentration increased up to 5ᵗʰ week after sowing and it decreased afterwards. The NO₃⁻-N and NH₄⁺-N concentration decreased with increased maize growth stage, and decreased to the lowest value at harvesting. The dry matter yield of maize at maturity correlated well with SOC, WSC, KMnO₄-C, NH₄⁺-N and NO₃⁻-N concentration. Crop yield of maize and N uptake increased with NPK+FYM application at all growth stages.

Nitrogen, phosphorus and potassium content in maize dry biomass under the effect of different levels of mineral fertilization

Abstract. The aim of the study was to assess the influence of different fertilizer doses on the content of macroelements (nitrogen, phosphorus and potassium) in dry biomass and grain of maize during the 2016 – 2018 period. A field experiment with fertilization of maize was carried out on Alluvial-meadow soil (Fluvisol) in the region of Tsalapitsa village, near Plovdiv. Three variants of mineral fertilization were studied V2 (N15P10K0), V3 (N20P15K0) and V4 (N25P20K0), and a control variant V1 (N0P0K0) – without fertilization. It was established that N% content in maize dry biomass was affected significantly by the variants of fertilization (18% of the variance). Significant differences (P≤0.05) between the control variant and all the variants of fertilization were established. Increasing the fertilizer dose, nitrogen content in dry biomass increased, too. The highest was the average content of nitrogen in maize leaves (0.94%), followed by the cobs (0.71%) and the lowest was the content in the stems (0.58%). Phosphorus and potassium content of dry biomass were affected significantly by the year of the study (10% and 9% of the variance, respectively). At the 7-8th leaf growth stage of maize, the highest nutrients content (N, P, K) in dry biomass were reported. With aging of plants the nutrient content in their biomass decreased. Nitrogen, phosphorus and potassium content in maize grain was significantly affected by the year of the experiment. Mineral fertilization had impact mostly on the nitrogen content of the grain, which was the highest in V3 variant, accepted as optimal – 0.66% on average.

Estimation of maize yield and effects of variable-rate nitrogen application using UAV-based RGB imagery

Accurate crop yield estimation is important for agronomic and economic decision-making. This study evaluated the performance of imagery data acquired using a unmanned aerial vehicle (UAV)-based imaging system for estimating yield of maize (Zea mays L.) and the effects of variable-rate nitrogen (N) application on crops. Images of a 27-ha maize field were captured using a UAV with a consumer-grade RGB camera flying at ~100 m above ground level at three maize growth stages. The collected sequential images were stitched and the Excess Green (ExG) colour feature was extracted to develop prediction models for maize yield and to examine the effect of the variable-rate N application. Various linear regression models between ExG and maize yield were developed for three sample area sizes (21, 106, and 1058 m2). The model performance was evaluated using coefficient of determination (R2), F-test and the mean absolute percentage error (MAPE) between estimated and actual yield. All linear regression models between ExG and yield were significant (p ≤ 0.05). The MAPE ranged from 6.2 to 15.1% at the three sample sizes, although R2 values were all

Solar-induced chlorophyll fluorescence and its link to canopy photosynthesis in maize from continuous ground measurements

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides great potential for estimating gross primary production (GPP) of terrestrial ecosystems. A strong relationship between SIF and GPP has been observed at the seasonal scale from both ground-based and satellite observations. However, variations of SIF due to changes in plant growth stages appear to influence the SIF-GPP relationship. It remains unclear how this relationship is affected by plant growth-related changes, especially for C4 plants such as maize. In this study, continuous in situ measurements for canopy far-red SIF retrieval and GPP calculation were made in maize during the growing season of 2017. Diurnal and seasonal variations of canopy SIF and its yield (SIFyield) were analyzed over different growth stages of maize to understand how they affect the relationship with GPP. The results show that the relationship between SIF and GPP varies with the growth stages of maize during the growing season, indicating that canopy structure has a strong impact on the seasonal variations of canopy SIF and its relation to GPP. Furthermore, we found that SIFyield is significantly correlated with canopy photosynthetic light use efficiency (LUE) at the canopy level throughout the season. However, it is almost uncorrelated with LUE after adjusting for the effects of canopy structure with the structural vegetation index MTVI2. This finding highlights the importance of canopy structure in the relationship between SIFyield and LUE, complicating the use of canopy SIF for tracking vegetation physiological activity. Overall, our observation-based findings show that canopy structure affects the SIF-GPP relationship, strengthening our understanding of the mechanistic link between SIF and photosynthesis.

Plant Growth Regulator-Brassinolide for Mitigating Field Waterlogging Stress on Maize

Aim: To assess the pleiotropic role of a plant growth regulator, commercially identified as brassinolide (BR) in mitigating waterlogging stress imposed on maize.&#x0D; Study Design: A factorial combination of two maize varieties [Ikom White (IKW) and Oba-98], two BR levels (0 and 250 ml) and two waterlogging stages of maize growth [control (WL0) and seedling stage (WL1)], arranged as a split-split plot in a randomized complete block design with three replications was used.&#x0D; Place and Duration of Study: Akpabuyo Local Government Area, Cross River State-Nigeria. A two-year field experiment was conducted during the dry seasons of December 2016 and December 2017.&#x0D; Methodology: Waterlogging test was conducted on plots by demarcating them with 3.6 by 1.7 m metal sheets buried to a depth of 60 cm to prevent lateral soil-water movement. Two maize seeds were sown at 25 cm within and 75 cm between rows. The BR (250 ml) was sprayed foliar at 21 DAS. The non-waterlogging plots served as control. Observations were made on growth and yield variables as well as the plant's physiological traits.&#x0D; Results: Waterlogging significantly reduced the growth attributes of maize and increased (p≤0.05) the leaf moisture content. The photosynthetically active radiation on maize plants was substantially reduced (p≤0.05) by the waterlogging stress. Dry matter yield (DMY) and nutrient uptake in the leaves, stems and grains were reduced (p≤0.05) at both silking and at harvest. The effect of the BR was greater in Oba-98 with higher nutrient contents, radiation absorption, dry matter and grain yields than IKW.&#x0D; Conclusion: Treatment of maize plants with BR could induce some tolerance of field waterlogging. Thus, for optimum efficiency in maize production under stressed soil condition of waterlogging, it is recommended that the foliar spray of BR at the 250 ml per plant rate be considered.