Rainfed Maize Crop Research Articles

Crop classification and weed detection in rainfed maize crops using UAV and PlanetScope imagery

Crop classification and weed detection in rainfed maize crops using UAV and PlanetScope imagery

The Interactive Impact of Straw Mulch and Biochar Application Positively Enhanced the Growth Indexes of Maize (Zea mays L.) Crop

A two-year experiment was carried out at Shenyang Agricultural University’s research field area in China to evaluate the impact of the combined application of straw mulch (0 and 8 t ha−1) and biochar (0, 4, 12, and 36 t ha−1) on the morphological traits and grain development of rainfed maize during 2018 and 2019. The results showed that straw mulch and different biochar application rates significantly impacted the maize growth index. Compared to non-biochar-treated soils, the introduction of straw mulch improved plant height, stem diameter, leaf area index (LAI), leaves, stem, root, and crop growth rate (CGR), and dry weight of rainfed maize crop. The highest plant height, stem diameter, LAI, leaves, stem, root growth rate, CGR, and dry weight of rainfed maize crop were reported when soil was treated with a higher rate of biochar (36 t ha−1). Biochar increased grain filling rate while decreasing grain filling duration in rainfed maize crops. Our results indicate that straw mulch and biochar-based soil management strategies can improve the rainfed maize growth with the environmental benefits of global warming mitigation. However, due to the wide range of biochar properties, the interactions between straw mulch and biochar should be given special consideration in the maize cropping system.

The residual impact of straw mulch and biochar amendments on grain quality and amino acid contents of rainfed maize crop

The inability of humans and many farm animals to synthesize certain amino acids has long triggered tremendous interest in increasing the levels of these so-called essential amino acids in crop plants. Hence, a two-year field experiment was conducted to evaluate the effects of straw mulch (8 t ha−1) and biochar applied at various rates (0, 4, 12, 36 t ha−1) on the chlorophyll, photosynthesis, total nitrogen in soil, essential and nonessential amino acid (AA) contents of maize grain. The maize straw mulch and biochar significantly increased chlorophyll contents, photosynthesis rate of maize crop and total soil nitrogen. The application of biochar (12 t ha−1) increased the chlorophyll contents and photosynthesis rate and total soil nitrogen during both years. However, excessive biochar applications (more than 12 t ha−1) had negative effects on chlorophyll contents, photosynthesis rate of maize crop and total soil nitrogen of soil. The AAs were significantly affected by biochar, depending on the application rate. In conclusion, the application of straw mulch and biochar improved the rate of leaf chlorophyll contents, photosynthesis rate and amino acid contents in maize grain when applied at appropriate rates, but the effects were negative when biochar was overused.

Effects of different tillage practices and nitrogen application rate on carbon dioxide emissions and carbon balance in rain-fed maize crops

Effects of different tillage practices and nitrogen application rate on carbon dioxide emissions and carbon balance in rain-fed maize crops

Land suitability levels for rainfed maize under current conditions and climate change projections in Mexico

An assessment of land suitability classes for rainfed maize (spring–summer agricultural cycle) with current climate conditions (1950–2000) and projected climate change scenarios was carried out for Mexico. The method considered the most restrictive factors or agroclimatic requirements from different variables needed by rainfed maize. These factors were analyzed spatially in a geographic information systems (GIS) context, resulting in areas classified into four suitability levels: high, medium, low, and not suitable for maize. We considered two general circulation models (GCM): HADGEM2-ES and MPI-ESM-LR; one radiative forcing concentration representative concentration pathways (RCP) 8.5 Wm−2 and the far period (2075–2099). Results at a national-level analysis showed that under actual conditions, 57.5% of the area of Mexico presents some level of suitability for rainfed maize. The high suitability class is 11.4% of the country, while 20.7% and 25.3% had medium and low suitability levels, respectively. Other results showed that with the HADGEM2-ES and MPI-ESM-LR projections of climate change models, 50.4% and 46.7%, of Mexico’s continental area, respectively, present some level of suitability for the rainfed maize crop. In the first case, with respect to the present climate conditions, the HADGEM2-ES model presented an area decrease of −2.4% and the MPI-ESM-LR model of −5.5% in the high suitability level for the rainfed maize crop. Results at a state-level analysis showed there are five states (Jalisco, Campeche, Oaxaca, Chiapas, and Michoacán) in the interval of more than 50,000 km2 of surface with high and medium suitability levels, with a maximum extent change between the present to the projected climate conditions of −46% for the HADGEM2-ES and −57% for the MPI-ESM-LR. In general, the MPI-ESM-LR model showed the most adverse projected conditions for rainfed maize growth.

Rainfall and crop modeling-based water stress assessment for rainfed maize cultivation in peninsular India

Water stress due to uneven rainfall distribution causes a significant impact on the agricultural production of monsoon-dependent peninsular India. In the present study, water stress assessment for rainfed maize crop is carried out for kharif (June–October) and rabi (October–February) cropping seasons which coincide with two major Indian monsoons. Rainfall analysis (1976–2010) shows that the kharif season receives sufficient weekly rainfall (28 ± 32 mm) during 26th–39th standard meteorological weeks (SMWs) from southwest monsoon, whereas the rabi season experiences a major portion of its weekly rainfall due to northeast monsoon between the 42nd and 51st SMW (31 ± 42 mm). The later weeks experience minimal rainfall (5.5 ± 15 mm) and thus expose the late sown maize crops to a severe water stress during its maturity stage. Wet and dry spell analyses reveal a substantial increase in the rainfall intensity over the last few decades. However, the distribution of rainfall shows a striking decrease in the number of wet spells, with prolonged dry spells in both seasons. Weekly rainfall classification shows that the flowering and maturity stages of kharif maize (33rd–39th SMWs) can suffer around 30–40% of the total water stress. In the case of rabi maize, the analysis reveals that a shift in the sowing time from the existing 42nd SMW (16–22 October) to the 40th SMW (1–7 October) can avoid terminal water stress. Further, AquaCrop modeling results show that one or two minimal irrigations during the flowering and maturity stages (33rd–39th SMWs) of kharif maize positively avoid the mild water stress exposure. Similarly, rabi maize requires an additional two or three lifesaving irrigations during its flowering and maturity stages (48th–53rd SMWs) to improve productivity. Effective crop planning with appropriate sowing time, short duration crop, and high yielding drought-resistant varieties will allow for better utilization of the monsoon rain, thus reducing water stress with an increase in rainfed maize productivity.

Management and health of three corn farming systems in the region of Llanos de San Juan, Puebla, Mexico

ABSTRACTIn this study, the effects of rainfed maize crop management on agroecosystem health was studied. In the state of Puebla, three systems were analyzed: traditional agriculture (TA), conservation agriculture (CA), and conventional agriculture (CVA). A methodological proposal for evaluation was developed through the Agroecosystem Health Index on an interval scale (0–5), to which a cluster analysis and an ordinal scale (1–3) were applied. Finally, the variance of the data was analyzed under a bifactor design (management, site). The variables of study were chemical, physical, and biological properties of the soil, as well as annual net income of the production unit. The interval scale applied to the chemical properties of the soil indicates that TA has better conditions for growing corn, with a score of 3.6, followed by CA with 3.5, and CVA with 3.3. The cluster analysis only showed correlation with the order of the scores for the type of management. The ordinal scale showed a holistic view of the conditions of the plot’s resources and CA was ranked first, followed by CVA and TA, for their ability to promote the health of the agroecosystem. A statistically significant effect of the management was found in all chemical and physical soil properties, whereas for the biological factors it was necessary to analyze the dominant taxonomic groups.

Regional analysis of climate variability at three time scales and its effect on rainfed maize production in the Upper Lerma River Basin, Mexico

This study explored climate variability in the Upper Lerma River Basin, State of Mexico, Mexico, at three timescales: annual (1960–2010), monthly (1980–2010) and seasonal (1980–2010). The effects of monthly and seasonal (2003–2010) variability on rainfed maize crops were also evaluated. The variables of rainfall, maximum temperature, minimum temperature and number of hailstorms were interpolated to generate monthly spatial-temporal series. Over a period of 51 years, the climate of the region shows an accumulative annual increase of 131mm in rainfall and an increase of 0.8 and 0.74°C in maximum and minimum temperature, respectively. In conclusion, significant changes in the climate variables were found at the three analyzed timescales. Seasonal climate changes were found to coincide with the most vulnerable stage or flowering period of maize; particularly, a shift in the rainfall pattern generates a water deficit that impacts production yield. Hailstorms have increased in frequency, yet their phase shift results in a lesser impact to maize during its most critical stage of development.

Water use by a groundwater dependent maize in a semi-arid region of Inner Mongolia: Evapotranspiration partitioning and capillary rise

This study aimed at assessing the soil water balance, groundwater contribution, crop transpiration and soil evaporation of a rainfed maize crop in Horqin sandy area, north-eastern Inner Mongolia, China. Two years of field data from the Agula site were used, 2008 with relatively high rainfall (363mm) and high water table, and 2009 with low rainfall (125mm) and lower water table. The SIMDualKc water balance model was calibrated with observed soil water content data of 2008 and validated with data of 2009. The model uses the dual crop coefficient approach for evapotranspiration (ET) partitioning, and parametric functions for computing capillary rise. The respective modelling results show that the groundwater contribution represented ca. 50% of crop ET in both years. Estimation errors are small, with root mean square errors of 0.007 and 0.008cm3cm−3 respectively in 2008 and 2009. The Nash and Sutcliffe modelling efficiency were high, 0.93 in both years, which indicates a low variance of residuals. The calibrated basal crop coefficient Kcb mid=0.95 denotes a low density of the crop because it is much lower than common potential values. Soil evaporation was relatively low, 23% of ET in the wet year and 17% in the dry year, because capillary rise does not contribute to soil evaporation but to roots extraction only. Results show that capillary rise plays a main role in supplying the vegetation throughout the season, hence a strong dependence of vegetation upon groundwater.

A simple agroclimatic index to delineate suitable growing areas for rainfed maize production in the Free State Province of South Africa

The risk associated with climate and its variability over the Free State Province of South Africa is the major determining factor for agricultural productivity and has a major impact on food security in that region. In this study, suitability of planting a rainfed maize crop in the province was investigated using an agroclimatic index. The index is formulated from the combination of frost probability over the growing period, non-exceedence probability of onset of rains and agricultural drought index. The Poone AgroClimatic Suitability Index (PACSI) was introduced to integrate the major climate hazards affecting maize production in the Free State. The index was further used to delineate suitable areas across the Free State for planting a maize variety requiring 1420 growing degree days (heat units) to maturity. The resulting maps show areas of high maize production suitability over the Thabo Mofutsanyane district from mid-October to early November. Areas over Fezile Dabi and northern parts of the Lejweleputswa district also showed high suitability of maize especially from mid-November to the end of December. The western and southern Xhariep district is not suited for planting maize while other marginal dryland maize production areas include western Motheo, southwestern Lejweleputswa and most parts of the central and eastern Xhariep districts. Comparison of the index with maize yields and crop model outputs shows a good agreement in most stations and areas respectively and thus, PACSI can be used to delineate areas suitable for planting maize in the Free State Province of South Africa.

Evapotranspiration of irrigated and rainfed maize–soybean cropping systems

We have been making year-round measurements of mass and energy exchange in three cropping systems: (a) irrigated continuous maize, (b) irrigated maize–soybean rotation, and (c) rainfed maize–soybean rotation in eastern Nebraska since 2001. In this paper, we present results on evapotranspiration (ET) of these crops for the first 5 years of our study. Growing season ET in the irrigated and rainfed maize averaged 548 and 482 mm, respectively. In irrigated and rainfed soybean, the average growing season ET was 452 and 431 mm, respectively. On average, the maize ET was higher than the soybean ET by 18% for irrigated crops and by 11% for rainfed crops. The mid-season crop coefficient K c (=ET/ET 0 and ET 0 is the reference ET) for irrigated maize was 1.03 ± 0.07. For rainfed maize, significant dry-down conditions prevailed and mid-season K c was 0.84 ± 0.20. For irrigated soybean, the mid-season K c was 0.98 ± 0.02. The mid-season dry down in rainfed soybean years was not severe and the K c (0.90 ± 0.13) was only slightly lower than the values for the irrigated fields. Non-growing season evaporation ranged from 100 to 172 mm and contributed about 16–28% of the annual ET in irrigated/rainfed maize and 24–26% in irrigated/rainfed soybean. The amount of surface mulch biomass explained 71% of the variability in non-growing season evaporation totals. Water use efficiency (or biomass transpiration efficiency), defined as the ratio of total plant biomass ( Y DM) to growing season transpiration ( T) was 5.20 ± 0.34 and 5.22 ± 0.36 g kg −1, respectively for irrigated and rainfed maize crops. Similarly, the biomass transpiration efficiency for irrigated and rainfed soybean crops was 3.21 ± 0.35 and 2.96 ± 0.30 g kg −1. Thus, the respective biomass transpiration efficiency of these crops was nearly constant regardless of rainfall and irrigation.

Trends of Rainfall and Maize Productivity in Malawi

Daily rainfall data between 1966 and 2005 across all Agricultural Development Areas (ADDs) in Malawi was investigated to determine changes in selected rainfall characteristics and their impact on Maize productivity. Rainfall indices analyzed included rainfall amounts (annual and seasonal), onset, cessation, dry spells and length of rainy season. Man Kendal’s trend test was applied to the time series of these indices to detect any trends in the time series. WaterRequirement Satisfaction Index (WRSI) for maize crop was used to study the spatial-temporal variation of maize productivity and thus its linkage to rainfall. Definition of onset and cessation adopted from the Department of Meteorological Service (DMS) Malawi was used in demarcating seasons to extract seasonal rainfall amount, length and other parameters. The results of the study indicate that with the exception of Karonga ADD located at the Northern tip of the country there were no significant trends in all variables related to crop productivity including onset, cessation, rainfall amount and dry spells. The spatial and temporal variability of maize production in Malawi was captured quite well by the WRSI. The relationship between long-term average WRSI and maize yield (tonnes/ha) for different stations in Malawi had a correlation coefficient of 0.82 while the relationship of countrywide average WRSI and maize yield had a correlation coefficient of 0.75. Areas with low long term average WRSI like Shire valley also showed low productivity while those with higher WRSI like Mzimba and Salima ADD had a good yield. On average Malawi has sufficient rainfall to sustain rain-fed maize crop as most of the time (67%) rain-fall is enough to give an average yield. It was also foundout that Malawi experience droughts and hence food shortages when WRSI value is close to or below 60%.

Vulnerability of rainfed maize crops in Mexico to climate change

The impacts of a potential climate change on rainfed maize crops in Mexico are analyzed. For that purpose, baseline scenanos based on current climate conditions and their relation with maize crop development were created. Climate change scenarios were further developed and the crop vulnerability under each scenario was assessed. Two methods were used to quantify vulnerability. In the first place, maps describing the suitability for crop production accorhng to climate conditions were produced. The differences between the baseline and the climate change scenarios allowed for estimating the area of the country likely to be positively or negatively affected. Secondly, the CERES-Maize model was applied to estimate rainfed maize crop yields at 7 sites in Mexico under the baseline and climate change scenarios. Adaptive measures were proposed and their feasibility was assessed on the basis of a simple cost-benefit analysis.