Yield Potential Of Maize Research Articles

The impacts of spring basal and side dressing on maize yield

The yield potential of maize is very high. According to Tollenaar (1983), maize yield potential is as high as 25 t ha-1 (absolute dry yield) which is the highest among all cereals. In order to fully utilise this high yield potential, proper nutrient replenishment is of chief importance among all agrotechnical factors.
 The aim of research was to examine the effect of nitrogen fertiliser applied as basal and side dressing on maize yield.
 The measurements were performed at the Látókép experiment site (47° 33’ N, 21° 26’ E, 111 m asl) of the Centre for Agricultural Sciences of the University of Debrecen on mid-heavy calcareous chernozem soil with deep humus layer in an established experiment in 2011, 2012 and 2013. The trial design was split-split-plot with two replications.
 Based on the experiment results, it can be established that the nutrient uptake of maize is greatly dependent on the amount of water store in the soil. From the aspect of the development of the maize plant and water supply, the most determinant factor was the distribution of precipitation over the growing season and not the amount precipitation. This is shown by the fact there was only 276 mm precipitation – which was favourably distributed – in 2012 to increase the availability of nutrients and the main average was the highest in this year (14.394 t ha-1).
 Spring basal dressing helped maize development in all three years even on chernozem soil which is well supplied with nutrients. Although the effect of side dressing did not result in any yield increase, it could still contribute to mitigating the stress effects caused by environmental factors. Altogether, nutrient supply adapted to the various development stages of maize can favourably affect the success of maize production.

A Crop Model and Fuzzy Rule Based Approach for Optimizing Maize Planting Dates in Burkina Faso, West Africa

AbstractIn sub-Saharan Africa, with its high rainfall variability and limited irrigation options, the crop planting date is a crucial tactical decision for farmers and therefore a major concern in agricultural decision making. To support decision making in rainfed agriculture, a new approach has been developed to optimize crop planting date. The General Large-Area Model for Annual Crops (GLAM) has been used for the first time to simulate maize yields in West Africa. It is used in combination with fuzzy logic rules to give more flexibility in crop planting date computation when compared with binary logic methods. A genetic algorithm is applied to calibrate the crop model and to optimize the planting dates at the end. The process for optimizing planting dates results in an ensemble of optimized planting rules. This principle of ensemble members leads to a time window of optimized planting dates for a single year and thereby potentially increases the willingness of farmers to adopt this approach. The optimized planting date (OPD) approach is compared with two well-established methods in sub-Saharan Africa. The results suggest earlier planting dates across Burkina Faso, ranging from 10 to 20 days for the northern and central part and less than 10 days for the southern part. With respect to the potential yields, the OPD approach indicates that an average increase in maize potential yield of around 20% could be obtained in water-limited regions in Burkina Faso. The implementation of the presented approach in agricultural decision support is expected to have the potential to improve agricultural risk management in these regions dominated by rainfed agriculture and characterized by high rainfall variability.

Identification of Heterotic Pairs by Full-Sib Reciprocal Recurrent Selection in Maize Synthetic Populations on Turda CompositeA(B)(2) x Turda CompositeB(A)(2)

In the last 40 years, pre-breeding works induced, in more and more centers of maize breeding, full-sib reciprocal recurrent selection programmes to identify some heterotic pairs which can be sources for obtaining performance inbred lines. The aim is to identify the heterotic pairs with the best results according to the yield potential of maize, the breaking and falling resistance, and the grains moisture at the harvesting time. The creation programme of A and B composite population started at ARDS Turda in 1985. Inside of A composite came the next inbred lines: B73, A632, M117, TC209, T291, being from the B SSS heterotic group, and inside of B composite came the inbred lines Mo17, C103, TC 208, T248, W633, appreciated by us or being related to Lancaster Sure Crop heterotic group. The experimentation was done in two orientation comparative cultures, each one with 49 variants, in 4 repetitions; the comparative culture was a balanced quadratic grid of 7x7 type. From each culture were chosen the first six variants, which were evaluated according to the next characters: production potential, breaking and falling resistance, grains moisture at harvest. The presented results are a part from the second cycle of full-sib reciprocal recurrent selection. Test crosses and self-pollinations were made on plants from the two composites which had two cobs; on the first cob from A Composite realised the cross with the corresponding plant from the B Composite, and from the plant panicle of the B Composite was collected pollen to pollinate the chosen plant from the A Composite. At the both plants from the crossing, the second cob was self-pollinated and kept in reserve until 2010, when the test crosses was experimented and were selected the pairs with the best results according to the above characters. Using the full-sib reciprocal recurrent selection, we can successfully harnessing, simultaneously, the additive and non-additive gene effects.

Adaptability of APSIM Maize Model in Northeast China

The APSIM (Agricultural Production Systems Simulator) model was introduced to simulate maize growth, development and yields in Northeast China using the field experimental data and climate data collected from six typical agricultural meteorological stations in the studied area. APSIM was calibrated using the first part of data to determine the varietal parameters, then simulated the growing periods, leaf area index (LAI), total above-ground biomass and yields using the second part of data at each site. The results showed that there was a good agreement between the simulated and measured values in growing periods. The difference of growing periods from sowing to emergence, from sowing to flowering and from sowing to maturity between simulated and measured data was 0–2.0, 0.7–2.0, and 0.7–2.3 d, respectively. The Normalized Root Mean Square Error (NRMSE) values for measured and simulated LAI and total above-ground biomass in Harbin station were 33% and 11%, respectively. NRMSE values for measured and simulated yield in Harbin, Hailun, Tailai, Huadian, Tonghua, and Benxi station were 18%, 13%, 4%, 4%, 5%, and 2%, respectively. These re-sults indicated that APSIM model has good ability to simulate the growing periods, dynamic process of LAI, dynamic process of above-ground biomass and yield of maize in Northeast China. This research supports the model application in Northeast China, such as simulating maize potential yield, or prescribing yield limiting factors.

Influence of Post Emergence Application of Glyphosate on Weed Control Efficiency and Yield of Transgenic Maize

Field experiment was conducted during kharif 2009 and rabi 2009-2010 at Tamil Nadu Agricultural University, Coimbatore to evaluate the weed control efficiency and yield potential of glyphosate resistant transgenic maize. Treatments consisted of two transgenic maize hybrids named Hishell and 900 M gold with application of glyphosate as post emergence at 900, 1800 and 3600 g a.e/hathese were compared with non-transgenic counterpart maize hybrids with application of atrazine as pre-emergence at 0.5 kg/ha followed by one hand weeding at 40 Days After Sowing along with need based insect control practices. Post emergence application of glyphosate at 900, 1800 and 3600 g a.e/ha in transgenic maize hybrids was recorded with lower weed density and higher weed control efficiency compared to other treatments. Higher grain yield was recorded with post emergence application of glyphosate at 1800 g a.e/ha in transgenic hybrid 900 M Gold and 3600 g a.e/ha in transgenic hybrid Hishell during kharif 2009 and rabi 2009-2010 seasons, respectively.

The effect of water supply and crop year on the yield potential of sweet maize (Zea mays L. convar. saccharata Koern.) hybrids with different genotypes

The successfulness of crop production is significantly affected by not only the the average yields that provide cost effectiveness, but also the success of striving for yield safety, therefore, varieties and hybrids tolerant to environmental stress factors are worth being included into the sowing structure. Our aim was to further the decision making of producers in prepaering the right sowing structure by the evaluation of sweet maize hybrids’ tolerance to excess rainfall.We performed our examinations in an extremely wet year (2010) on chernozem soil on three sweet maize hybrids (GSS 8529, GSS 1477, Overland) in 12 replications. Comparing the yields of 2010 with those that can be expected under optimal rainfall conditions, we showed that the examined hybrids react to the amount of rainfall higher than their needs with yield depression. The excess rainfall tolerance of the examined hybrids is different in the case of each hybrid.

Modern maize hybrids in Northeast China exhibit increased yield potential and resource use efficiency despite adverse climate change

The impact of global changes on food security is of serious concern. Breeding novel crop cultivars adaptable to climate change is one potential solution, but this approach requires an understanding of complex adaptive traits for climate-change conditions. In this study, plant growth, nitrogen (N) uptake, and yield in relation to climatic resource use efficiency of nine representative maize cultivars released between 1973 and 2000 in China were investigated in a 2-year field experiment under three N applications. The Hybrid-Maize model was used to simulate maize yield potential in the period from 1973 to 2011. During the past four decades, the total thermal time (growing degree days) increased whereas the total precipitation and sunshine hours decreased. This climate change led to a reduction of maize potential yield by an average of 12.9% across different hybrids. However, the potential yield of individual hybrids increased by 118.5kgha(-1) yr(-1) with increasing year of release. From 1973 to 2000, the use efficiency of sunshine hours, thermal time, and precipitation resources increased by 37%, 40%, and 41%, respectively. The late developed hybrids showed less reduction in yield potential in current climate conditions than old cultivars, indicating some adaptation to new conditions. Since the mid-1990s, however, the yield impact of climate change exhibited little change, and even a slight worsening for new cultivars. Modern breeding increased ear fertility and grain-filling rate, and delayed leaf senescence without modification in net photosynthetic rate. The trade-off associated with delayed leaf senescence was decreased grain N concentration rather than increased plant N uptake, therefore N agronomic efficiency increased simultaneously. It is concluded that modern maize hybrids tolerate the climatic changes mainly by constitutively optimizing plant productivity. Maize breeding programs in the future should pay more attention to cope with the limiting climate factors specifically.

Potential maize yield realization and related driving factors in four typical soils

土壤条件是否或在多大程度上限制了我国玉米产量潜力的实现是亟需回答的科学问题。本文选择我国4个玉米主产区的典型土壤(黑龙江黑土、陕西黑垆土、河南潮土和四川紫色土)进行了实证研究。结果表明: 不同土壤条件下玉米产量潜力的实现程度不同, 黑龙江852农场、陕西长武、河南温县与四川简阳4个试验点在设定的高产栽培管理条件下获得的产量分别为10.7 t·hm^-2、14.1 t·hm^-2、9.2 t·hm^-2与6.7 t·hm ^-2, 分别实现了当年光温水条件下该栽培体系产量潜力的92%、104%、84%与78%。相关分析表明, 土壤容重与产量潜力实现程度呈显著负相关, 根干重密度与产量潜力实现程度呈显著正相关。土壤物理(容重)与肥力(有机质含量)条件对玉米根系的生长和产量潜力的实现有显著影响。对土壤容重和有机质含量分析表明, 黑龙江852农场黑土土壤容重适中, 土壤有机质含量高, 耕层有机质为69.3 g·kg^-1, 陕西长武黑垆土土壤容重最小, 耕层容重为1.15 g·cm^-3, 土壤质地为壤质土, 两地的土壤条件有利于根系生长, 玉米根量较大, 0~40 cm横向分布广泛, 有利于产量潜力的实现, 分别实现92%和104%产量潜力; 河南温县潮土10 cm以下土壤容重大, 尤其10~20 cm的犁底层容重最大为1.53 g·cm^-3, 土壤有机质含量较低, 四川简阳紫色土土壤有机质含量较低, 整个土体容重较高, 并且土壤黏重, 两地的土壤性状不利于根系生长, 分别实现了产量潜力的84%和78%。因此, 应根据各主产区的土壤状况进行针对性的土壤改良与培肥, 为实现玉米产量潜力与大面积均衡增产奠定基础。

Potential maize yield realization and related driving factors in four typical soils

土壤条件是否或在多大程度上限制了我国玉米产量潜力的实现是亟需回答的科学问题。本文选择我国4个玉米主产区的典型土壤(黑龙江黑土、陕西黑垆土、河南潮土和四川紫色土)进行了实证研究。结果表明: 不同土壤条件下玉米产量潜力的实现程度不同, 黑龙江852农场、陕西长武、河南温县与四川简阳4个试验点在设定的高产栽培管理条件下获得的产量分别为10.7 t·hm^-2、14.1 t·hm^-2、9.2 t·hm^-2与6.7 t·hm ^-2, 分别实现了当年光温水条件下该栽培体系产量潜力的92%、104%、84%与78%。相关分析表明, 土壤容重与产量潜力实现程度呈显著负相关, 根干重密度与产量潜力实现程度呈显著正相关。土壤物理(容重)与肥力(有机质含量)条件对玉米根系的生长和产量潜力的实现有显著影响。对土壤容重和有机质含量分析表明, 黑龙江852农场黑土土壤容重适中, 土壤有机质含量高, 耕层有机质为69.3 g·kg^-1, 陕西长武黑垆土土壤容重最小, 耕层容重为1.15 g·cm^-3, 土壤质地为壤质土, 两地的土壤条件有利于根系生长, 玉米根量较大, 0~40 cm横向分布广泛, 有利于产量潜力的实现, 分别实现92%和104%产量潜力; 河南温县潮土10 cm以下土壤容重大, 尤其10~20 cm的犁底层容重最大为1.53 g·cm^-3, 土壤有机质含量较低, 四川简阳紫色土土壤有机质含量较低, 整个土体容重较高, 并且土壤黏重, 两地的土壤性状不利于根系生长, 分别实现了产量潜力的84%和78%。因此, 应根据各主产区的土壤状况进行针对性的土壤改良与培肥, 为实现玉米产量潜力与大面积均衡增产奠定基础。

Understanding production potentials and yield gaps in intensive maize production in China

Understanding yield potentials and exploitable gaps in current intensive maize (Zea mays L.) production is essential in order to increase grain yields to meet future food requirements amid strong competition for limited resources. In this study, we used simulations with the Hybrid-Maize Model (http://www.hybridmaize.unl.edu/), highest recorded yields published in the literature, field experiments, and farm survey data to assess yield potentials and gaps in four maize agro-ecological regions of China. In 50 simulations of high-yield sites across China from 1990 to 2009, the yield potential averaged 16.5Mgha−1 for irrigated maize and 13.9Mgha−1 for rainfed maize, respectively. During the same period, the highest recorded yield was 15.4Mgha−1, or 93% of the yield potential of irrigated maize. In comparison, the average farmer's yield was 7.9Mgha−1 based on 5584 farms surveyed in 2007–2008. Consequently, the yield gap between the average farmer's yield and the modeled yield potential (YGM) was 8.6Mgha−1 for irrigated maize and 6.0Mgha−1 for rainfed maize and so farmers attained 48–56% of the yield potential. The yield gap between the average farmer's yield and highest recorded yield (YGR) was 7.6Mgha−1, so farmers attained 51% of the recorded yield. Because the sites used for simulated and recorded yields possessed the most favorable combinations of soil and crop management, closing the gaps in YGM and YGR in farmers’ fields within a short time frame could be very difficult. The attainable yield was collected from field experiments, which were conducted in farmers’ fields by farmers using recommended management practices by local agronomists. The data for attainable yield averaged 12.3Mgha−1 according 137 field experiments across China. The yield gap between the average farmer's yield and the experimental yield (YGE) was 4.5Mgha−1, with farmers attaining 64% of the experimental yield. The main factor explaining this gap was inefficient crop management practices, which constrained yield improvements in farmers’ fields. In order to narrow this gap, multidisciplinary understanding and cooperation among the disciplines of plant science, agronomy, soil science, agro-ecology and extension, resulting in integrated soil–crop system management, are essential.

Why Early Season Weed Control Is Important in Maize

Control of early-emerging weeds is essential to protect the yield potential of maize. An understanding of the physiological changes that occur as a result of weed interference is required to address variability in yield loss across sites and years. Field trials were conducted at the University of Guelph (UG), the Ohio State University (OSU), and Colorado State University (CSU) during 2009 and 2010. There were six treatments (season-long weedy and weed-free, and weed control at the 1st-, 3rd-, 5th-, and 10th-leaf-tip stages of maize development) and 20 individual plants per plot were harvested at maturity. We hypothesized that, as weed control was delayed, weed interference in the early stages of maize development would increase plant-to-plant variability in plant dry-matter accumulation, which would result in a reduction of grain yield at maturity. The onset of the critical period for weed control (CPWC) occurred on average between the third and fifth leaf tip stages of development (i.e., V1 to V3, respectively). Rate of yield loss following the onset of the CPWC ranged from 0.05 MG ha−1d−1at UG 2009 to 0.22 MG ha−1d−1at CSU 2010 (i.e., 0.5 and 1.6% d−1, respectively). On average, reductions in kernel number per plant accounted for approximately 65% of the decline in grain yield as weed control was delayed. Biomass partitioning to the grain was stable through early weed removal treatments, increased and peaked at the 10th-leaf-tip time of control, and decreased in the season-long weedy treatment. Plant-to-plant variability in dry matter at maturity and incidence of bareness increased as weed control was delayed. As weed control was delayed, the contribution of plant-to-plant variability at maturity to the overall yield loss was small, relative to the decline of mean plant dry matter.

Maize potential yields and yield gaps in the changing climate of northeast China

AbstractNortheast China (NEC) is not only one of the major agricultural production areas in China, but it is also the most susceptible to climate variability. This led us to investigate the impact of climate change on maize potential yield and yield gaps in this region, where maize accounts for about 30% of the nation's production. The APSIM‐Maize model was calibrated and validated for maize phenology and yields. The validated model was then used to estimate potential yields, rain‐fed potential yields, and yield gaps for assessing the climate impacts on maize productivity in NEC. During maize growing seasons from 1981 to 2010, the analysis indicates a warming trend all across NEC, whereas the trends in solar radiation and total precipitation tended to decrease. When the same hybrid was specified in APSIM for all years, a simulated increase of maximum temperature resulted in a negative impact on both potential yield and rain‐fed potential yield. A simulated increase in minimum temperature produced no significant changes in potential or rain‐fed potential yield. However, the increase of minimum temperature was shown to result in a positive impact on the on‐farm yield, consistent with our finding that farmers adopted longer season hybrids for which the increase in minimum temperature provided better conditions for germination, emergence, and grain filling during night time. The gap between potential and rain‐fed potential yields was shown to be larger at locations with lower seasonal precipitation (<500 mm). Our results indicate that regions with the largest yield gaps between rain‐fed potential and on‐farm yields were located in the southeast of NEC. Within NEC, on‐farm maize yields were, on average, only 51% of the potential yields, indicating a large exploitable yield gap, which provides an opportunity to significantly increase production by effective irrigation, fertilization, herbicide, and planting density in NEC.

Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent.

Genetic analysis of grain yield and other traits of extra-early yellow maize inbreds and hybrid performance under contrasting environments

Maize (Zea mays L.) is a major staple crop in West and Central Africa (WCA) but production is constrained by Striga hermonthica parasitism and recurrent drought in the savannas where maize yield potential is highest. Two studies were conducted for 2 years at 5 locations in Nigeria. The objective was to determine the combining ability of seven extra-early yellow-endosperm inbreds, place them into heterotic groups, identify the best testers and superior single-cross hybrids under drought, Striga infestation, optimal conditions and across environments. General combining ability (GCA) and specific combining ability (SCA) mean squares were significant for grain yield and most other traits across test environments. Mean squares for GCA were larger than those of SCA in all environments, indicating that additive gene action was more important in the inheritance of traits. Three testers (TZEEI 79, TZEEI 76 and TZEEI 63) and opposing heterotic groups (TZEEI 95, TZEEI 78, TZEEI 79), (TZEEI76, TZEEI 82) and (TZEEI 63, TZEEI 58) were identified across environments. TZEEI 79 had the highest positive GCA effects for grain yield across environments. Furthermore, TZEEI 95×TZEEI 79 was identified as the potential single-cross tester for the development of three-way and double-cross hybrids. Results of repeatability analysis showed that the managed drought test site, IKDT, was the most repeatable even though it was not very discriminating. In contrast, ZAWW had high representativeness, discriminating ability and repeatability, indicating that it was the ideal test location. The best extra-early hybrid TZEEI 79×TZEEI 63 under drought stress and TZEEI 82×TZEEI 79 under Striga infestation were comparable in yield to the best open-pollinated early check. GGE biplot analysis revealed TZEEI 79×TZEEI 76 as the highest yielding and most stable hybrid across environments. The available extra-early maize inbred lines are not only drought escaping but also possess genes for drought tolerance.

Planting Geometry and Plant Population Affect Dryland Maize Grain Yield and Harvest Index

Water for dryland grain production in the Texas panhandle is limited. Agronomic practices such as reduction in plant population or change in sowing time may help increase maize (Zea mays L.) yield potential. Tiller formation under dryland conditions leads to more vegetative growth and reduced yield. We hypothesized that clump planting dryland maize would reduce environmental stress, tillering, and vegetative growth, and increase harvest index by having more soil water available during grain filling. Clump planting was studied during 2008 at Bushland, Texas. Two plant populations—30,000 and 40,000 plants ha−1—and three plant geometries—clumps of three or four plants (3 PPC or 4 PPC) and equally spaced single plants (ESP)—were grown in 75 cm rows. Growing season precipitation was 209 mm. Harvest index (HI) 200-seed mass and harvested ears were higher in 3 PPC and 4 PPC compared with ESP. Three PPC planted at 40,000 plants ha−1 had the highest harvest index of 0.46. The ESP produced 27% more unproductive ears compared with 3 PPC and 4 PPC. Leaf area index (LAI) was 14% more in ESP than in 4 PPC. The lower population produced higher HI and seed mass than the higher population, regardless of geometry. Grain yields were not significantly higher for clumps, yet increased number of productive ears, seed mass, and HI values, suggesting clump geometry may be a good strategy for dryland maize production.

Near-Infrared Reflectance Spectroscopy (NIRS) Assessment of δ18O and Nitrogen and Ash Contents for Improved Yield Potential and Drought Adaptation in Maize

The oxygen isotope composition (δ(18)O), accumulation of minerals (ash content), and nitrogen (N) content in plant tissues have been recently proposed as useful integrative physiological criteria associated with yield potential and drought resistance in maize. This study tested the ability of near-infrared reflectance spectroscopy (NIRS) to predict δ(18)O and ash and N contents in leaves and mature kernels of maize. The δ(18)O and ash and N contents were determined in leaf and kernel samples from a set of 15 inbreds and 18 hybrids grown in Mexico under full irrigation and two levels of drought stress. Calibration models between NIRS spectra and the measured variables were developed using modified partial least-squares regressions. Global models (which included inbred lines and hybrids) accurately predicted ash and N contents, whereas prediction of δ(18)O showed lower results. Moreover, in hybrids, NIRS clearly reflected genotypic differences in leaf and kernel ash and N contents within each water treatment. It was concluded that NIRS can be used as a rapid, cost-effective, and accurate method for predicting ash and N contents and as a method for screening δ(18)O in maize with promising applications in crop management and maize breeding programs for improved water and nitrogen use efficiency and grain quality.

Rice-maize systems of South Asia: current status, future prospects and research priorities for nutrient management

Rice (Oryza sativa L.) and maize (Zey mays) are grown in 3.5 million hectares (Mha) in Asia that includes 1.5 Mha in South Asia. These crops are grown in sequence on the same land in the same year either in double–or triple-crop systems to meet the rice demand of a rapidly expanding human population and maize demand of livestock and poultry. The objective of this review is to provide a comprehensive overview of the current state of technical knowledge on agro-ecosystems and adaptation, area and distribution, yield potential and yield gaps, and nutrient management for rice-maize (R-M) systems in South Asia. Rice-maize systems are emerging all around South Asia but in particular are developing quite rapidly in Bangladesh and South and North India. Yield potential of rice and maize, as estimated by ORYZA2000 and Hybrid Maize models, reaches up to 15 and 22 t ha-1, respectively. However, data from several environments in India reveal gaps between potential and attainable yields of maize of upto 100% and between attainable and actual yields of upto 25–50%. Nutrient demand of R-M system is high due to high nutrient removal by high-yielding maize. Nutrient balance studies for these highly–productive and nutrient-extractive systems are scarce in South Asia. The review outlines principles of nutrient management for R-M systems, and identifies development, refinement, and dissemination of the integrated plant nutrition system technologies based on site-specific nutrient management principles as priorities for future research to increase yield, profitability, and sustainability of R-M systems.

Trait dissection of maize kernel weight: Towards integrating hierarchical scales using a plant growth approach

Maize (Zea mays L.) yield is a function of the number harvested kernels per unit land area and the individual kernel weight (KW). Kernel weight and its development show a wide variability due to the genotype, the environment, the crop management, and all possible interactions. Commercial maize hybrids differ markedly in the patterns (rate and duration of kernel growth) behind differences in final KW. The same can be observed when public or elite proprietary maize inbred lines are analyzed. To progress in our understanding of KW variability, we reviewed and discussed current knowledge for analyzing kernel growth as an integrated system, modulated by processes linking different levels of organization (the different kernel tissues, the whole kernel, the plant, the canopy). Ideas on how to integrate this knowledge towards the development of a multi-hierarchical scale framework for predicting KW under different growth environments are currently needed, as they have high relevance for dissecting the genetic basis of kernel growth and maize yield definition at the canopy level. At the kernel and tissue level, we highlight the need of focusing and studying traits like assimilate movement into developing kernels, endosperm cell division, endosperm cell death, kernel internal homeostasis and kernel water relations. These specific processes need to be connected affecting the rate or duration of grain filling at the whole kernel level for studying kernel size variability. At the plant and canopy levels, the dynamic response of both kernel number and potential KW to plant growth around flowering appears critical for understanding KW variations, as maize final KW is highly associated with the potential KW determined during the first stages of grain filling. Focusing on the period around flowering in this species is important for yield improvement through both yield components, kernel number and size. At present it seems that maize potential yield can only be improved by modifying the sink capacity established at the end of the lag phase and increasing the source strength during grain filling so as to fulfill this potential.

Evaluation of NASA Satellite‐ and Model‐Derived Weather Data for Simulation of Maize Yield Potential in China

Use of crop models is frequently constrained by lack of the required weather data. This paper evaluates satellite‐based solar radiation and model‐derived air temperature (maximum temperature, Tmax; minimum temperature, Tmin) from NASA and their utility for simulating maize (Zea mays L.) yield potential at 39 locations in China's major maize‐producing regions. The reference data in this evaluation were the corresponding ground‐observed weather data and simulated yield using these data. NASA weather data were closely correlated with data from ground weather stations with an r2 > 0.8, but a systematic underestimation of air temperature was found (Tmax of −2.8°C; Tmin of −1.4°C). As a result, use of NASA data alone for yield simulation gave poor agreement with simulated yields using ground weather data (r2 = 0.2). The simulations of yield potential using satellite‐derived solar radiation, coupled with temperature data from ground stations, agreed well with simulated results using complete ground weather data in three of the five regions (r2 > 0.9). The agreement in the other two regions was relatively poor (r2 = 0.62 and 0.64). Across all 710 site‐years evaluated, the agreement was shown with a mean error (ME) = 0.2 t ha−1, a root mean square error (RMSE) = 0.6 t ha−1, and r2 = 0.9. Our results indicate that combining NASA solar radiation with ground‐station temperature data provides an option for filling geospatial gaps in weather data for estimating maize yield potential in China.

Potential productivity and water requirements of maize–peanut rotations in Australian semi-arid tropical environments—A crop simulation study

The growing demand for maize (Zea mays L.) in intensive livestock and other industries has opened up fresh opportunities for further expansion of the maize industry in Australia, which could be targeted in relatively water rich semi-arid tropical (SAT) regions of the country. This crop simulation study assessed the potential productivity and water requirements of maize peanut (Arachis hypogaea L.) rotations for the SAT climatic zone of Australia using the Agricultural Production Systems Simulator (APSIM) model. APSIM was configured to simulate maize (Pioneer hybrid 3153) either in the dry (May�October) or wet season (November�April) and peanut (cv. Conder) in the following season for three soils found at Katherine (14.48°S, 132.25°E) from 1957 to 2008. The simulated mean total yield potential of the dry season maize and wet season peanut (DMWP) rotation (15�19.2 t/ha) was about 28% greater than the wet season maize�dry season peanut (WMDP) rotation because of the higher yield potential of maize in the dry season compared to in the wet season. These high yields in the DMWP rotation have been achieved commercially. The overall simulated irrigation water requirement for both rotations, which varied from 11.5 to 13.8 ML/ha on different soils, was similar. The DMWP rotation had 21% higher water use efficiency. Similar yield and water use efficiency advantages of the DMWP rotation were apparent for eight other agriculturally important locations in the Northern Territory, Western Australia and Queensland. The simulations for Katherine also suggested that the irrigation requirement of the two rotations could increase by 17.5% in El-Nino years compared to La-Nina years for only a small gain in yield, which has implications for climate change scenarios