Kernel Number Determination in Maize

Environmental conditions affect grain yield in maize (Zea mays L.) mainly by altering the kernel number per plant (KNP). This number is determined during a critical period of about 2 weeks around silking. The objectives of this study were to assess how the rate and timing of nitrogen (N) fertilizer applications affect biomass partitioning and KNP in two genotypes with different N use efficiency, and to compare kernel set of these genotypes under varying regimes of carbohydrate and N availability during the critical period for kernel set. In the first field experiment, plant density and the rate of N supply per plant were varied independently. In the second field experiment, N availability was controlled via the application of N fertilizer, and carbohydrate availability was controlled by shading or thinning at silking. In both experiments, low rates of N supply reduced KNP more strongly in the non-efficient genotype when compared to the efficient genotype. The genotypic differences in kernel set were neither associated with N uptake into the above-ground biomass at maturity, nor above-ground biomass at silking. In the non-efficient genotype, application of N fertilizer at silking increased KNP. This increase was not associated with an increase in plant growth but with increased partitioning of biomass towards the reproductive organs during the critical period for kernel set. The genotype which had been selected for its high N use efficiency also showed higher kernel set at high plant density and shading during flowering when compared to the non-efficient genotype. Under conditions of restricted resource availability per plant, plant and ear growth rates during the critical period of about 14 days after onset of flowering declined compared with non-limiting conditions. However, these growth rates were less reduced in the efficient genotype. Pooling treatments of different plant density and different available N, each hybrid showed linear responses of KNP to plant growth rate and to ear growth rate. Furthermore, in the efficient genotype KNP was reduced to a lesser extent in response to decreasing growth rates. We conclude that higher kernel set of the efficient genotype compared to the non-efficient genotype under stressful conditions was associated with low sensitivity of plant growth and dry matter distribution towards reproductive organs to low assimilate availability during the critical period of kernel set, and particularly with low sensitivity of kernel set to decreasing plant and ear growth rates.

Core Ideas The dynamics of kernel set in maize was modeled at the individual kernel level.Kernels survived when enough assimilate was available to meet their needs.The model captures the dynamics of ear size, plant growth rate, and kernel growth. The adjustment of kernels plant−1 to the assimilate supply is an important component of the yield production process in maize (Zea mays L.). A simulation model (KNMAIZE) was developed to better understand this process at the individual kernel level. Kernel survival was determined by comparing the assimilate supply (calculated from solar radiation) partitioned to reproductive growth during the initial stages of kernel development with the kernel assimilate requirement (based on published kernel growth curves) on a daily basis. When model parameters were optimized by maintaining the ratio of the sink (total kernel growth rate) and the source (total assimilate supply) equal to 1.0 during the linear phase of kernel growth, the model accurately mimicked the effect of plant growth rate, individual kernel growth rate, and ear size on kernels plant−1. The model also mimicked the plant density‐kernels m−2 relationship. Short‐term (3 or 5 d) variation in plant growth rate influenced kernels plant−1 11 to 15 d after the beginning of kernel growth. Modeling kernel number at the individual kernel level makes it possible to capture important aspects of the dynamics of kernel set that will lead to better predictions of kernel number and a clearer understanding of the elements of maize productivity in the field.

Inter-plant variability in maize crops grown under contrasting N × stand density combinations: Links between development, growth and kernel set

Kernel weight and its response to source manipulations during grain filling in Argentinean maize hybrids released in different decades

Intra-specific competition in maize: Ear development, flowering dynamics and kernel set of early-established plant hierarchies

Critical period for seed number determination in soybean as determined by crop growth rate, duration, and dry matter accumulation

The study aimed to determine the response of growth and yield of kailan on the interaction effect of a dolomite lime with bokashi of cow manure and its single factor effect. The experiment was conducted in Completely Randomized Design (CRD) with two factors in three replications. The first factor was dolomite lime which consists of 2 t ha-1 (k1), 5 t ha-1 (k2), 10 t ha-1 (k3) and 15 t ha-1 (k4), while the second factor was bokashi of cow manure consisting of 0 t ha-1 (b0), 10 t ha-1 (b1), 15 t ha-1 (b2), and 20 t ha-1 (b3). By observing growth components consisting of relatif growth rate (RGR), crop growth rate (CGR), net assimilation rate (NAR), shoot/root ratio (S/R), and crop yield. As well as the components of soil nutrient content of N, P, K, C-organic content, pH and cation exchange capacity (CEC). The results showed that the application of dolomite lime at a dose of 15 t ha-1 with bokashi fertilizer at a dose of 20 t ha-1 give the highest value of crop growth rate (CGR), net assimilation rate (NAR), shoot/root ratio (S/R), C-organic content, phosphorus (P), and Potassium in peat soil. The application of bokashi fertilizer at a dose of 15 t ha-1 was not different with 20 t ha-1 in terms of relatif growth rate (RGR), crop yield and cation exchange capacity (CEC), and respectively higher than the dose of 10 t ha-1 and without bokashi fertilizer. The application of dolomite lime at a dose of 10 t ha-1 was not different with 15 t ha-1 on the relative growth rate (RGR), and pH of peat soil, and each dose was higher than the doses of 5 t ha-1 and 2 t ha-1 . In terms of nitrogen (N) content, the application of dolomite lime at a dose of 5 t ha-1 was not different with the dose of 10 t ha-1 , and 15 t ha-1 , the N content was higher than the dose of 2 t ha-1 . The increase in the dose of dolomite lime at 20 t ha-1 of bokashi fertilizer showed a positive linier correlation, except for the Potassium which showed a quadratic correlation. The increase dose of dolomite lime in the bokashi fertilizer, the plant growth rate (PAR), net assimilation rate (NAR), shoot/root ratio (S/R), C-organic content, and phosphorus (P) would increase as well. Each single factor of the dose of dolomite lime and bokashi fertilizer showed a positive linier relationship to the relatif growth rate (RGR), crop yield, N-total, pH, and cation exchange capacity (CEC) of peat soil, except for N-total and pH in bokashi fertilizer.

Genetic improvement in maize (Zea mays L.) grain yield is associated with improvements in dry matter accumulation during the grain‐filling period and the ability to maintain partitioning to the grain (i.e., harvest index) when grown at higher plant population densities. Although several attributes have been identified that lead to improved dry matter accumulation during the grain‐filling period, the attributes that have enabled the maintenance of harvest index at higher plant population densities remain elusive. Using the Ontario ERA hybrids that represent five eras of genetic improvement in Ontario, we examined genetic improvement in several attributes associated with sink establishment and partitioning to the grain. We show that the number of florets on an ear initial is not influenced by plant density, nor is there any evidence of a genetic improvement in floret number. There has been genetic improvement, however, in the ability to support kernel set at a lower threshold level of dry matter accumulation and to more efficiently set kernels at lower dry matter accumulation levels, such as those experienced at higher plant densities. Genetic improvement is evident for reduced plant‐to‐plant variability for dry matter accumulation, grain yield, kernel number, and plant growth rate around silking, but most notably for grain yield. Finally, we show that genetic improvement in reduced plant‐to‐plant variability for grain yield is the result of the lower threshold dry matter levels required for seed set and the improved resource utilization, which has led to greater stability of individual plant performance in a stand.

In the last years globally, daily night‐time low temperatures have increased more than twice compared with maximum temperatures. There is little evidence about maize growth and yield responses to high night temperature (HNT) under field conditions. In this study, we aimed to (i) evaluate the effect of HNT during post‐flowering on kernel number (KN), crop growth rate expressed in chronological days and thermal units (CGRDand CGRTU, respectively), radiation use efficiency (RUE), night respiration (Rn), net photosynthesis (Amax), chlorophyll fluorescence and cell membrane stability (CMS), and (ii) identify associations among the measured physiological traits. Two hybrids (Te, temperate; and St, subtropical) were exposed to two thermal conditions from R1 + 2d to R1 + 16d: (i) HNT from 1900 to 0700 h, and (ii) ambient night temperature (ANT). The HNT resulted in reductions in KN (8%), CGRD(11%), and CGRTU(19%), with non‐significant changes in kernel weight and grain yield. Reductions in KN were better explained by drops in CGRTUthan in CGRD. Under HNT, Amax significantly decreased (p < 0.05; 17%, among experiments and hybrids) with insignificant changes in CMS and chlorophyll fluorescence. HNT caused a larger effect on Rn in Te (+40%) than in St. We found a strong negative relationship between Rn and Amax, indicating that high Rn might exhibit an indirect effect on Amax, altering carbon balance and growth.

Context Sulfur deficiency is a limiting factor of cereal crops, causing significant crop losses associated with a decrease in the number of grains. In barley (Hordeum vulgare L.) crops, grain number (and grain yield) is associated with spike biomass at anthesis, which is related to crop growth rate during the period preceding anthesis (i.e. the ‘critical period’) when spike growth occurs. These relationships have been established for various cultivars under varying radiation intensity and in different locations, and have been confirmed in crops grown under nitrogen and phosphorus deficiencies. Aims The objective of this study was to determine, for malting barley, whether the effects of sulfur, nitrogen and their interaction on the number of grains per unit area could be explained by changes in crop growth rate or photothermal quotient (ratio of intercepted photosynthetically active radiation to temperature) during the critical period. Methods Three field experiments were conducted in the Pampean region of Argentina to evaluate the effects of sulfur fertilisation under three levels of nitrogen availability on the number of grains per unit area. Key results Changes in grain number were associated with crop growth rate or photothermal quotient during the critical period. This association was maintained when sulfur fertilisation changed grain number. Crop growth rate during the critical period varied mainly as a result of changes in accumulated intercepted radiation. Conclusions Sulfur fertilisation increases grain number and grain yield by increasing radiation interception during the critical period, probably as a consequence of increased leaf area. Implications The determination of grain number under sulfur deficiency is similar to that observed under deficiencies of other nutrients.

Field studies with the spring wheat (Triticum aestivum L.) cultivars ‘Era’ and ‘OlaF’ were conducted to assess the effects of reductions in kernel number per spike and defoliation of individual culms on kernel growth characteristics. The importance of stage of kernel growth at which treatments were applied was also examined by treating both at anthesis and anthesis + 14 days, the later date being after the beginning of the kernels linear dry matter accumulation period.The effects of the treatments on final weight per kernel depended on the time of treatment and on the relative weights of kernels from the untreated (control) culms. Reduction in kernel number per spike increased final kernel weight, particularly when control weights were low, whereas defoliation always reduced final weight. Treatment at anthesis usually had a larger effect.Growth rates of kernels during the linear dry matter accumulation period were enhanced by kernel removal and depressed by defoliation. Within each genotype, growth rates were highly correlated with final kernel weight. This association, however, differed between years because of variation in length of the grain filling period. No consistent effect of the treatments on grain filling duration was found.The response to early kernel number reduction, as well as the response in additional experiments to spikelet “trimming” suggested that upper limits, or potentials, for both final weight and growth rate were approached. These potential kernel weights and growth rates appeared to depend on genotype, kernel position in a spikelet, and possibly environment.

Accurate prediction of kernel number per plant is critical for yield simulation in maize (Zea mays L.). Model predictions of kernel number generally are based on empirical relationships between final kernel number and carbohydrate supply or plant growth at silking, without regard to flowering dynamics. The objective of this study was to develop a model for predicting kernel set from seasonal dynamics of pollen shed and silk exsertion. Hybrids were planted in isolated plots at four ratios of male fertile (MF) and male sterile (MS) plants. Dynamics of pollen shed in each plot was described by a Gauss curve and by a population index (Pind) derived from the percentage of plants at beginning, maximum, and ending pollen shed. Percentage of plants at silking followed a sigmoid curve, whereas the number of silks exposed daily per ear followed a monomolecular model. Pollen shed and silk exsertion curves were translated to potential kernel set using a published relationship. Excellent agreement was observed between predicted and measured number of florets per hectare available for pollination. The model overpredicted kernel number per hectare at high pollen shed densities. Predicted kernels per hectare were within 5% of actual kernel numbers at low pollen shed densities when delayed development of subapical ears and asynchronous pollination within ears were considered. These results indicate kernel set in maize can be predicted from simple measures of the flowering process. They confirm that kernel set is limited primarily by factors other than pollen amount when all plants in the population are MF.

The Influence of the Length of the Growth Period and Planting Density on Total Crop Yield

A half diallel set of crosses among six inbred lines of maize were evaluated under two plant densities (23333 and 35000 plants/fad) for grain yield and its components and quality traits at Sherenkash Village, Talkha district, El-Dakahlia Governorate. Obtained results are as follows: 1- Highly significant variances due to general and specific combining ability for all studied yield and yield components and quality traits, except ears number per plant and protein percentage under both plant densities and oil percentage under normal plant density. 2- The GCA/SCA ratio was less one for all studied yield and yield components and quality traits under both plant densities, suggesting that non additive genetic action was more important than additive, except rows number per ear, kernels number per row and 100-kernel weight under stress plant density. 3- GCA effects showed that the lines R24, R25 and R39 were good general combiners for grain yield per plant under normal plant density. 4- SCA effects showed that the best F1 cross combinations were P1xP2, P1xP4, P1xP6, P2xP3, P3xP5 and P5xP6 for grain yield per plant. These crosses had highly significant estimates of SCA effects under normal plant density. 5- The highest value of heterotic effects relative to mid and better parents for grain yield per plant were obtained by P4xP5 followed by P5xP6. These crosses had the highest positive significant heterotic under both plant density.

Seed number, the main yield component of cereals and oil‐seed species, strongly depends on the physiological status of the crop during a critical period for seed set. Using a comparative approach including three species with contrasting reproductive strategies, we investigated the relationship between seed number per plant (SNP) and plant growth rate during the critical period for seed set (PGRC). Indeterminate soybean [Glycine max (L.) Merr.], sunflower (Helianthus annuus L.), and maize (Zea mays L.) crops were grown under a wide range of plant densities to generate contrasting availability of resources per plant. Growth of individual plants was estimated by a novel, nondestructive method based on relationships between actual shoot dry matter and morphometric variables, including stem diameter, plant height, and dimensions of reproductive structures. Seed number per plant ranged from 0 to 890 in soybean, 0 to 4096 in sunflower, and 0 to 1348 in maize and PGRC (g d−1) from 0.01 to 4.3 in soybean, 0.3 to 17.6 in sunflower, and 0.4 to 12.3 in maize. Our study showed that (i) the relationship between SNP and PGRC was linear in soybean, reflecting the reproductive plasticity of this species, and curvilinear in sunflower and maize, reflecting morphogenetic restrictions to generate reproductive sinks under favorable growing conditions; (ii) the PGRC threshold below which no seed was set varied among species, being negligible in soybean, close to 0.35 g d−1 in sunflower, and 1 g d−1 in maize. Quantitative relationships between seed number and plant growth rate during the critical period of seed set could be useful for crop modeling.