No abstract

Development of new peanut (Arachis hypogaea L.) cultivars over the past 40 years has more than doubled yield potential. The purpose of this paper is to identify and evaluate the physiological changes made in the course of this varietal improvement that are responsible for the great increase in yield potential. Weekly harvests of large samples of four Florida cultivars, a Spanish peanut type, and one soybean (Glycine max (L.) Merr.) cultlvar gave the information needed to show the progressive changes in dry weights of all plant parts throughout the growing season. Other weekly samplings and observations gave numbers of pegs, flowers, and fruits as well as fruit weights, root length, shoot length, and leaf areas. Quantitative estimates of the physiologlcal factors responsible for the dry weight differences were made by computer simulation using the PENUTZ model. Differences in three physiological processes explain most of the yield variation among the five peanut cultivars; the partitioning of assimilate between vegetative and reproductive parts, the length of the filling period, and the rate of fruit establishment. Of these, the partitioning of assimilate had the greatest effect on fruit yield. Estimates of partitioning to fruit ranged from 41% in the first cultivar released to 98% in the most recently released cultivar. Crop growth rates did not differ significantly among peanut cultivars but all were much higher than the crop growth rate of soybeans.

For leaf area indices (LAI) of less than approximately 3.0, differences in leaf angle are predicted by computer simulation to have only small effects on canopy photosynthetic rates. For higher LAI values, layers of vertical and horizontal leaves can be arranged to give both the highest and lowest possible rates of canopy photosynthesis for the conditious assumed. These arrangements of leaf layers and angles are not much affected by leaf type or latitude within usual limits.The ratio of highest to lowest photosynthetic rate varied from 1.14 at LAI 3.0 to 2.0 at LAI 10.0. Calculations with one set of corn (Zea mays L.) descriptions indicate that canopy photosynthetic rates may range from 92% of theoretical maximum at LAI 3.0 to 76% at LAI 7.0.

At maturity a black closing layer develops in the placental region of corn (Zea mays L.). The suitability of this black layer as an indicator of physiological maturity was studied in four hybrids of a range in maturity. As viewed by the naked eye the layer developed in 3 days or less, and its appearance coincided with the achievement of maximum kernel dry weight. An examination of a wide range of genotypes indicated that the black‐layer formation is a common feature of commercial hybrids at maturity.An investigation of incompletely developed florets on partially barren ears or in the tip region of normal ears revealed black‐layer formation in those showing limited endosperm development. No black‐layer development was seen in nonfertilized or parthenocarpic florets.The cause and mechanisms of black‐layer formation are unknown. However, it is speculated that such development is related to assimilate movement into the developing floret.

No satisfactory explanation for the effect of planting patterns on soybean [Glyclne max (L.) Merr.] seed yields under favorable growing conditions has been proposed. The purpose of this paper is to suggest two postulates that together explain soybean yield response to various planting patterns. They are: (1) seed yields continue increase with plant density to a limit that is well above that needed for almost complete light interception, and (2) yield is directly related to vegetative plant weight, all other conditions remaining the same. To illustrate the application of the first postulate, interplant competition is divided into three parts: Phase I in which there is no interplant competition for light among fully developed plants, Phase II in which canopy light interception is complete while seed yield increases with plant density, and Phase III in which yield per unit area is at a maximum for the planting patterns and is independent of plant density. The second postulate explains whyields per unit area differ with row width even when there is no difference in either plant density or canopy light interception. The validity of the postulates is tested using published data. No proof is offered for the postulates other than that they explain the data and seem physiologically possible.

Twenty‐two races of maize (Zea mays L.) and one selection of teosinte (Euchlaena mexicana Schrad) were grown under natural daylight in eight glasshouses where day/night temperatures were maintained from 15/10 to 36/31 C. Differences were found among temperatures and races in net photosynthetic rates, relative leaf growth rates, and leaf numbers. At low temperatures, high altitude races had relatively higher leaf growth rates and dry weights at harvest. At high temperatures high altitude races had relatively lower net photosynthetic rates. Leaf numbers increased with increasing temperatures.

A Significant linear relationship was found among several corn (Zea mays L.) hybrids grown in 1966 and 1967 at Guelph, Ontario at several planting densities, between grain yield and effective filling period duration. Effective filling period duration (EFPD) is defined as final grain yield divided by the average rate of grain dry weight accumulation during the linear period of grain formation, and hence, is a relative measure of the length of the grain filling period. In each year yield differences among hybrids were more closely related to EFPD differences than to differences in the rate of ear dry weight accumulation. EFPD was unaffected by planting density. Results suggest that significant potential exists in corn for higher grain yields through a genetic extension of the length of the grain filling period.

Synopsis The logarithm of the average yield of individual corn plants making up a population bears a linear relationship to the population. Therefore, only two yield‐population values are needed to estimate yields at any other population within the linear range. Equations are given for estimating maximum yield and maximum‐yield population.