Wiley

The model, Y_ij = μ₁ + β₁I_j + δ_ij, defines stability parameters that may be used to describe the performance of a variety over a series of environments. Y_ij is the variety mean of the i^th variety at the j_th environment, µ₁ is the i^th variety mean over all environments, β₁ is the regression coefficient that measures the response of the i^th variety to varying environments, δ_ij is the deviation from regression of the i^th variety at the j^th environment, and I_j is the environmental index.

The data from two single‐cross diallels and a set of 3‐way crosses were examined to see whether genetic differences could be detected. Genetic differences among lines were indicated for the regression of the lines on the environmental index with no evidence of nonadditive gene action. The estimates of the squared deviations from regression for many hybrids were near zero, whereas extremely large estimates were obtained for other hybrids.

We developed stage of development descriptions which we believe apply to all soybean (Glycine max (L.) Merr.) genotypes grown in any environment. The descriptions apply to single plants or a community of plants and are precise and objective.

Vegetative and reproductive development are described separately. Vegetative stages are determined by counting the number of nodes on the main stem, beginning with the unifoliolate node, that have or have had a completely unrolled leaf. Reproductive stages Rl and R2 are based on flowering, R3 and R4 on pod development, R5 and R6 on seed development, and R7 and R8 on maturation.

The stage descriptions should enhance soybean research by standardizing descriptions of soybean plant development. The system also will be used by the soybean hail insurance industry for stage determination in adjustment of losses.

Critical issues in the use of diallel analysis are reviewed. From a statistical point of view the critical issue concerns the choice of a model with fixed or random genotypic effects. From a genetical point of view, two assumptions are critical in attempts to interpret the resuits of diallel analyses. The assumption concerning the independent distribution of genees in the parents is most critical to proper interpretation and seems to be least acceptable in actual practice. The second assumption, that there is no epistasis, may frequently be incorrect. Epistasis affects estimates of general and specific combining ability mean squares, variances, and effects in an unpredictable manner. As an alternative to genetic interpretation, the statistical description provided by dialiel analysis can be used to help answer questions concerning the importance of specific combining ability and the predictability of hybrid performance using general combining ability or parental performance.

One‐fifth of irrigated agriculture is adversely affected by soil salinity. Hence, developing salt‐tolerant crops is essential for sustaining food production. Progress in breeding for salt‐tolerant crops has been hampered by the lack of understanding of the molecular basis of salt tolerance and lack of availability of genes that confer salt tolerance. Genetic evidence suggests that perception of salt stress leads to a cytosolic calcium‐signal that activates the calcium sensor protein SOS3. SOS3 binds to and activates a ser/thr protein kinase SOS2. The activated SOS2 kinase regulates activities of SOS1, a plasma membrane Na⁺/H⁺ antiporter, and NHX1, a tonoplast Na⁺/H⁺ antiporter. This results in Na⁺ efflux and vacuolar compartmentation. A putative osmosensory histidine kinase (AtHK1)‐MAPK cascade probably regulates osmotic homeostasis and ROS scavenging. Osmotic stress and ABA (abscisic acid)‐mediated regulation of LEA (late‐embryogenesis‐abundant)‐type proteins also play important roles in plant salt tolerance. Genetic engineering of ion transporters and their regulators, and of the CBF (C‐repeat‐binding factor) regulons, holds promise for future development of salt‐tolerant crops.

A standardized, accurate, and easy system is needed to describe sunflower (Helianthus annuus L.) plant development. The objective of this study was to develop and describe stages of sunflower plant development in a manner which is simple but accurate.

Plants were divided into either Vegetative (V) or Reproductive (R) stages of plant development. Vegetative development is divided into two phases, emergence and true leaf development. The latter stages are determined by the number of true leaves in excess of 4 cm in length. The number of vegetative stages is dependent upon the number of true leaves formed by the plant, making the method flexible but accurate. The reproductive development was divided into nine stages based on the development of the inflorescence from its initial appearance through anthesis to physiological maturity of the seed. This method of describing the stages of development in sunflower is rapid, accurate, greatly simplifies current methods, and can be used to determine plant development for either single or branched inflorescence sunflower.

The large area of rice (Oryza sativa L.) production worldwide is critical to the well being of large numbers of the world's people. Yet for rice, the most important single plant species for human nutrition, there is not a widely used growth staging system. Despite good points of the published rice growth staging systems, none has been used widely for describing rice growth and development. Consequently, an objective growth staging system with enumeration adapted to cumulative leaf number (CLN) would improve communication among scientists, farmers, and educators. We propose a rice developmental staging system divided into three main phases of development: seedling, vegetative, and reproductive. Seedling development consists of four growth stages: unimbibed seed (S0), radicle and coleoptile emergence from the seed (S1, S2), and prophyll emergence from the coleoptile (S3). Vegetative development consists of stages V1, V2 … VN; N being equal to the final number of leaves with collars on the main stem. Reproductive development consists of 10 growth stages based on discrete morphological criteria: panicle initiation (R0), panicle differentiation (R1), flag leaf collar formation (R2), panicle exertion (R3), anthesis (R4), grain length and width expansion (R5), grain depth expansion (R6), grain dry down (R7), single grain maturity (R8), and complete panicle maturity (R9). Assigning rice growth stages based on discrete morphological criteria will result in unambiguous growth‐stage determination. For example, using this system, two people staging the same plant will arrive at the same growth stage. This is because the system exploits the presence or absence of distinct morphological criteria in a symbolic logic dichotomous framework that only permits yes or no answers.

This paper addresses the question of whether there has been an increase in yield potential of maize (Zea mays L.) hybrids released in the north‐central United States since the advent of the “Green Revolution” that began in the late 1960s. Because there are few published data about hybrid growth rates and yield‐determining plant traits when grown at yield potential levels, we attempt to address this issue indirectly by evaluation of maize breeding efforts, changes in plant traits of commercial hybrids, and by comparison of statewide average yield trends and yield trends in sanctioned yield contests. On the basis of these sources of information and a definition of yield potential as the yield that can be achieved with an adapted hybrid when grown without obvious stress of any kind, we found that there is conflicting evidence to support the hypothesis that maize yield potential has increased. We recommend experimental approaches to quantify and investigate the determinants of maize yield potential in the north‐central United States and for use in breeding hybrids with greater yield potential.

Yield potential is defined as the yield of a cultivar when grown in environments to which it is adapted, with nutrients and water non‐limiting and with pests, diseases, weeds, lodging, and other stresses effectively controlled. As such, it is distinguished from potential yield, which we define here as the maximum yield which could be reached by a crop in given environments, as determined, for example, by simulation models with plausible physiological and agronomic assumptions. Several implications of the definitions given above are considered, particularly those arising from cultivar interactions with agronomic practices and with the biotic and abiotic environments. We then discuss both direct and indirect methods of measuring progress in yield potential. Continuing progress in yield potential through conventional breeding is apparent in many crops, and is significant for yield progress at the farm level under a wide range of conditions. Among the small grain cereals, greater yield potential has derived mainly from the rise in harvest index associated with dwarfing, whereas in maize (Zea mays L.), it has come from increased tolerance to closer planting. The duration of photosynthetic activity has been extended in several crops but there is little evidence of increases in photosynthetic capacity or maximum crop growth rate. The rise in genetic yield potential in wheat and maize cultivars has been associated with progressive widening of their genetic background, and there is little sign of this slowing down.

Since the release of IR8 in 1966, 42 additional indica rice (Oryza sativa L.) cultivars developed by the International Rice Research Institute (IRRI) for the irrigated and favorable rainfed lowlands have been released in the Philippines. The maximum yield of IR8 has been reduced by about 2 Mg ha⁻¹ during the past 30 yr. Empirical breeding for population improvement within the indica germplasm has resulted in the maintenance of rice yield potential in the tropics of about 10 Mg ha⁻¹. To break the yield barrier, several approaches are being explored. These include development of a new plant type (NPT) with low tillering capacity and large panicles from tropical japonica germplasm and exploitation of heterosis through intervarietal and intersubspecific hybrids. Hybrid rice between indicas increased yield potential by about 9% under the tropical conditions. The higher yield potential of indica/indica hybrids compared with indica inbred cultivars was attributed to the greater biomass production rather than harvest index. New plant type breeding has not yet improved yield potential due to poor grain filling and low biomass production. Factors that cause poor grain filling and low biomass production of the NPT lines have been identified. Selecting parents with good grain filling traits, introduction of indica genes into NPT's tropical japonica background, and a refinement of the original NPT design are expected to improve the performance of the NPT lines. Further enhancement in yield potential may be possible from use of intersubspecific heterosis between indica and NPT lines.