Genetic Relationships among and Selection for Rice Yield and Yield Components

Crop Science ◽  
1993 ◽  
Vol 33 (2) ◽  
pp. 249 ◽  
Author(s):  
Kenneth A. Gravois ◽  
Ronald W. McNew
1994 ◽  
Vol 34 (7) ◽  
pp. 949 ◽  
Author(s):  
KA Gravois ◽  
RS Helms

Establishing a uniform rice (Oryza sativa L.) stand is an important beginning to managing a rice crop and attaining high yields. Most rice management practices in the United States are timed according to rice growth stages. Non-uniform rice stands, and subsequently non-uniform growth stages, present problems for the timely application of management practices for attaining high yields. Our objective was the determination of the effects of uneven emergence on rice yield, milling yield, and yield components. Experiments were conducted in 1988 and 1989 on a Hebert silt loam (Vertic Hapludoll) at the Southeast Branch Experiment Station near Rohwer, Arkansas. Uneven emergence was simulated by delayed (18 days from emergence) interseeding of rice to achieve 0, 20, 40, 60, and 80% uneven emergence. Each experiment was planted with the cultivars Lemont (semi-dwarf) and Tebonnet (tall) and was replicated 4 times. Rice yields for the uneven emergence treatment levels were significantly less than the rice yields seeded exclusively at PD1 (planting date 1), except for the uneven emergence levels 80-20 (80% planted at PD1 and 20% planted at PD2) and 60-40 for Tebonnet, and 60-40 in 1988 for Lemont. In 1989, there was a trend for head rice yields to decrease as uneven emergence levels increased. Average panicle density and number of grains per panicle for both Lemont and Tebonnet decreased with increasing uneven emergence, indicating a failure in the typical compensatory relationship between panicle density and grain per panicle. Lemont exhibited reduced average grain weights due to uneven emergence, especially at 80-20, 60-40, and 40-60 uneven emergence levels. Harvest indices were higher for PD1 than for PD2, except at 20-80 uneven emergence level. Essentially, the later emerging rice from the second planting acted much like a weed by competing against rather than contributing to rice yields. Late interseeding to enhance poor rice stands is unlikely to produce an economic return that could be expected from an adequate initial plant stand.


2001 ◽  
Vol 49 (4) ◽  
pp. 337-342 ◽  
Author(s):  
N. VASIC ◽  
M. IVANOVIC ◽  
L. A. PETERNELLI ◽  
D. JOCKOVIC ◽  
M. STOJAKOVIC ◽  
...  

The synthetic maize population 316PO2 was subjected to genetic correlation analyses between grain yield, yield components and morphological traits. The purpose was to enable estimates to be made of the advantage of using selection indices compared with selection based on grain yield only, and if that advantage was present, to choose enough simple selection indices for practical use. Selection indices were constructed out of four traits highly significantly correlated with grain yield, in addition to yield itself. Grain yield exhibited a highly significant additive genetic correlation with ear diameter (ra=0.588**), kernels row-1 (ra=0.643**), ears plant-1 (ra=0.871**) and ear height (ra=0.427**). The most efficient index was Index No. 14 (R.E.I12345= 108.83%), which included all four traits and grain yield. Index No. 3, one of the simplest forms of index, including only ears plant-1 and grain yield, showed slightly less relative efficiency (R.E.I35=107.24%) than Index No. 14. Using this simple form of index with two characters (Index No. 3) could improve the efficiency of selection for grain yield. The estimated advantage from its use is 179.6 kg/selection cycle for grain yield over selection based only on grain yield.


2020 ◽  
Vol 112 ◽  
pp. 125961 ◽  
Author(s):  
Chunhua Lv ◽  
Yao Huang ◽  
Wenjuan Sun ◽  
Lingfei Yu ◽  
Jianguo Zhu

HortScience ◽  
2000 ◽  
Vol 35 (4) ◽  
pp. 708-711 ◽  
Author(s):  
Christopher S. Cramer ◽  
Todd C. Wehner

The relationships between fruit yield and yield components in several cucumber (Cucumis sativus L.) populations were investigated as well as how those relationships changed with selection for improved fruit yield. In addition, the correlations between fruit yield and yield components were partitioned into partial regression coefficients (path coefficients and indirect effects). Eight genetically distinct pickling and slicing cucumber populations, differing in fruit yield and quality, were previously subjected to modified half-sib family recurrent selection. Eight families from three selection cycles (early, intermediate, late) of each population were evaluated for yield components and fruit number per plant in four replications in each of two testing methods, seasons, and years. Since no statistical test for comparing the magnitudes of two correlations was available, a correlation (r) of 0.7 to 1.0 or –0.7 to –1.0 (r2 ≥ 0.49) was considered strong, while a correlation of –0.69 to 0.69 was considered weak. The number of branches per plant had a direct positive effect on, and was correlated (r = 0.7) with the number of total fruit per plant over all populations, cycles, seasons, years, plant densities, and replications. The number of nodes per branch, the percentage of pistillate nodes, and the percentage of fruit set were less correlated (r < |0.7|) with total fruit number per plant (fruit yield) than the number of branches per plant. Weak correlations between yield components and fruit yield often resulted from weak correlations among yield components. The correlations among fruit number traits were generally strong and positive (r ≥ 0.7). Recurrent selection for improved fruit number per plant maintained weak path coefficients and correlations between yield components and total fruit number per plant. Selection also maintained weak correlations among yield components. However, the correlations and path coefficients of branch number per plant on the total fruit number became more positive (r = 0.67, 0.75, and 0.82 for early, intermediate, and late cycles, respectively) with selection. Future breeding should focus on selecting for the number of branches per plant to improve total fruit number per plant.


Crop Science ◽  
2019 ◽  
Vol 59 (1) ◽  
pp. 280-292 ◽  
Author(s):  
Yun Gao ◽  
Tiesong Hu ◽  
Qin Wang ◽  
Hongwei Yuan ◽  
Jiwei Yang

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