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Results of 25 Years of Upland Rice Breeding in Brazil

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914 WWW.CROPS.ORG CROP SCIENCE, VOL. 51, MAYJUNE 2011 RESEARCH U pland rice ( Oryza sativa L.) is an important crop in Brazil, with almost 2 million ha planted each year. Although this area is less than half of the area planted in the 1980s as a pioneer crop in the Brazilian savannas (also known as Cerrado), this system is regarded as having a high potential for expansion (Pinheiro et al., 2006) in a scenario of increase in the international demand for rice. The Brazilian Corporation for Agricultural Research (Embrapa) conducts an upland rice breeding program since 1975, in collaboration with other public institutions, aiming at develop- ing rice cultivars with improved agronomic and grain quality char- acteristics, resistant to biotic and abiotic stresses, and well adapted to the upland rice growing regions in Brazil (Pinheiro et al., 2004). Plant breeding is a long-term investment; hence, decisions made today will show their consequences years later in the per- formance of the resulting cultivars. Results achieved in the past can help to forecast trends and plan ahead for program adjust- ments. For this reason, it is important to monitor the efficiency of the breeding program through time. Genetic gain estimates are Results of 25 Years of Upland Rice Breeding in Brazil Flavio Breseghello,* Orlando Peixoto de Morais, Patrícia Valle Pinheiro, Ana Carolina Simões Silva, Emilio da Maia de Castro, Élcio Perpétuo Guimarães, Adriano Pereira de Castro, José Almeida Pereira, Altevir de Matos Lopes, Marley Marico Utumi, and Jaison Pereira de Oliveira ABSTRACT The objective of this study was to estimate the results of the upland rice (Oryza sativa L.) breed- ing program conducted by the Brazilian Agri- cultural Research Corporation (Embrapa) and collaborators over the period of 1984 to 2009 covering 25 annual steps of improvement. The best lines generated by this program are evalu- ated in “value for cultivation and use (VCU) tri- als.” This study used data from 603 VCU trials conducted in seven Brazilian States. The group of lines entering VCU in each year was taken as a sample of the elite program in that year. Best linear unbiased estimates (BLUEs) of the means of groups were computed, and the regression of the BLUEs on years was taken as an estimate of the efficiency of the breeding program. Traits studied were grain yield (GY), days to flower- ing (DTF), and plant height (PH). For GY, three phases were described: from 1984 to 1992, the gain for GY was nonsignificant, from 1992 to 2002, the yearly gain was 15.7 kg ha −1 (0.53%), and from 2002 to 2009, the yearly gain was 45.0 kg.ha −1 (1.44%). No evidence of yield plateau was observed. There was a reduction of 0.25 d yr −1 in DTF and 0.52 cm yr −1 in PH, reflecting the change from traditional to modern cultivars. Factors influencing the results of the breeding program in this period are discussed. F. Breseghello, O.P. Morais, P.V. Pinheiro, A.C.S. Silva, E.M. Cas- tro, É.P. Guimarães, A.P. Castro, and J.P. Oliveira, Embrapa Rice and Beans, Santo Antonio de Goiás, GO, Brasil 75375-000; J.A. Pereira, Embrapa Mid-North. A.M Lopes, Embrapa Eastern Amazon. M.M. Utumi, Embrapa Rondônia. Received 6 June 2010. *Corresponding author (fl[email protected]). Abbreviations: BLUE, best linear unbiased estimate; BLUP, best lin- ear unbiased predictor; DTF, days to flowering; GY, grain yield; PH, plant height; TPE, target population of environments; VCU, value for cultivation and use. Published in Crop Sci. 51:914–923 (2011). doi: 10.2135/cropsci2010.06.0325 Published online 14 Mar. 2011. © Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
Transcript
Page 1: Results of 25 Years of Upland Rice Breeding in Brazil

914 WWW.CROPS.ORG CROP SCIENCE, VOL. 51, MAY–JUNE 2011

RESEARCH

Upland rice (Oryza sativa L.) is an important crop in Brazil, with almost 2 million ha planted each year. Although this

area is less than half of the area planted in the 1980s as a pioneer crop in the Brazilian savannas (also known as Cerrado), this system is regarded as having a high potential for expansion (Pinheiro et al., 2006) in a scenario of increase in the international demand for rice.

The Brazilian Corporation for Agricultural Research (Embrapa) conducts an upland rice breeding program since 1975, in collaboration with other public institutions, aiming at develop-ing rice cultivars with improved agronomic and grain quality char-acteristics, resistant to biotic and abiotic stresses, and well adapted to the upland rice growing regions in Brazil (Pinheiro et al., 2004).

Plant breeding is a long-term investment; hence, decisions made today will show their consequences years later in the per-formance of the resulting cultivars. Results achieved in the past can help to forecast trends and plan ahead for program adjust-ments. For this reason, it is important to monitor the effi ciency of the breeding program through time. Genetic gain estimates are

Results of 25 Years of Upland Rice Breeding in Brazil

Flavio Breseghello,* Orlando Peixoto de Morais, Patrícia Valle Pinheiro, Ana Carolina Simões Silva, Emilio da Maia de Castro, Élcio Perpétuo Guimarães, Adriano Pereira de Castro, José Almeida Pereira,

Altevir de Matos Lopes, Marley Marico Utumi, and Jaison Pereira de Oliveira

ABSTRACT

The objective of this study was to estimate the

results of the upland rice (Oryza sativa L.) breed-

ing program conducted by the Brazilian Agri-

cultural Research Corporation (Embrapa) and

collaborators over the period of 1984 to 2009

covering 25 annual steps of improvement. The

best lines generated by this program are evalu-

ated in “value for cultivation and use (VCU) tri-

als.” This study used data from 603 VCU trials

conducted in seven Brazilian States. The group

of lines entering VCU in each year was taken as

a sample of the elite program in that year. Best

linear unbiased estimates (BLUEs) of the means

of groups were computed, and the regression

of the BLUEs on years was taken as an estimate

of the effi ciency of the breeding program. Traits

studied were grain yield (GY), days to fl ower-

ing (DTF), and plant height (PH). For GY, three

phases were described: from 1984 to 1992, the

gain for GY was nonsignifi cant, from 1992 to

2002, the yearly gain was 15.7 kg ha−1 (0.53%),

and from 2002 to 2009, the yearly gain was 45.0

kg.ha−1 (1.44%). No evidence of yield plateau

was observed. There was a reduction of 0.25

d yr−1 in DTF and 0.52 cm yr−1 in PH, refl ecting

the change from traditional to modern cultivars.

Factors infl uencing the results of the breeding

program in this period are discussed.

F. Breseghello, O.P. Morais, P.V. Pinheiro, A.C.S. Silva, E.M. Cas-

tro, É.P. Guimarães, A.P. Castro, and J.P. Oliveira, Embrapa Rice and

Beans, Santo Antonio de Goiás, GO, Brasil 75375-000; J.A. Pereira,

Embrapa Mid-North. A.M Lopes, Embrapa Eastern Amazon. M.M.

Utumi, Embrapa Rondônia. Received 6 June 2010. *Corresponding

author (fl [email protected]).

Abbreviations: BLUE, best linear unbiased estimate; BLUP, best lin-

ear unbiased predictor; DTF, days to fl owering; GY, grain yield; PH,

plant height; TPE, target population of environments; VCU, value for

cultivation and use.

Published in Crop Sci. 51:914–923 (2011).doi: 10.2135/cropsci2010.06.0325Published online 14 Mar. 2011.© Crop Science Society of America | 5585 Guilford Rd., Madison, WI 53711 USA

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Page 2: Results of 25 Years of Upland Rice Breeding in Brazil

CROP SCIENCE, VOL. 51, MAY–JUNE 2011 WWW.CROPS.ORG 915

useful as indicators of the effi cacy of the methodology used as well as the potential of the germplasm exploited.

Two types of methods have been used for estimating genetic gains from plant breeding programs through time: (i) evaluation of old and recent cultivars in fi eld trials, fol-lowed by a regression analysis of phenotypic values as a function of the year of release of the cultivars (e.g., Peng et al., 2000; Tabien et al., 2008; De Vita et al., 2007), and (ii) meta-analysis of historical data from series of fi eld tri-als, normally conducted with the aim of testing the value for cultivation and use (VCU) of candidate lines for vari-etal release. Meta-analysis has been used more frequently in Brazil (e.g., Soares et al., 1999; Breseghello et al., 1999; Cargnin et al., 2008) than in other countries, probably due to the infl uential work of Prof. Vencovsky (Vencovsky et al., 1986). If proper statistical methods are used, meta-anal-ysis allows adjustment for environmental and experimental design eff ects in the unbalanced data sets normally available in breeding programs (Breseghello et al., 1998).

Both approaches (i.e., cultivar comparison and meta-analysis) are capable of computing valid estimates of genetic gains. Advantages of cultivar comparison are that materials can be evaluated under homogeneous crop management for several traits simultaneously under equal methods of measurement. On the other hand, meta-analysis of a large data set allows better sampling of the environmental variation in the target population of envi-ronments (TPE), both in time and space, and includes both released and nonreleased materials.

The contribution of plant breeding for grain yield has been studied in several annual crops (Table 1). In most cases, those studies indicated that plant breeding resulted in productivity gains. Although estimates vary consider-ably, genetic gains for grain yield are normally a few tens of kilograms per year. It is common to present the gain per year as a percentage of the mean yield for the crop under study. In this way, most rates of progress correspond to less than 1% (e.g., Zhou et al., 2007a).

Peng et al. (2000) evaluated the genetic gain for irrigated rice, based on 12 rice cultivars developed at the International Rice Research Institute (IRRI), in the period of 1966 to 1995, resulting in a genetic gain of 75 to 81 kg ha−1 yr−1, cor-responding to 1% per year. Breseghello et al. (1999) estimated the genetic gain for irrigated rice in the northeast of Brazil as 0.8% per year. Soares et al. (1999) computed the genetic gain for upland rice in the state of Minas Gerais, for the short-cycle and the intermediate-cycle subprograms, fi nding the genetic gains of 23.8 and 46.4 kg ha−1 yr−1, respectively. No report has been published so far on the genetic gain of the national rice breeding program in Brazil.

This study was conducted with the objective of esti-mating the genetic gain resulting from Embrapa’s upland rice breeding program on grain yield, days to fl owering, and plant height through the meta-analysis of a large data

set of fi eld trials conducted in the most important upland rice growing states in Brazil in the period of 1984 to 2009.

MATERIALS AND METHODS

Source of DataThe data used in this study were taken from the records of the

VCU trials conducted by Embrapa and collaborators, under the

scope of the upland rice breeding program, including 603 trials

conducted during the period of 1984 to 2009, thus representing

25 steps of improvement (Table 2). The average number of trials

per year was 23.2, varying from eight trials in 1990 to 39 trials

in 1995. The geographic area represented includes the states of

Goiás, Mato Grosso, Tocantins, Pará, Rondônia, Maranhão, and

Piauí, where most of the upland rice is planted in Brazil nowa-

days. The data set comprised 45,688 fi eld plots for grain yield (an

average of 1757 plots per year), from which 37,119 plots (81.2%)

had data for days to fl owering and 41,468 plots (90.8%) had data

for plant height. On average, 40.5 lines were tested in each year,

varying from 17 lines in 2008 to 79 lines in 1993, whereas the

number of lines debuting in VCU (lines that entered VCU for

the fi rst time) varied from three in 1991 to 40 lines in 1986.

In the fi rst year of the series (1984), all lines were consid-

ered novel, although not all of them were actually debuting

in the VCU in that year. Only trials with reliable data, unam-

biguous genotype identifi cation, and acceptable experimental

precision (coeffi cient of variation for grain yield [GY] < 25%)

were used.

Description of Field ExperimentsThe typical VCU trial used was conducted in randomized com-

plete block design with four replicates and approximately 20

entries, from which four were check cultivars and the rest were

breeding lines under test for the fi rst, second, or third year.

Novel lines were selected for VCU based on preliminary and

regional trials, which are similar to VCU trials, although in a

reduced number of sites. Bad performance in the VCU resulted

in elimination of the material, whereas good performance

resulted in further testing or submission for release as com-

mercial cultivars. Cultivars or inbred lines from other breeding

programs have been tested in those trials as well, for the pur-

pose of comparison with Embrapa’s materials.

In the VCU trials, dry seeds were hand- or machine sown in

rows normally 5 m long. Plots were composed of four or fi ve rows.

One row in each side was considered a border, and the intermedi-

ate 4 m of the internal rows were evaluated and reaped. All trials

were conducted in the rainy season, without irrigation (exception-

ally, supplementary sprinkler irrigation may have been provided).

Chemical fertilizers were applied in the soil at sowing, in interme-

diate to high rates compared to farmer’s management. Nitrogen

fertilizer was normally top-dressed at the end of the vegetative

stage. Weed control was made by hand weeding, herbicides, or a

combination of the two. Insect control was made with insecticides

applied to the furrow in most trials and, if needed, complemented

with canopy spraying. No fungicides were applied, for evaluation

of genetic resistance to fungal diseases.

All traits were evaluated at the plot level. Days to fl owering

was evaluated as the interval between sowing and approximately

Page 3: Results of 25 Years of Upland Rice Breeding in Brazil

916 WWW.CROPS.ORG CROP SCIENCE, VOL. 51, MAY–JUNE 2011

50% of the plants fl owered. Plant height was evaluated as the

distance from the ground to the tip of the highest panicle in the

prematurity stage. Plots were hand harvested and threshed and

grains were sun dried and stored in room temperature for a few

weeks for grain moisture stabilization before weighing. Grain

yield was adjusted to kilograms per hectare.

Statistical AnalysisMaterials were grouped according to the fi rst year when they

have been included in the VCU trials. For example, the group

2000 includes all the materials for which the earliest VCU data

available are from the year 2000, irrespective of how many

years they stayed under testing or whether the lines have been

discarded or released as cultivars. Each year, some lines were

discarded and others were added to the VCU trials. However,

there were always common lines and checks between consecu-

tive years, allowing control of the environmental variation

through the entire period.

From the 493 lines evaluated in the period, 376 were from

Embrapa’s breeding program, whereas the remaining lines

where from state-level programs or private-sector programs or

were introductions from other countries. All materials origi-

nated from other breeding programs were pooled into a sepa-

rate group. This group contributed to the adjustment of the

model but was not used in the regression step, for the estimation

of the genetic gain.

A mixed-eff ects model was used, with groups as fi xed

eff ects and lines within groups, years, experiments within

years, and replicates within experiments as random eff ects. The

statistical model can be represented as:

Yijkmn

= μ + gj + l

i/g

j + a

k + t

m/a

k + b

n/at

km + ε

ijkmn

Table 1. Summary of results from previous studies on genetic gain of plant breeding programs.

Crop† Region Period Method of estimation Genetic gain (ha–1 yr–1) Reference

Rice, irrigated Brazil, mid-north 1984–1997 Meta-analysis 18 kg (0.3%) Rangel et al., 2000

Rice, irrigated Brazil, northeast 1984–1993 Meta-analysis 54.9 kg (0.8%) Breseghello et al., 1999

Rice, irrigated United States, Texas 1944–1992 Cultivar comparison 42.2 kg (high N input)

26.3 kg (low N input)

Tabien et al., 2008

Rice, irrigated Philippines 1966–1995 Cultivar comparison 75 to 81 kg (1%) Peng et al., 2000

Rice, upland Brazil, State of

Minas Gerais

1975–1995 Meta-analysis 23.8 kg (short cycle);

46.4 kg (medium cycle)

Soares et al., 1999

Rice, irrigated

and rainfed

India 1976–1997 Meta-analysis NS‡ (upland, rainfed lowland and irrigated) Muralidharan et al., 2002

Barley Argentina 1944–1998 Cultivar comparison 1944–1970: NS

1970–1998: 41 kg

Abeledo et al., 2003

Sorghum United States,

Nebraska

1950–1999 Cultivar comparison 13.5 kg Mason et al., 2008

Maize United States,

Nebraska

1950–1999 Cultivar comparison 37.4 kg Mason et al., 2008

Sunfl ower Argentina 1983–2005 Meta-analysis Grain yield: NS

Oil yield: 11.9 kg

De La Vega et al., 2007

Bread wheat Brazil, State of

Minas Gerais

1976–2005 Meta-analysis 48 kg (1.8%) Cargnin et al., 2008

Winter wheat Southern China 1949–2000 Cultivar comparison 14.0 kg (0.3%) to 40.8 kg (0.7%)

for different provinces

Zhou et al., 2007a

Winter wheat Northern China 1960–2000 Cultivar comparison 32.1 kg (0.5%) to 72.1 kg (1.2%)

for different provinces

Zhou et al., 2007b

Durum wheat Italy 1900–1990 Cultivar comparison 19.9 kg De Vita et al., 2007

†Rice, Oryza sativa L.; barley, Hordeum vulgare L.; sorghum, Sorghum bicolor (L.) Moench.; maize, Zea mays L.; sunfl ower, Helianthus annuus L.; bread wheat or winter wheat,

Triticum aestivum L.; durum wheat, Triticum turgidum L. subsp. durum (Desf.) Husn.‡NS, nonsignifi cant.

Table 2. Summary of the Embrapa’s upland rice breeding

program data set used in this study.

YearNo. of trials

Total no. of lines tested

No. of new lines from Embrapa

No. of fi eld plots

1984 12 54 37 700

1985 38 58 26 2052

1986 19 77 40 1358

1987 10 67 9 674

1988 23 54 4 1484

1989 10 34 9 792

1990 8 32 16 450

1991 16 34 3 1060

1992 15 60 23 944

1993 24 79 24 1477

1994 19 44 9 1536

1995 39 49 12 2597

1996 22 28 6 2046

1997 26 32 13 2143

1998 33 37 21 2552

1999 32 42 16 2485

2000 34 45 16 2756

2001 24 34 15 2297

2002 18 28 9 1819

2003 27 28 9 2733

2004 26 25 10 2408

2005 27 26 13 2299

2006 18 28 13 1830

2007 25 18 5 1520

2008 31 17 6 1841

2009 27 23 12 1835

Arithmetic

mean

23.2 40.5 14.5 1757

Total 603 493 376 45688

Page 4: Results of 25 Years of Upland Rice Breeding in Brazil

CROP SCIENCE, VOL. 51, MAY–JUNE 2011 WWW.CROPS.ORG 917

in which Yijkmn

is the data at the plot level, μ is the intercept,

gj is the fi xed eff ect of group j, l

i/g

j is the random eff ect of line

i within group j, ak is the random eff ect of year k, t

m/a

k is the

random eff ect of trial m within year k, bn/at

km is the random

eff ect of block n within trial m in year k, and εijkmn

is the random

error N(0, σ2).

Analysis was done in SAS (SAS Institute, 2004), with the

following commands:

proc mixed; class group line year trial block; model GY DTF PH

= group; random year trial(year) block(year trial) line(group)/s;

lsmeans group/cov; run;.

Proc Mixed solves the following matrix equation by

restricted maximum likelihood to estimate best linear unbiased

estimates (BLUEs) of the fi xed eff ects and the corresponding

matrix of covariances.

y = Xβ + Zλ + εin which y is the vector of observations, X and Z are the design

matrices of fi xed and random factors, respectively, β is the vec-

tor of fi xed eff ects of groups, λ is the vector of random eff ects

of years, trials within years, blocks within trial within year, and

lines within groups, and ε is the vector of random errors.

Genetic gain was computed as the generalized linear

regression coeffi cients of the BLUEs on years, according to

the model:

θ = (X′V−1X)−1(X′V−1Y)

in which θ is the vector of solutions of the generalized linear

regression, X is the matrix of incidence, formed by a column of

1’s and a column indicating the year in the series corresponding

to the groups, V is the matrix of covariances of the BLUEs of

groups, and Y is the vector of BLUEs of groups.

Signifi cance of slopes was evaluated by the t test. Relative

genetic gain was estimated as the ratio between the slope and

the intercept, in percentage, in which the intercept represents

the initial stage of the breeding program.

The best linear unbiased predictors (BLUPs) of some lines

(those released as cultivars or in the pipeline) were computed as

the sum of the BLUEs for the group plus the eff ect of the line

within group.

RESULTS

Structure of the Data Set

All of the design variables were considered random factors for modeling part of the variance of the data as covariances between observations taken within groups. Lines within groups were considered as random samples from the elite breeding program in the year corresponding to the group. The structure of the matrix Z and the estimates of vari-ance components are presented in Table 3. Years and trials within year responded by a large proportion of the vari-ance, especially for GY and PH. The importance of tri-als (loosely corresponding to locations) in this data set is explained by the fact that the geographic area represented is very large, including many diff erent soil types, cli-mate patterns, and biotic and abiotic stresses. Blocks pre-sented small importance for DTF and PH and moderate

importance for GY. Lines within groups responded by a moderate proportion of the variance for GY, probably because lines entering VCU were previously selected for GY in preliminary trials. Contrastingly, a great propor-tion of the variance for DTF was related to lines, because in former years there were two contrasting groups of materials: the early fl owering lines and the intermediate-cycle lines (late-fl owering lines have not been focused on by rice breeding in Brazil in this period).

The BLUPs of all lines evaluated were computed, and Pearson’s correlations between variables were estimated. Those correlations may result from simultaneous selection for diff erent traits in the breeding program. Considering only Embrapa lines, no correlation was found between GY and DTF, indicating that early fl owering lines were not less productive than intermediate-cycle lines, as one might expect. Mild negative correlation was found between GY and PH (r = −0.23 and p = 0.001), probably due to the fact that modern materials are shorter and higher yielding. A weak positive correlation was detected between PH and DTF (r = 0.11 and p = 0.05), also an expected result from combined selection for short and early-fl owering plants.

Genetic Gain for Grain YieldTaking the whole period of 26 yr (corresponding to 25 yr of improvement, considering 1984 as year zero), the mean gain for GY was 19.1 kg ha−1, corresponding to 0.67% per year. However, gains were clearly nonlinear. Those results were analyzed in the light of the history of the breeding program (see the Discussion Section) and the years 1992 and 2002 were taken as break points, dividing the period under study in three diff erent phases (Fig. 1 and Table 4).

In the fi rst phase, from 1984 to 1992 (eight steps), no signifi cant gain was observed for GY. Although there was a short stretch of gains from 1987 to 1990, those gains were not retained. The year of 1991 stands out of the series, with only three lines entering VCU trials and pre-senting very low GY. The mean of the group 1992 was nearly the same from the beginning of the series. In the second phase, from 1992 to 2002 (ten steps), some trend of increase in GY was observed. In those 10 yr, genetic improvement added an average of 15.7 kg ha−1 yr−1 (p < 0.05), representing 0.53% per year. The third phase, from 2002 to 2009 (seven steps), presented the highest estimate of genetic gain in the period, with a slope of 45.0 kg ha−1 yr−1 (p < 0.01), representing 1.44% per year. Group 2008 presented the highest mean of the period under study, and group 2009 had the second highest mean. No trend of ceasing gains for GY was observed. Parametrically, the total genetic gain in the period under study was 471.6 kg ha−1, being 156.6 kg ha−1 from the second phase and 315.0 kg ha−1 from the third phase. Therefore, 2/3 of the total gain for GY in the 25-yr period was achieved in the last seven improvement steps.

Page 5: Results of 25 Years of Upland Rice Breeding in Brazil

918 WWW.CROPS.ORG CROP SCIENCE, VOL. 51, MAY–JUNE 2011

Table 3. Estimates of components of variance for random factors in the mixed model.

Random factor Number of columns in Z† Grain yield Days to fl owering Plant height

Year 26 105357 20.17 66.23

Trial within year 603 849670 59.37 215.45

Block within trial within year 2354 32216 0.42 4.84

Line within group 493 84426 78.96 104.57

Residual [3476] 487024 12.14 58.01

†Z, the design matrix of random factors.

Figure 1. Genetic gain for grain yield in the upland rice breeding program. Black dots represent the mean of groups of lines debuting in

the value for cultivation and use (VCU) trials. Open circles represent best linear unbiased predictor (BLUP) for cultivars according to their

group. Generalized linear regression lines and equations are given for group means on years for three phases within the period under

study. ns, nonsignifi cant; *, signifi cant at the 0.05 probability level; **, signifi cant at the 0.01 probability level.

Table 4. Estimates of parameters for the generalized linear regression of grain yield, days to fl owering, and plant height on

years in the period of 1984 to 2009.

Grain yield (kg ha−1) Days to fl owering Plant height (cm)

1984–1992 1992–2002 2002–2009 1984–2009 1984–2009

Intercept 2917.5 2961.3 3127.3 86.91 107.53

Slope (gain yr−1) 6.55 NS† 15.66 * 44.99 ** −0.254 *** −0.522 ***

Standard deviation 10.21 8.35 16.03 0.061 0.073

t value 0.64 1.87 2.81 −4.16 −7.15

p-value 0.261 0.031 0.003 <0.0001 <0.0001

Relative gain – 0.53% 1.44% −0.29% −0.49%

*Signifi cant at α = 0.05 by the t test.

**Signifi cant at α = 0.01 by the t test.

***Signifi cant at α = 0.001 by the t test.†NS, not signifi cant.

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CROP SCIENCE, VOL. 51, MAY–JUNE 2011 WWW.CROPS.ORG 919

Genetic Gain for Days to Flowering

The cycle of the lines from sowing to fl owering presented a trend of reduction at a rate of 0.25 d yr−1 (p < 0.0001). In the whole period, this change represented a reduction of 6.35 d in the duration of the crop (Fig. 2a). The reduc-tion in DTF was due more to the selection against late-fl owering lines than for selection for very early-fl owering lines. Since 2001, the DTF mean remained almost con-stant, around 80 d.

The cycle of released cultivars showed an interesting trend (Fig. 2a). Until 1995, there were two clearly distinct groups: the early-fl owering cultivars, with DTF ≤ 75 d, and the inter-mediate-cycle cultivars, with DTF ≥ 85 d. No cultivars from that period presented DTF between 75 and 85, whereas after the year 2000 all released cultivars and lines in the pipeline for release presented fl owering time within that range.

Genetic Gain for Plant HeightPlant height was reduced at a mean rate of 0.52 cm yr−1 (p < 0.0001), which represents a reduction of 13 cm for the whole period (Fig. 2b). Until 1995, most group means were above 100 cm, whereas after that year most group means were below that value. In the period 2003 to 2007, mean PH increased at a pace of approximately 3 cm yr–1. The groups 2008 and 2009 reverted most of this problem, presenting mean plant height of approximately 95 cm.

The cultivars released by the program presented PH varying from 88 to 120 cm. The range of variation was larger in the early phase, before 1990. The reduction of the mean PH observed through time was due to selection against tall plants rather than selection for very short plants.

DISCUSSIONThis study describes the facts related to the largest upland rice breeding program in Brazil, for a period of a quar-ter century, in which changes in plant type, grain type, genetic background, and breeding methods were observed (Pinheiro et al., 2004). A very large data set was used, representing a wide range of years, locations, input levels, and genotypes, within the broad TPE represented by the upland rice crop in the center-north of Brazil.

The data set used in this meta-analysis was highly unbalanced, since diff erent lines were evaluated in dif-ferent locations and years. The 15 most important check varieties represented 10,471 data points (22.9% of the data), whereas 57 lines had fewer than 10 data points each. The mixed model analysis used in this study is consid-ered robust against data unbalance and generates estimates for fi xed eff ects and predictors for random eff ects that are unbiased and have minimum error variance (BLUE and BLUP; Searle, 1971). The expectation of the BLUEs of groups are free of eff ects of design factors, including years;

Figure 2. Genetic gain for (a) days to fl owering and (b) plant height in the upland rice breeding program. Black dots represent the mean

of groups of lines debuting in the value for cultivation and use (VCU) trials. Open circles represent best linear unbiased predictor (BLUP)

for cultivars according to their group. Generalized linear regression line and equation are given for group means on years. ***, signifi cant

at the 0.001 probability level.

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920 WWW.CROPS.ORG CROP SCIENCE, VOL. 51, MAY–JUNE 2011

hence, they can be taken as estimates of the genetic value of the program in a given year. The slope of the linear regression of those estimates on the time represented the mean genetic gain of the program.

The genetic gain for grain yield computed in this study was satisfactory, especially considering that it accelerated in recent years (Fig. 1). Compared to previous estimates from other crops, such as wheat (Triticum aestivum L.), sun-fl ower (Helianthus annuus L.), sorghum [Sorghum bicolor (L.) Moench], and maize (Zea mays L.) (Table 1), the gain of 45 kg ha−1 (1.44%) per year, observed in the third phase, is rela-tively high. However, if the whole period is considered, the mean gain of 19.1 kg ha−1 yr−1 (0.67%) is not as impressive.

A previous study on the genetic gain of upland rice (Soares et al., 1999), for a state level breeding program in collaboration with Embrapa, estimated the progress per year at 23.8 kg ha−1 for early-fl owering lines and 46.4 kg ha−1 for intermediate-cycle lines. That state was not covered in the present study; nevertheless, the results found here are similar in magnitude.

Irrigated rice, for comparison, has presented limited progress for yield potential in the post-green revolution era. Muralidharan et al. (2002) found no gains for yield in a meta-analysis of data from 21 yr of INGER (Inter-national Network for Germplasm Evaluation of Rice) tri-als in India although, due to the reduction observed in crop duration, yield per day has increased. The genetic gain for irrigated rice breeding has been computed for two diff erent regions in Brazil, considering only semi-dwarf germplasm. In the mid-north (the states of Mara-nhão and Piauí), the gain per year was only 18 kg ha−1 (Rangel et al., 2000), whereas for the northeast the gain was estimated at 54.9 kg ha−1 (Breseghello et al., 1999). Those results are of similar magnitude compared to the progress in this study for upland rice. However, when the transition from traditional varieties to modern varieties is included in the series, as in Peng et al. (2000), the mean gain of irrigated rice is signifi cantly higher.

Wheat is a crop with similar mean yield compared to upland rice; thus it is interesting to compare the genetic gains for both species. Gains reported for bread wheat in Brazil are of 48 kg ha−1 yr−1 (Cargnin et al., 2008), approx-imately the same value found for the third phase in this study (2002–2009). Estimates of gain for wheat in China (Zhou et al., 2007a, b) varied from 14 to 72 kg ha−1 yr−1. On average, those results indicate that upland rice breed-ing in Brazil must sustain the gains of the third period for keeping up with the pace of wheat improvement.

Phases of the Breeding ProgramThree phases of the breeding program were recognized in this study. A similar trend was found by Abeledo et al. (2003) for barley (Hordeum vulgare L.) improvement in Argentina, with a phase of null gains followed by a phase of linear progress.

Phase I (1984–1992) was a period of “trial and error,” when a large number of lines were tested but no genetic gain for GY was achieved. In this period, lines var-ied widely for DTF and PH, revealing a lack of a clear ideotype to be selected in the TPE. Brazilian landraces of upland rice belong to the tropical japonica subspecies, descending from varieties introduced by Portuguese set-tlers (Pereira, 2002). This germplasm is characterized by tall plants with droopy leaves, moderate tillering, and large panicles, which are vigorous and weed competitive. Those varieties were desirable for low input farming, with manual weeding and harvesting; however, they presented low harvest index and were prone to lodging. Most cul-tivars from the fi rst phase (e.g., Guarani, Rio Paraguai, Xingu) presented characteristics of the traditional germ-plasm and are now considered obsolete.

Phase II (1992−2002) was marked by a strong infl u-ence of introduced materials, especially from CIAT and the United States. CIAT’s infl uence was more impor-tant on plant type although having also infl uenced grain shape and amylose content. United States materials were introduced with the main purpose of improving grain quality. The preference for shorter plants in the second phase of the program refl ects a change of focus toward a high-input, fully mechanized cropping system, in which lodging resistance was a priority. During phase II, a great deal of novel variability was introduced within the scope of a collaborative breeding program between Embrapa and CIAT (Morais et al., 2006). CIAT upland materials, although based on japonica background, had some intro-gression of indica genome (e.g., from the parent Colombia 1) and revealed highly competitive in Brazil, resulting in seven cultivars released (Progresso, Maravilha, and Can-astra, resulting from lines introduced in Phase I, and BRS Bonança, BRS Carisma, BRS Talento, and BRSMG Curinga, from lines introduced in Phase II). This wave of introgression in the Brazilian program resulted in a reduction in the mean stature, abundant and upright til-lering, short and erect fl ag leaves, and lower panicles in the canopy, contributing to a signifi cant reduction in lodging proneness. Those traits were readily incorporated into the ideotype sought by Brazilian’s breeders.

Gains for GY in Phase II were faster until 1998; how-ever, most of it was reversed in a linear decay in the period of 1998 to 2001. The reason for that decay in mean yield was the ceasing of the supply of high yielding CIAT lines, while the lines resulting from the use of CIAT materials as parents in Embrapa’s program were not yet in VCU trials. Nevertheless, the reduction in DTF and PH observed in phase II added to the overall cropping system productivity, with a trend of increasing input use at farmer level. Tabien et al. (2008) also found a signifi cant reduction in cycle duration and plant stature in U.S. rice varieties, which

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implies that those traits are favorable both in irrigated and in rainfed rice systems.

Interestingly, grain characteristics were an impor-tant limiting factor for the adoption of cultivars directly derived from CIAT introductions. Moderate levels of ker-nel chalkiness and slightly sticky cooked grains have been perceived by consumers as relevant shortcomings. The three most important Embrapa cultivars currently in the market, BRS Sertaneja, BRS Monarca, and BRS Pepita, all resulted from crosses between CIAT parents and other materials used to correct those problems.

Phase III (2002–2009) represents the current stage of Embrapa’s breeding program, with emphasis on selection for GY while keeping other traits within a suitable range. The genetic gain for GY in the third phase was the high-est (Table 4). Plant stature and cycle are under stabilizing selection; therefore, those traits are expected to remain steady in the near future, with DTF around 80 d and PH around 95 cm. The linear increase in PH in the period from 2003 to 2007 raised concerns about reverting long term reduction for this trait and, for that reason, truncated selection for PH ≤ 100 cm is being applied. On the other hand, very short plants tend to be less productive and less weed competitive, so PH is expected to stabilize between 90 and 100 cm. There was a clear trend of reduction in the number of lines tested at VCU level through time (Table 2), refl ecting a more focused program with a clear ideo-type. Several lines from the third phase are in the pipe-line for release, for which GY estimates are above the best current cultivars. The introduction of those new lines is expected to contribute to increase the upland rice yield at farmer level in Brazil.

An alternative way of looking at the progress of the breeding program would be based on the variation of GY of the top-yielding cultivars released by the program. In this sense, Embrapa’s program has consistently pushed the yield ceiling upward through time (Fig. 1). Excepting the culti-var Mearim, which has very long cycle duration, the top-yielding cultivars frequently superseded previous records for GY, with a trend of acceleration in the later phases.

Factors Promoting the Acceleration of the Genetic Gain for Grain YieldSome explanations can be off ered for the faster gain for GY in Phase III. One of them is the application of a modifi ed pedigree breeding scheme, in which crosses are selected for grain yield in F

2 followed by plant selection within F

1:3

families. This procedure is repeated in the F5 generation

(Morais et al., 2006). This scheme combines early selec-tion for yield potential at the family level with ideotype selection at the single-plant level.

Furthermore, the program adopted a recurrent selec-tion philosophy in which selected plants are recombined to build elite populations with high potential for line

extraction. New variability is tested carefully before intro-duction in the elite gene pool, avoiding yield setbacks. Breseghello et al. (2009) estimated the genetic progress through recurrent selection on one upland rice synthetic population, fi nding a gain of 103 kg ha−1 yr−1 (3.6% of the population mean) and showing the high potential of this approach for rice breeding.

Finally, intense selection pressure is being applied on yield, since most of the elite population presented adequate plant type, cycle, and grain quality. The example from hybrid maize breeding shows that continuous gain for yield can be achieved through systematic selection in elite germ-plasm (Duvick, 2005). Embrapa’s upland rice breeding pro-gram is progressively becoming a maize-like program.

Factors Limiting the Genetic Gain for Grain YieldSome factors represented a restraint in the rate of genetic progress for yield. Disease resistance, especially blast resis-tance, has been a major selection factor during the period under study. Rice blast (Magnaporthe oryzae) is the most aggressive pathogen of upland rice in Brazil (Filippi et al., 2007) such that blast susceptibility has always been a major factor for discarding breeding lines or prevent-ing crosses between high-yielding cultivars that lack blast resistance. On the other hand, considering that VCU tri-als are not treated with fungicides, gains for disease resis-tance probably contributed to the observed gains for GY. There is a project under way for implementing marker-assisted selection in the routine of the breeding program, which could allow further enhancement of genetic gains for grain yield. The genetic gains reported here resulted exclusively from classical methods, since the application of molecular markers have not yet infl uenced the quality of the elite lines evaluated in fi nal trials.

Concomitantly with the changes in GY, DTF, and PH, a major shift in grain type was produced during the period under study (Fig. 3). The grain type of the tra-ditional upland varieties was long and wide with high chalkiness and low amylose content, resulting in relatively sticky rice after cooking. In the 1980s, those character-istics begun to be rejected in the market, such that the upland rice product had a price penalty compared to irri-gated rice. In response to that, high-quality varieties from the United States (e.g., Bluebelle, Lebonnet) were used in crosses for steering Embrapa’s upland rice program toward long slender kernels. Strong selection was applied for grain shape, intermediate amylose content and gelatini-zation temperature, high vitreousness, soft and nonsticky cooking quality, high milling yield at diff erent harvesting dates, glabrous and well closed husks, absence of awns, and nonshattering (neither too hard to thresh) panicles.

Selection for grain quality during most of the period covered by this study certainly had a signifi cant trade-off

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on GY progress. The current elite breeding population has converged to a very strict grain ideotype, and for this reason introduction of novel variability must be done with caution.

Another limiting factor has been the vast geographic region represented by the TPE of Embrapa’s upland rice breeding program, which encompasses a large range of soil, climate, and crop management variation. Consider-ing that elite lines must perform well for the average of those locations, the variance related to genotype × envi-ronment interaction is not well exploited (Pacheco et al., 2005). Subprograms focused on more specifi c TPEs could result in faster genetic gain for GY. However, the low geographic density of the upland rice crop in Brazil makes seed companies normally favor cultivars of broad adapta-tion with more marketing options.

CONCLUSIONSThe upland rice breeding program conducted by Embrapa and partners resulted in increase in grain yield and reduc-tion in plant height and duration of plant cycle in the period of 1984 to 2009. The gain for grain yield was high-est in recent years, showing no sign of yield plateau. Dur-ing the same period, great changes have been promoted in plant type and grain quality, adding value to modern upland rice cultivars.

AcknowledgmentsWe thank all the research assistants and fi eld workers that helped

generating the data used in this study. Special thanks to Dr. Antônio

Carlos de Oliveira, for the review on the statistical analysis.

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