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Precision Agric (2013) 14:357–375 DOI 10.1007/s11119-012-9297-y

Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations B. V. Ortiz • K. B. Balkcom • L. Duzy • E. van Santen D. L. Hartzog

•

Published online: 20 January 2013 Ó Springer Science+Business Media New York 2013

Abstract Increasing the peanut (Arachis hypogea L.) digger efficiency by accurate placement over the target rows could minimize damaged pods and yield losses. Producers have traditionally relied solely on tractor operator skills to harvest peanuts. However, as peanut production has shifted to new growing regions in the Southeast US, producers face difficulties digging peanuts under conventional and new management schemes. The present study aimed to: (i) determine the effect of row deviations (RD) of the digger from the target row on peanut yield and quality, and (ii) determine the economic value of using RTK auto-steer guidance systems to avoid tractor deviations during peanut harvest. The study consisted of a randomized complete block design of tillage [conventional (CT) and strip tillage (ST)], row patterns [single (SR) and twin (TWR)] and row deviation (RD0 mm, RD90 mm, and RD180 mm). The RD90 mm and RD180 mm treatments exemplify manual driving deviations compared to using an RTK auto-steer guidance system (RD0 mm). Higher yields and higher net returns resulted from using the RTK auto-steer guidance system. Data showed that for every 20 mm row deviation, an average of 186 kg ha-1 yield loss can be expected. Overall, yield was higher for the conventional tillage and twin row pattern treatments compared to the other treatments. Yield losses for the SR-CT treatment were higher as the row deviation increased compared with the TWR-CT treatment. In contrast, higher yield losses for TWR-ST compared to SR-ST were observed when deviations of 180 mm occurred instead of digging using the RTK auto-steer guidance system. While a farmer using an RTK auto-steer guidance system with an accuracy within 25 mm (RD0 mm treatment) could potentially expect additional net returns of between 94 and 404 $ ha-1 compared to those from row deviations of 90 mm, higher net returns of between 323 and 695 $ ha-1 could be perceived if the guidance system is used instead of B. V. Ortiz (&) E. van Santen Department of Agronomy and Soils, Auburn University, 257 Funches Hall, Auburn, AL 36849, USA e-mail: [email protected] K. B. Balkcom D. L. Hartzog Wiregrass Research and Extension Center, P.O. Box 217, Headland, AL 36845, USA L. Duzy National Soil Dynamics Laboratory, USDA-ARS, 411 S. Donahue Dr., Auburn, AL 36832, USA

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having row deviations of 180 mm. Therefore, the use of RTK auto-steer guidance system will allow growers to capitalize on the increases in yield potential by implementing changes in tillage and row patterns as those evaluated in this study. Keywords Auto-steer guidance Autoguidance system Digger GPS Harvest Peanut Row pattern Tillage

Introduction The use of guidance systems aided by global positioning systems (GPS) for ground-based equipment in agriculture started in the United States (US) around the mid 90’s with 5 % adoption on all custom fertilizer and pesticide application equipment by 1999 (LowenbergDeBoer 1999). The advantage of using GPS guidance systems for agricultural operations, such as planting, spraying, fertilizer spreading, tillage, and harvest, has resulted in substantial economic and environmental benefits. Adopters of guidance systems have realized significant benefits in a number of areas. Griffin (2009) suggests that using automated steering guidance with a base station real time kinematic (RTK) GPS that provides centimeter accuracy (±1 cm) to control vehicle traffic on farmers’ fields can result in net returns for using RTK auto-steer guidance technology of up to 42.42 $ ha-1. Increased crop yields have been attributed to the use of GPS-guidance for strip tillage operations (Taylor et al. 2008; Bergtold et al. 2009), planting (Bergtold et al. 2009), optimum input placement (Griffin et al. 2008) and establishment of controlled-traffic patterns, which results in a reduction of compaction problems (Watson and Lowenberg-DeBoer 2003). Reduction in fuel consumption have been also reported (Schimmelpfennig and Ebel 2011). Today, guidance system adoption on US planted areas for corn and soybeans is in the range of 15–35 % (Schimmelpfennig and Ebel 2011). In 2009, 56 % of custom service operators used a GPS auto-steer guidance system for at least some of their work, representing a 100 % increase as compared to adoption in 2008 (Whipker and Akridge 2009). Adoption rates for various precision agriculture technologies (PAT) differ across regions in the US. For example, in cotton production, the use of PAT is higher than the national average in the Delta States, but is lower in the Southern Plains, Southeast and Appalachia (Schimmelpfennig and Ebel 2011). Contrasting with that is the data from a survey conducted in Alabama in 2009 which indicated that 60 and 40 % of Alabama and Florida farmer-respondents, respectively, used light bar guidance. The same survey showed that 27 % of Alabama and 40 % of Florida respondents were using automated guidance in 2009 and 40 % intend to use RTK auto-steering guidance in the next 2 years (Winstead et al. 2010). Factors that influence the adoption of PAT are the economic value of the crop, the farm size and the level of education of the producers (Griffin et al. 2005; Griffin 2009; Paxton et al. 2010). Therefore, peanuts (Arachis hypogaea L.) seem to be a good candidate for increased PAT usage. Peanuts are produced mainly in the Southeast US (Alabama, Florida, Georgia, Mississippi and South Carolina), with 67 % of US production coming from the states of Georgia and Alabama. In Alabama, the production area has expanded from the traditional planting region in the southeast [94 % of the total production in 1998 (U.S. Department of Agriculture—National Agricultural Statistics Service 2000)] to nontraditional areas in central and southwestern Alabama [15 % of the total production in 2009 (U.S. Department of Agriculture—National Agricultural Statistics Service 2010)]. The expansion towards non-traditional peanut production areas, in addition to the increased number of new producers, has partly influenced producers’ decisions to adopt new

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technologies, such as GPS-based autoguidance systems, in order to improve operations efficiency and reduce the risk for yield losses. The use of guidance systems by peanut producers may have greater benefits than for other row crop producers. Peanuts develop in the soil and are harvested by digging them from the ground with a digger-shaker-inverter, letting them partially dry in the field before being harvested. Therefore, peanuts can be left in the ground if the tractor driver deviates from the peanut row resulting in higher risk for yield losses. Before the introduction of GPS-based autoguidance systems, peanut producers relied on skilled tractor operators to plant and then accurately harvest peanuts. However, producers today are growing high leaf biomass varieties, some of which have green vines at harvest; therefore, inexperienced tractor operators find it difficult to keep the peanut digger positioned over the target rows, covered either by peanut leaf biomass or crop residue (Balkcom et al. 2010). Peanuts in the southeast US are grown on sandy Coastal Plain soils, which are coarse textured with poor structure, and compact naturally during the course of the year (Radcliffe et al. 1988; Bergtold et al. 2009). Therefore, in-row subsoiling or strip tillage is used to reduce compaction and to avoid subsequent yield losses. In addition, strip tillage has shown promising results on reducing disease incidence of leaf spot, Tomato Spotted Wild Virus (TSWV) and white mold (Cantonwine et al. 2006, 2007; Culbreath et al. 1999). Strip tillage in peanut production consists of planting a winter annual cereal cover crop, chemically terminating the cover crop in the spring, and using an in-row subsoiler with coulters and baskets (Balkcom et al. 2010). At planting, producers plant the peanuts over the loosened zone created during the strip tillage operation; however, it can be difficult due to the small area disrupted in the soil profile and the high residue present on the soil surface. Hence, tractors equipped with GPS-based autoguidance can provide the accuracy needed to conduct in-field operations maximizing the benefits of subsoiling operations (Raper et al. 2008). Based on the results from a cotton experiment, Bergtold et al. (2009) showed that as the distance between the planted row and the tillage pass increased, seed cotton yield decreased 24–52 % and net revenues from cotton production decreased 38–83 %. They also concluded that the profitability of RTK-GPS auto-steer guidance systems was dependent on driver accuracy, as well as the size of the agricultural operation. For example, RTK-GPS auto-steer guidance systems were profitable for larger farms (approximately 500 ha) when the accuracy of the driver was off by more than 100 mm (Bergtold et al. 2009). Besides the advantage of using GPS-based autoguidance systems in peanut production using strip tillage, changes in row configuration from a single row to a twin-row pattern can be used as an alternative to control TSWV and Stem Rot diseases (Culbreath et al. 2008; Sconyers et al. 2007), as well as thrips (Cantonwine et al. 2006). A twin-row configuration could be easily adopted through the use of guidance systems. Most of the studies involving GPS-based guidance systems have focused on accuracy evaluation and factors impacting performance, such as changes of the terrain, travel speed and distance from the base station (Adamchuk et al. 2007; Stombaugh et al. 2007; Stombaugh and Shearer 2001). However, few studies have quantified yield benefits and economic return of using tractor guidance system. Raper et al. (2008) evaluated the use of tractors equipped with GPS-based guidance systems under Alabama cotton production conditions, and demonstrated that cotton planted within 50 mm of the in-row subsoil strip yielded 44 % more than cotton planted without subsoiling. The study also showed that the accuracy of in-row subsoiling and planting was only maintained with the use of an autoguidance system. Griffin (2009) also studied the impact of farm size related to the economic returns gained by using autoguidance and found that GPS guidance systems become more profitable as farm size increases.

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The objectives of this study were to determine the effect of deviations of the digger from the target row on peanut yield and quality, and to determine the economic value of using RTK GPS-based auto-steer guidance systems to avoid tractor deviations during peanut harvest. Additional consideration is given to the use of strip tillage, as opposed to conventional tillage, and a twin-row configuration, as opposed to a single row configuration.

Materials and methods Study field and experimental plan The study was conducted at the Wiregrass Research and Extension Center in Headland, Alabama (Latitude 31°210 N and Longitude 85°190 W) to evaluate the effect of digger drift associated with tractor deviations from the target row on peanut yield during the 2005–2007 growing seasons. The soil type at the location was a Dothan sandy loam (fineloamy siliceous, thermic Plinthic Kandiudult) with less than 2 % slope. Small straight-row plots, 3.6-m wide and 18-m long, were established in a randomized complete block design with four replications. The experimental plots were planted with the Georgia Green peanut cultivar in 2005 and the Ga O3L cultivar in 2006 and 2007. The treatments consisted of two tillage systems [conventional (CT) and strip tillage (ST)], two row configurations [single (SR) and twin row (TWR)], and three tractor deviations from the target row [no deviation (RD0 mm) and deviations of 90 mm (RD90 mm) and 180 mm (RD180 mm) off the target row] (Table 1). The RD90 mm and RD180 mm treatments were included as deviations that might result from manual driving compared to minimum or no deviation, where the tractor is equipped with a RTK GPS-based auto-steer guidance system. For this particular study, the two deviation treatments were implemented in the field through the use of a RTK auto-steer guidance system by setting the guidance system to drive 90 and 180 mm off the predefined AB line. The conservation tillage plots were planted with an oat (Avena sativa L.) cover crop in the fall of each year with a no-till drill seeded at 100 kg ha-1. Nitrogen fertilizer, at a rate of 33.63 kg ha-1, was applied to the cover crop at planting. The implements used for the tillage systems were a KMC Generation I Rip-Strips (Kelly Manufacturing Co., Tifton, GA, USA). The implements used for the conventional tillage system included a moldboard plow, disk and two passes with a KMC field cultivator. The conservation tillage implements included a four-row KMC strip till unit with four coulters behind the in-row sub-soil shank followed by a rolling basket and a drag chain. For this experiment, there was not a separation distance between the planted row and tillage pass. Single rows spaced 0.91 m apart (Fig. 1) were planted in both tillage systems with a John Deere 1700 XP MaxEmerge Plus (Deere & Co., Moline, IL, USA) vacuum planter equipped with a Dawn row cleaners (Dawn Equipment Co., Sycamore, IL, USA). The twin rows were planted in both tillage systems with a Monosem (Monosem Inc., Edwardsville, KS, USA) twin row planter that had a coulter mounted in front of each individual row. The twin-row pattern consisted of rows spaced 0.23 m apart on 0.91 m centers (Fig. 1). Individual plant populations for both single rows of the twin-row configuration corresponded to one half, 10 seeds m-1, of the single row configuration with 20 seeds m-1, to ensure the same population on both treatments. The tractor used for tillage, planting and digging was a John Deere 7810 MFWD tractor with a three-point hitch system for the implements. The tractor was equipped with a StarFire iTC receiver (12 Channel, dual-frequency differential GPS Receiver with integrated terrain compensation), a RTK radio, a GreenStar 2 screen

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Precision Agric (2013) 14:357–375 Table 1 List of abbreviations of used to identify the experimental treatments used throughout the manuscript

361

Abbreviation

Description

CT

Conventional tillage

RC

Row configuration

RD RD0

Row deviation mm

RD90

mm

RD180

mm

None row deviation Row deviation of 90 mm Row deviation of 180 mm

ST

Strip tillage

SR

Single row pattern

SR-CT

Single row-conservation tillage

SR-ST

Single row-strip tillage

T

Tillage

TWR

Twin row pattern

TWR-CT

Twin row-conventional tillage

TWR-ST

Twin row-strip tillage

Y

Year

and an integrated AutoTrac assisted steering kit. For differential correction a StarFire RTK signal was used, which provided accuracy within a range of 13–23 mm. The same base station for the correction signal was used for tillage, planting and digging operations. The middle two center rows from each plot were dug mechanically and inverted with a 2-row (1.8 m wide) KMC digger/inverter (Kelly Manufacturing Co., Tifton, GA, USA). The field where the experiment was conducted did not exhibit significant changes on terrain’s slopes, therefore, drift from the planter or digger due to terrain changes was minimal or none. The middle two rows of each plot were harvested and sacked with a 2-row Hustler peanut combine. The plot bags were dried to approximately 10 % moisture to determine yield and total sound mature kernels (TSMK). Economic analysis In order to calculate the net impact of tillage, row configuration, and deviations from the target row, net returns (NR) in $ ha-1 were evaluated between the treatments. The NR were calculated using a partial budgeting approach of the form: NRijk ¼ DGijk R þ L Pijk Cijk H Pijk where NRijk = net return in $ ha-1 for tillage treatment i, row pattern j and deviation from the target row k; DGijk = difference between average grade (72.93 percent) and grade for tillage treatment i, row pattern j and deviation from the target row k; R = 2 011 rate per percent for TSMK for segment 1 Runner type peanuts; Pijk = peanut yield in kg ha-1 for tillage treatment i, row pattern j and deviation from the target row k; L = 2 011 National loan rate in $ kg-1; Cijk = cost of machinery, fuel, and labor in $ ha-1 for tillage treatment i, row pattern j and deviation from the target row k; and H = yield based costs, such as cleaning, drying and marketing, in $ ha-1. A partial budgeting approach was utilized to calculate net return above costs of treatments since the remaining production costs were the same across treatments. The cost of machinery, fuel and labor (Cijk) includes only variable costs. Revenue was calculated from the US Department of Agriculture, Farm Service Agency’s 2011 CY loan rate and

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(a) Single row pattern 0.91 m

(b) Twin row pattern 0.23 m 0.91 m

Fig. 1 Diagram of row patterns consisting of: a Single row planting pattern with rows spaced 0.91 m apart, and b twin row planting pattern with rows spaced 0.23 m apart on 0.91 m centers

premiums (US Department of Agriculture–Farm Service Agency 2011), and production costs were based off of the 2012 University of Georgia Peanut Enterprise Budgets (University of Georgia 2012). Revenue and cost variables and values are shown in Table 2. The cost of production differed between treatments due to the difference in tillage and planting costs, and the cost of purchasing a RTK auto-steer guidance system. The variable costs of conventional tillage and strip tillage differ due to the type of machinery used for tillage, the number of passes with tillage implements and the establishment and termination of an oat cover crop as part of the strip tillage treatment. Statistical Analysis Data were analyzed using mixed models methodology as implemented in the SAS GLIMMIX procedure (SAS v. 9.3, SAS Institute, Cary, North Carolina, USA). Year (Y), tillage treatment (T), row configuration (RC), row deviation (RD) and their interactions

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Precision Agric (2013) 14:357–375 Table 2 Price and cost parameters and associated assumptions

363

Revenue National loan rate

$0.39 kg-1

Rate per percent TSMK

$0.0054 SMK percent-1 kg-1

Variable production costs Tillage treatments Conventional tillage

$110.98 ha-1

Strip-till (includes an oat cover crop)

$177.77 ha-1

Row-spacing treatments Single row

$27.68 ha-1

Twin row

$30.05 ha-1

RTK system treatments a

Yield based costs include the costs for cleaning, drying, and marketing. The National Peanut Board checkoff is not included. The yield based costs are assumed for a portion of the crop to account for differences between producers and are 33, 67, and 100 % for cleaning, drying, and marketing, respectively

Production area

500 acres

Price of RTK system

$33 250

Life span of RTK system

5 years

Interest rate

6.5 %

Total annualized costs for RTK Yield based costs

$39.54 ha-1

a

Cleaning

$0.013 kg-1

Drying

$0.033 kg-1

Marketing

$0.0033 kg-1

were treated as fixed effects. Block within years was the sole specified random effect and was used as the appropriate error term for years. The residual variance was used as the error term for all other fixed effects.

Results and discussion Peanut yield Monthly precipitation anomalies, average maximum and minimum temperatures changes and soil temperature at 1 m depth during the 2005–2007 growing season for the study site are illustrated in Fig. 2. Precipitation anomalies were calculated using the 30-year monthly average precipitation. In 2005, above average precipitation was observed for the months of April, June and August, which contrasts with the lower precipitation, with respect to the historic average, in 2006 and 2007 for the months of May, June, July and August. Maximum temperature from May to August in 2006 and 2007 was higher compared with 2005. Significant differences in minimum temperature during the months of May to August were not observed between the years. Average peanut yields for 2005, 2006 and 2007 were 3956, 4042 and 2612 kg ha-1 respectively, when averaged across tillage (T), row configuration (RC) and row deviation (RD) treatments. Peanut yield tended to decrease from 2006 to 2007, probably as a result of the decreased precipitation during the early establishment to the primary reproductive activity period (Fig. 2). The higher yield during 2005 and 2006 as compared to 2007 can possibly be explained by the higher soil temperatures during the months of May and June in 2005 and 2006. Rowland et al. (2007) attributed better pod development and higher

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Precipitation Anomaly (mm)

150 100 50 0 -50 -100

2005

-150

Apr

May

Jun

2006 Jul

2007 Aug

Sep

Oct

Nov

40

Temperature ( oC)

35 30 25 20 15

Max. Temp. Min. Temp

10

2005 2005

2006 2006

2007 2007

5 Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Soil Temp. ( oC) - 10 cm depth

40 38 36 34 32 30 28 26 24

2005

22

2006

2007

20 M

J

J

A

S

O

N

Fig. 2 Average weather patterns for the 2005, 2006 and 2007 growing seasons

yield to increased soil temperatures during the period from planting to the start of the reproductive activity. The analysis of variance showed significant yield differences for the main effects of Y, T, RC, and RD and those accounted for 46, 7, 3 and 34 % of the fixed effects variation, respectively (Table 3). Among the interactions with the RD factor, the four-way interaction (P = 0.007), T 9 RC 9 RD (P = 0.079) and Y 9 T 9 RD (P = 0.016) were of interest. Peanut yield by row deviation level averaged across years, tillage and row configuration treatments showed a ranking of RD0 mm [ RD90 mm [ RD180 mm (Fig. 3). A linear regression model fitted to the data indicated that every two centimeters deviation of the tractor-digger from the center of the row will result in 186 kg ha-1 loss in yield (data not shown).

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365

Table 3 Analysis of variance for peanut yield and total sound mature kernels from a tillage, row configuration and row deviation experiment conducted during the 2005–2007 growing seasons Source of variation

Numerator df

Peanut yield F value

Total sound mature kernels a

P value

F value

P value

Year (Y)

2

173.68

0.001*

68.68

0.001*

Tillage (T)

1

54.37

0.001*

12.24

0.001*

Y9T

2

6.66

0.002*

2.82

0.065**

Row configuration (RC)

1

23.58

0.001*

0.09

0.765

Y 9 RC

2

0.27

0.762

0.83

0.442

T 9 RC

1

3.32

0.072**

0.29

0.590

Y 9 T 9 RC

2

5.04

0.009*

2.37

0.100**

Row deviation (RD)

2

124.42

0.001*

2.92

0.060**

Y 9 RD

4

0.93

0.454

0.25

0.907

T 9 RD

2

0.74

0.482

0.12

0.889

Y 9 T 9 RD

4

3.26

0.016*

0.47

0.756

RC 9 RD

2

0.67

0.517

0.56

0.572

Y 9 RC 9 RD

4

1.43

0.231

1.48

0.216

T 9 RC 9 RD

2

2.62

0.079**

0.09

0.910

Y 9 T 9 RC 9 RD

4

3.79

0.007*

0.89

0.474

a

One or two asterisks (*) indicate statistical significance at the 0.05 or 0.1 confidence level, respectively

The interaction T 9 RC 9 RD is better explained by first discussing yield differences between T and RC factors separately (Table 4). Overall, peanut yield was significantly different between tillage treatments with pod yield under CT higher than ST every year of the experiment in spite of the significant Y 9 T interaction (P = 0.002). On the average, CT peanuts yielded 490 kg ha-1 more than ST peanuts (Fig. 4). These results agree with an average yield increase of 540 kg ha-1 in CT systems compared to ST reported by Jordan et al. (2001) and 348 kg ha-1 reported by Sorensen et al. (2010). Yield differences between RC treatments can be better explained by the significant interactions of T 9 RC (P = 0.072) and Y 9 T 9 RC (P = 0.009). The RC effect was the same for three-way interaction means; TWR yielded more than SR in all but one case (2005 ST). A similar trend was observed from the two-way interaction, where TWR yields were higher than SR yields; therefore, the RC effect is generalized at the main effect level. On the average, TWR out-yielded SR by 347 kg ha-1 (Fig. 5). Yield increments on TWR peanuts over SR peanuts have been previously reported from studies conducted in Alabama (Balkcom et al. 2010), Georgia (Sconyers et al. 2007; Culbreath et al. 2008; Tubbs et al. 2011) and North Carolina (Lanier et al. 2004). Lanier et al. (2004) attributed higher yield in twin row peanuts to a 20 % plant population increase per hectare compared with the single row planting. In contrast, Tubbs et al. (2011) attributed the increased yield of TWR peanuts to a wider in-row seeding space providing more room for the root to explore soil profile resources which results in a greater final stand than the SR pattern. Because of the significant yield differences between row configuration treatments, the impact of row deviation by tillage treatment, taking into account the row configuration, was analyzed by subtracting SR yield from TWR yield. The results showed that yield losses for the SR-CT treatment were higher as the row deviation increased compared to TWR-CT treatment (Table 4). Yield differences between SR and TWR treatments

123

4500

1400

4000

1200

3500 1000

3000 2500

800

2000

600

1500

400

1000

Net returns ($ ha-1)


Peanut Yield (kg ha -1)

366

200

500 0

0 0

90

180

Row deviation (mm)

Fig. 3 Peanut yield and net return differences between the row deviation treatments averaged across years, tillage and row configuration treatments Table 4 Peanut yield as influenced by tillage, row configuration and row deviation; average data from 2005 through 2007 Tillage

Row configuration

Row deviation (mm)a

Yield (kg ha-1)

Yield rank

Contrast P value vs. 9 cm

Conventional

Single

Twin

Strip

Single

Twin

18 cm

0

4 324

1

0.0010 \0.0001

90

3 664

2

\0.0001

180

2 692

3

0

4 639

1

0.0003 \0.0001

90

3 963

2

0.0083

180

3 444

3

0

3 690

1

0.0210 \0.0001

90

3 228

2

0.0009

180

2 629

3

0

4 074

1

0.0001 \0.0001

90

3 383

2

0.0002

180

2 711

3

a

The zero row deviation corresponds to digging peanuts using a RTK autoguidance system. The deviations of 90 and 180 mm were included as deviations that might result from manual driving

averaged 315, 299 and 752 kg ha-1 for the RD0 mm, RD90 mm and RD180 mm treatments, respectively (Table 4). Contrasting results were found for the ST treatment with average yield differences between SR and TWR of 384, 155 and 82 kg ha-1 for RD0 mm, RD90 mm and RD180 mm treatments, respectively. Results showed that under the SR-ST treatment, yield losses for each of the row deviation treatments were lower compared to the SR-CT treatment (Table 4). The impact of row deviation could be exacerbated when the crop develops under drought conditions such as in 2007. During 2007, yield losses increased from 52 % (SR-CT treatment) to 57 % (SR-ST treatment) when row deviations of 180 mm occurred as compared to digging using RTK auto-steer guidance (RD0 mm) (Table 5). The 2007 yield losses increased compared to the three-year average yield losses, especially for peanuts growing under conventional tillage conditions. The low precipitation and the elevated ambient temperatures observed in 2007 resulted in reduced soil moisture

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367

4000

P < 0.0001 -1

Peanut Yield (kg ha )

3500 3000 2500 2000 1500 1000 500 0 Conventional

Strip

Tillage

Fig. 4 Peanut yield differences between the tillage treatments 4000

1160

3500

1120

3000 1080

2500 2000

1040

1500

1000

1000

Net Returns ($ ha-1)

Peanut Yield (kg ha-1)

Fig. 5 Peanut yield and net returns ($ ha-1) for the two row configurations during the 2005–2007 growing seasons

960

500 0

920

Single

Twin

Row Pattern

conditions limiting digging operations and increasing yield losses when the digger was off the target row. Despite of the benefits of twin row planting patterns, the increased canopy closure under this management scheme can limit row visibility during the digging and inversion process compared to the standard single row pattern (Henning et al. 1982, Tubbs et al. 2011). The data reveals that yield losses occur if the tractor deviates during the digging process; however, this study also shows that inefficient digging and risk for losses can be minimized by the use of an RTK-based auto-steer guidance system (RD0 mm), which allows growers to capitalize on the increases in yield potential by implementing changes on tillage and row patterns as evaluated in this study. Percentage yield reduction was analyzed for the interaction T 9 RC 9 RD (Table 5). Under CT, lower yield losses for TWR peanuts compared to SR peanuts were found when the row deviation increased from 0 to 180 mm (Table 5). However, higher yield losses were observed for TWR-ST treatment compared to the SR-ST treatment for row deviations of 180 mm compared to digging using RTK auto-steer guidance (RD0 mm). Therefore, an understanding of the sources of increased yield risks when row deviation occurs is key for justifying the benefits of using RTK auto-steer guidance systems. Studies by Varnell et al. (1976) and Colvin et al. (1988) attributed yield loss under conservation tillage systems to seedbed preparation, shallow planting due to soil compaction in the planting zone and shallow root development. In contrast, yield increases have been found when peanuts are

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Table 5 Percentage yield reduction of peanuts dug from the row center respect to the digger drifted 90 and 180 mm off the row; averaged across the years Tillage

Row configuration Single

Twin

Row deviation (mm)a 180 vs. 0 90 vs. 0 Percentage yield reduction

180 vs. 0

90 vs. 0

Conventional

38

15

26

15

Strip

29

13

33

17

Conventional

52

31

47

28

Strip

57

19

18

11

2005–2007

2007

a

The zero row deviation corresponds to digging peanuts using a RTK autoguidance system. The deviations of 90 and 180 mm were included as deviations that might result from manual driving

planted on friable seedbed with some degree of surface tillage (Colvin et al. 1988; Grichar 2006). Adequate peanut seedbed preparation seems to be important not only for growth and yield but also at digging time. Jordan et al. (2001) reported that for peanut growers a higher digging efficiency is reached when peanuts are grown on elevated beds prepared under conventional tillage. Grichar (2006) reported problems with digging peanuts in a striptillage production system suggesting additional adjustments in digging equipment to increase efficiency. He explained that because peanuts in the strip-tillage system were planted flat compared with the other systems, the blades of the peanut digger were not able to penetrate far enough into the ground to dig all the peanut pods (Grichar 2006). The reduced digging efficiency on strip tillage reported by these various authors might explain the higher yield losses observed on the twin rows of this experiment compared to conventional tillage. Also, the results of this study showed that, as the digger deviated from the center of twin rows in the strip tillage system, many peanut pods could either be pulled off of the vine or left in the soil during the digging operation resulting in higher yield losses than conventional tillage (Table 5). Total sound mature kernels Differences in the percentage of TSMK (a measure of peanut quality represented by the sum of mature kernels and sound splits expressed as a percentage) were significant for the main effects of Y, T, RD and the interactions Y 9 T, Y 9 T 9 RC, and those accounted for 80.6, 5.3, 2.6, 2.5 and 2.1 % of the fixed effects variation, respectively (Table 3). Year and the Y 9 T interaction had a significant influence on TSMK, which implies that year to year climate variability had differing impacts on peanut quality. Independent of the treatments, peanut quality in 2006 decreased 6 % compared to 2005 and 2007 (data not shown). The lower quality observed in 2006 could be related to the reduction in rainfall compared to the historic average values for the months of June, July and August (Fig. 2). During those months, about 50 mm less precipitation was received compared to the historic values. Lamb et al. (1997) using 8 years of peanut records from the US south-eastern peanut-producing region found that low grades were associated with drought conditions

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369

76

1600 P = 0.001

P = 0.283

72

1400 1200 1000

P = 0.297

68

800 600

64

400

Net Return ($ ha-1)

Total Sound Mature Kernels (%)


200 60

0 Strip-tillage Conventional Strip-tillage Conventional Strip-tillage Conventional

2005

2006

2007

Fig. 6 Average Total sound mature kernels (% TSMK) and net returns ($ ha-1) by tillage treatment, 2005–2007. Net return values are presented with square dots

and poor seed germination under non-irrigation. Lamb et al. (2010) reported reductions of peanut grade of 6.5, 14.4 and 20 % for three years of a seven-year study when precipitation was lower than the historic average and irrigation was not supplemented. Analysis of the data over the 2005–2007 crop years indicated marginal differences in peanut quality associated with the row deviation (P = 0.065) with average % TSMK of 71.2, 70.3, and 71.1 for the RD0 mm, RD90 mm and RD180 mm treatments, respectively. No significant interactions involving the row deviation factor were observed. On average, over the three year period, % TSMK between tillage treatments were different with 1.65 % more TSMK under CT than ST but only significant differences in 2007 (P = 0.001). Figure 6 shows that the Y 9 T interaction (P = 0.065) was mainly the result of the low TSMK observed in 2006. These results agreed with Grichar (1998) who analyzed the long-term effect of tillage on peanut yield and quality and found that in three years of a ten year study, % TSMK was lower in a no-tillage system than a conventional system. When averaged over the ten-year period, conventional tillage plots produced a 3 % TSMK increase over the no-tillage plots. In contrast, the results from another study of Grichar (2006) showed that peanut grade was not affected by any tillage system. The Y 9 T 9 RC interaction (P = 0.10) shows that year to year differences were responsible for most of the variability and they was influenced mainly by the low grades in 2006 compared to other years. In 2005, TSMK were 1.5 % higher in TWR peanuts than SR peanuts, independent of the tillage treatment (Table 6). In 2006, even though the % TSMK was lower than in 2005 and 2007, TSMK was almost 1 % higher in TWR-ST peanuts than SR-ST peanuts. Contrasting results were observed in 2006 for ST peanuts and 2007 for CT peanuts. The higher % TSMK observed in TWR peanuts is consistent with previous research from Lanier et al. (2004), who reported increased % TSMK in twin rows compared with single rows or a narrow twin pattern, and Baldwin and Williams (2002), who evaluated runner market type cultivars. Net returns analysis The main effects for Y, T, RC and RD accounted for 44, 15, 3 and 26 % of the fixed effects variation, respectively (Table 7). Even with the significant interaction Y 9 T (P = 0.000), economic net returns were higher for CT than ST in each of the three years, which generated an average economic net return of 239 $ ha-1. The effects on net returns of the three row deviations at digging time for various tillage and row configuration treatments

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370


Table 6 The average treatment effects of year, tillage, and row configuration on total sound mature kernels (TSMK) Year/tillage

Row configuration

TSMK (%)

Standard error

Rank TSMK

Contrast P value

Strip

Single

71.8

0.61

2

0.579

Strip

Twin

72.2

0.58

1

Conventional

Single

72.3

0.61

2

Conventional

Twin

72.9

0.61

1

Strip

Single

67.1

0.55

2

Strip

Twin

67.8

0.55

1

Conventional

Single

68.8

0.58

1

Conventional

Twin

67.3

0.55

2

Strip

Single

71.8

0.66

1

Strip

Twin

70.8

0.64

2

Conventional

Single

73.5

0.68

2

Conventional

Twin

73.7

0.64

1

2005

0.503

2006 0.316 0.047

2007 0.274 0.875

are provided in Tables 8 and 9 and illustrated in Figs. 3, 5, and 6. Net return associated with the row deviation effect resulted in a similar trend to yield. Net returns decreased with an increase in the row deviation from the center of the row (Fig. 3). Averaged across all three years, the two tillage treatments and the two row configuration treatments, RD90 mm, as compared to the minimum deviation reached with the RTK auto-steer guidance system (RD0 mm), resulted in a decreased net return of 185 $ ha-1, while RD180 mm decreased net returns by 410 $ ha-1 (Fig. 3). Assuming peanut prices of 0.66 $ kg-1, this equates to 280 and 620 kg ha-1 of peanuts, respectively. Figure 5 displays the difference in net returns between SR and TWR treatments across all years, tillage and row deviation treatments. On average, net returns were lower by 104 $ ha-1 for SR configuration, as compared to a TWR configuration. Across all years, economic returns were highest with CT, which generated an average net return of 256 $ ha-1 more than ST. This is due primarily to the cost of planting and managing the cover crop, including seed and fertilizer costs. The tradeoff in digging accuracy between manual guidance (RD90 mm and RD180 mm) and RTK auto-steer guidance (RD0 mm) are illustrated in Tables 8 and 9. By using a RTK auto-steer guidance system that can provide accuracy within 25 mm (RD0 mm) for digging peanuts, a farmer could potentially expect net returns within the range of 94 $ ha-1 to a maximum of 404 $ ha-1 (Table 8) above net returns for RD90 mm depending on the tillage treatment and year. Moving from RD90 mm to deviations of less than 25 mm by using RTK auto-steer guidance system to maintain digging on the center of the row (RD0 mm), increased net returns by 194, 197 and 118 $ ha-1 in 2005, 2006 and 2007, respectively, under strip tillage conditions, and increased net returns by 94, 101 and 404 $ ha-1 in 2005, 2006 and 2007, respectively, under conventional tillage conditions (Table 8). Higher economic returns were also observed when the RTK auto-steer guidance system was used rather than row deviations of 180 mm (RD180 mm) resulting from manual guidance. The use of RTK auto-steer guidance (RD0 mm) to minimize row deviations resulted in increased net returns between 323 and 695 $ ha-1 above net returns to RD180 mm. The increased net return of 695 $ ha-1 observed in 2007 for the CT-RD0 mm

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Precision Agric (2013) 14:357–375 Table 7 Analysis of variance for net returns from a tillage, row configuration and row deviation experiment conducted during the 2005–2007 growing seasons

a

One or two asterisks (*) indicate statistical significance at the 0.05 or 0.1 confidence level, respectively

Table 8 Differences in net returns ($ ha-1) from peanut production under two tillage scenarios for various row deviations at digging time

371

Source of variation

Numerator df

Net return F value

P valuea \0.001*

Year (Y)

2

100.7

Tillage (T)

1

89.5

\0.001*

Y9T

2

10.3

\0.001* \0.001*

Row configuration (RC)

1

14.8

Y 9 RC

2

0.2

0.846

T 9 RC

1

2.4

0.128

Y 9 T 9 RC

2

4.1

0.019*

Row deviation (RD)

2

77.3

\0.001*

Y 9 RD

4

1.4

0.233

T 9 RD

2

1.4

0.248

Y 9 T 9 RD

4

2.2

0.076**

RC 9 RD

2

0.6

0.576 0.413

Y 9 RC 9 RD

4

1.0

T 9 RC 9 RD

2

2.4

0.096**

Y 9 T 9 RC 9 RD

4

2.9

0.026*

Year/tillage

Net return difference ($ ha-1) Row deviation (mm)a Difference between 0 and 90

Difference between 0 and 180

2005 Strip Conventional

197

414

94

356

2006 a

The zero row deviation corresponds to digging peanuts using an RTK autoguidance system. The deviations of 90 and 180 mm were included as deviations that might result from manual driving

Strip

194

323

Conventional

101

339

2007 Strip

118

331

Conventional

404

695

treatment compared to CT-RD180 mm treatment was associated with a 49 % yield loss observed on the CT-RD180 mm in 2007, which considerably exceeds the 23 % yield loss observed for the same treatment in 2005 and 2006. Since significant differences for the treatment combinations Y 9 T 9 RC 9 RD were observed (P = 0.026), the impact on net returns of using the RTK auto-steer guidance systems in peanut production is discussed for four T 9 RC management scenarios by year and averaged over all years (Table 9). As expected, net returns for the RTK auto-steer guidance system (RD0 mm) treatment are higher than the net returns for the RD90 mm treatment and the RD180 mm treatment across all years, tillage types and row configurations (Table 9). When analyzing the four T 9 RC management scenarios, the results are similar; however, the magnitudes differed by year. For conventional tillage, across all years, TWR

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372


Table 9 Net returns ($ ha-1) from peanut production under two tillage scenarios, two row configurations for various row deviations at digging time in 2005, 2006, and 2007 and averaged over all years Year/row deviation (mm)a

Tillage Conventional

Strip

Row configurations Single $ ha-1

Twin

Single

Twin

0

1 425

1 600

1 176

1 419

90

1 323

1 515

1 121

1 080

919

1 394

1 024

744

0

1 435

1 432

1 258

1 449

90

1 282

1 383

1 118

1 197

992

1 193

1 022

1 034

2005

180 2006

180 2007 0

1 288

1 321

715

677

90

875

927

554

604

180

566

654

189

542

0

1 383

1 451

1 050

1 182

90

1 160

1 275

931

960

826

1080

745

773

Average across all years

180 a

The zero row deviation corresponds to digging peanuts using an RTK autoguidance system. The deviations of 90 and 180 mm were included as deviations that might result from manual driving

produced net returns equal to or higher than the net returns produced by SR, regardless of row deviation. When comparing SR-CT with SR-ST, across all years, the SR-CT peanuts harvested with RTK auto-steer guidance exhibited larger net returns than SR-ST peanuts, and net returns increased when RTK auto-steer guidance system was compared against RD90 mm and RD180 mm. For TWR, net returns, on average, were higher when a RTK auto-steer guidance system was used for digging CT peanuts than ST peanuts (Table 9) with one exception. In 2006, net returns for TWR-ST were higher by 16 $ ha-1 than net returns for the TWR-CT. This might be explained by a yield increase of 69 kg ha-1 on the TWR-ST plots. In 2006, precipitation decreased during the early establishment to the primary reproductive activity period (Fig. 2), therefore; a probable soil moisture content increase on the strip tillage plots could favor better peanut development resulting in higher yield and net returns. The 2007 conventional tillage data highlights how critical it is to use RTK auto-steer guidance systems during digging operations, especially when drought conditions have reduced the yield potential. Manual driving after a dry season might exacerbate yield losses. For example, for the single row configuration under conventional tillage, yield losses were 31 % (RD90 mm) and 52 % (RD180 mm) and net returns were 47 % (RD90 mm) and 128 % (RD180 mm) lower than with the use of RTK auto-steer guidance. This equates to an increase in net returns of 413 $ ha-1 (RD90 mm) and 722 $ ha-1 (RD180 mm) for the RTK auto-steer guidance treatment. Moving from a RD180 mm to an RTK auto-steer

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373

guidance system, the potential average increase in net revenues could be as high as 41 % for SR-ST and 53 % for TWR-ST. More specifically, in 2005 and 2006, there were significant net return increases from using RTK auto-steer guidance system for digging TWR/ST peanuts. Moving from a RD90 mm to an RTK auto-steer guidance system in the TWR/ST peanuts treatment increased net returns by 339 and 252 $ ha-1 in 2005 and 2006, respectively. When the RTK auto-steer guidance treatment (RD0 mm) was compared to the manual guidance (RD180 mm) treatment, net returns for the TWR-ST treatment increased by 90 % in 2005 and by 40 % in 2006.

Conclusions The use of the RTK auto-steer guidance system to achieve a precise implement position control during digging operations favored in higher peanut yields and higher net returns, as compared to tractor deviations resulting from manual guidance. This study showed that, independent of the tillage and row pattern practices used by the peanut farmer, yield losses increased and net returns decreased as the tractor-digger deviates from the target row, with yield losses up to 186 kg ha-1 expected for every two centimeter row deviation. Overall, peanut yield under conventional tillage was 490 kg ha-1 higher than strip tillage with twin rows yielding more than 347 kg ha-1 over single rows. Under conventional tillage, yield losses from single rows were higher as the row deviation increased compared to the twin row pattern. Yield differences between single and twin row treatment averaged 315, 299 and 752 kg ha-1 for digging scenarios of RTK auto-steer guidance usage (RD0 mm) and manual guidance with hypothetical row deviations of 90 and 180 mm, respectively. When row deviations of 180 mm occurred compared to the proper implement position by the RTK autoguidance system, lower yield losses for twin row under conventional tillage with respect to the single row peanuts were observed. This small yield loss could be explained by the higher twin row yields which compensate for row deviations at digging time. The use of a RTK auto-steer guidance system not only resulted in minimized yield losses but also increased net returns. By using a RTK auto-steer guidance system proving accuracy within 25 mm (RD0 mm) for digging peanuts, a farmer could potentially expect net returns between 94 and 404 $ ha-1 higher than with row deviations of 90 mm and net returns between 323 and 695 $ ha-1 higher if row deviations of 180 mm are avoided, given the peanut prices and costs of production considered in this study. Higher economic benefits of using RTK auto-steer guidance systems to harvest single row peanuts under conventional tillage were observed with respect to strip tillage conditions. The results also provided evidence that higher yield and net returns can be achieved if row deviations are minimized by the RTK auto-steer guidance system when peanuts are grown under drought conditions. In summary, this study showed the benefits of using RTK auto-steer guidance systems on peanut production, with the potential for greater benefits from the implementation of management practices such as twin row patterns. Acknowledgments This work was supported by grant funds from the National Peanut Board (NPB).

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