Patent Application
20210204471
Implementations relate to plant growth characterization using specialized field plots and associated techniques. Particular implementations involve the characterization of hybrid corn varieties in different growing conditions using modular field plots.
Vast expansion in the diversity of genetically distinct field crops has provided growers with a large selection of plant seeds to choose from. Selecting the varieties most suitable for a particular set of growing conditions can be difficult, a decision often hampered by the lack of data specific to the growing conditions faced by a particular grower. The effectiveness of fertilizers, fungicides and/or pesticides may also vary with respect to different hybrid varieties, resulting in widespread waste of such additives. Accordingly, many variables impact plant growth, and identifying which plants, of many, will succeed in a particular location, remains elusive.
Implementations provide modular field plots and associated techniques configured to systematically evaluate a large assortment of plant varieties subjected to a wide range of growing conditions. Embodiments include customizable field plots and high-throughput methods for characterizing plant hybrids in different growing conditions. Such conditions can encompass environmental factors, including temperature, soil type, and/or precipitation, for example, and also agricultural factors, including levels of applied nitrogen, plant population density, fungicide application, and/or crop rotation schemes, just to name a few. The field plots can be grown and evaluated in multiple geographic locations to uncover regional differences in crop production responsive to each of the variables tested. Disclosed plant characterization processes are thus designed to distinguish genetic hybrid varieties with respect to a wide range of practical factors frequently confronted by growers looking to improve efficiency and optimize yield.
In accordance with principles of the present disclosure, a method of characterizing distinct plant varieties can involve planting the plant varieties in one or more field plots. Each field plot may include one or more crop rotation zones, one or more maturity zones within the rotation zones, one or more nitrogen exposure zones within the maturity zones, and one or more population zones within the maturity zones. The method can further involve extracting growth data from the plant varieties after a growing period.
In some examples, the crop rotation zones comprise a continuous planting zone within which a single plant species is planted in consecutive growing seasons. In some embodiments, the crop rotation zones comprise a rotating zone within which a single plant species is not planted in consecutive growing seasons. In some examples, the maturity zones each include plants having a distinct age-to-maturity ranging from 80 to 120 days. In some embodiments, the nitrogen exposure zones include at least one high nitrogen zone and/or at least one low nitrogen zone. In some examples, the population zones include at least one high population zone and/or at least one low population zone. In some embodiments, the high population zone includes about 35,000 to about 40,000 plants per acre and the low population zone includes about 20,000 to about 30,000 plants per acre. In some embodiments, each field plot includes 9 maturity zones, each maturity zone comprising 2 subplots, each subplot comprising a nitrogen exposure zone and a population zone. In some examples, each subplot includes about 15 to about 30 distinct plant varieties, inclusive. In some embodiments, each plant variety comprises a hybrid of a same species. In some such examples, the same species comprises corn. In some examples, each of the distinct plant varieties is planted in replicate within each subplot. In some embodiments, the field plots are duplicated in two or more distinct geographical locations. In some examples, the growth data comprises average yield data.
In accordance with principles of the present disclosure, a system for characterizing distinct plant varieties includes one or more field plots. Each field plot may include one or more crop rotation zones, one or more maturity zones within the rotation zones, one or more nitrogen exposure zones within the maturity zones, and one or more population zones within the maturity zones. The system can further include a database configured to store growth data extracted from the plant varieties after a growing period.
In some examples, the crop rotation zones comprise a continuous planting zone within which a single plant species is planted in consecutive growing seasons and a rotating zone within which a single plant species is not planted in consecutive growing seasons. In some embodiments, the maturity zones each include plants having a distinct age-to-maturity ranging from 80 to 120 days. In some examples, the nitrogen exposure zones include at least one high nitrogen zone and/or at least one low nitrogen zone. In some embodiments, the population zones include at least one high population zone comprising about 35,000 to about 40,000 plants per acre and at least one low population zone comprising about 20,000 to about 30,000 plants per acre. In some examples, each field plot includes 9 maturity zones, each maturity zone comprising 2 subplots, each subplot comprising a nitrogen exposure zone and a population zone.
Each of the field plots disclosed herein comprise a unitary tract of arable land used in agricultural operations at a particular geographic location. Each field plot includes an adjustable, modular design configured to evaluate a variety of plant hybrids under different growing conditions. The field plots and associated methods can be employed to evaluate the performance of an assortment of plants and determine the impact of different agronomic practices on crop production. As a result, optimized placement of certain plant types can be determined and communicated to growers. Each field plot can be utilized to evaluate a plurality of variables, including crop rotation scheme, fertility treatment, plant population, irrigation, soil type and/or temperature with respect to a plurality of plant hybrids. The field plots and associated methods can be replicated in multiple geographic locations to expand the volume and scope of information derived therefrom. Embodiments can also involve systems configured to store, process and display such information in accordance with user instructions.
As used herein, the term “hybrid” may refer to plants created by crossing two genetically distinct parent plants. Methods of creating the hybrids, e.g., cross-pollination, may vary. While example methods described herein refer to the assessment of different corn varieties, it should be understood that reference to corn is for ease of illustration, only, and other plant species may also be evaluated according to principles of the present disclosure. For example, soybeans, alfalfa, barley, rice, and/or wheat varieties, among others, can also be evaluated.
The configuration of the first crop rotation zone 102 and second crop rotation zone 104 may vary. For example, the relative size of the zones may be switched, such that the first crop rotation zone 102 is smaller than the second crop rotation zone 104. In some embodiments, the first crop rotation zone 102 or second crop rotation zone 104 may be omitted, such that the entire field plot 100 includes only one crop rotation scheme.
Within the crop rotation zones 102, 104, the field plot 100 can include a plurality of maturity sets 106-122. Each maturity set defines an area of distinct age-to-maturity for the plants included therein. For corn, the age-to-maturity may be defined by the number of days between planting and physiological maturity, which may be defined as the age at which the kernel black layer forms at the tip of the kernels. The total age-to-maturity of each set may vary, ranging from about 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145 or 150 days or more, or any length of time therebetween, for example a range of about 80 to about 120 days, specifically. The intervals between consecutive maturity sets, defined as the difference in maturity age between two plant varieties, included in a particular field plot may also vary, ranging from about 1 to about 20 days, about 2 to about 15 days, about 3 to about 10 days, about 4 to about 8 days, or about 5 days in various examples. The number of distinct maturity sets, each set defined by a unique age-to-maturity, included in a single trial can also vary, ranging from 1 to about 20 or more, about 2 to about 18, about 4 to about 16, about 6 to about 14, about 8 to about 12, or about 9. In the embodiment shown, maturity sets 106, 112 and 118 each define maturity ages of 110 days. Maturity sets 108, 114 and 120 each define maturity ages of 105 days. Maturity sets 110, 116 and 122 each define maturity ages of 100 days.
As further shown in
The subplots may also vary with respect to plant population, ranging from high population to low population. Populations may be based on stress and/or yield levels. For example, geographic locations that typically experience lower levels of stress, e.g., rarely experiencing drought and/or excessive heat, may include high-population subplots planted with, for example, about 30,000 to about 40,000 plants per acre, or any value therebetween. By contrast, geographic locations that typically experience higher levels of stress in the form of drought and/or excessive heat, may include low-population subplots planted with, for example, about 20,000 to about 30,000 plants per acre, or any value therebetween. In the example shown, high population subplots include 38,000 plants per acre, and low population subplots include 30,000 plants per acre.
The particular arrangement of different growing conditions and/or maturity sets may vary in different examples. In the specific example shown, subplots 106a, 108a, 110a, 112a, 114a and 116a comprise high population, high nitrogen subplots. Subplots 106b, 108b, 110b, 112b, 114b and 116b comprise low population, high nitrogen subplots. Subplots 118a, 120a and 122a comprise high population, low nitrogen subplots, and subplots 118b, 120b and 122b comprise low population, low nitrogen subplots. Accordingly, the field plot 100 shown in
Management schemes can be adjusted each growing season by modifying the conditions applied within each subplot. In some examples, growers utilizing the field plot 100 may specify a customized management scheme for application to one or more user-selected hybrids. Users may also specify one or more hybrids to be tested in one or more growing seasons under one or more of the 6 management schemes represented in
In some embodiments, additional management schemes may be implemented by adding one or more maturity sets containing one or more subplots defined by at least one different growing condition. For example, growing conditions may include fungicide exposure, ranging from high fungicide to low fungicide. Additional growing conditions can include herbicide and/or pesticide exposure, irrigation level, and/or sunlight exposure.
Each subplot defined by distinct growing conditions within the field plot 100 can include hybrid replicates to improve the statistical significance of the data gleaned from the field plot. For example, maturity set 106 includes a first pair of subplots 106a and a second pair of subplots 106b. This represents two identical sets of hybrid plant varieties within each management scheme. The arrangement of hybrid replicates shown in
The number of distinct hybrid varieties included in each maturity set may vary. The maturity set 112 includes 30 distinct hybrids, while other maturity sets may contain fewer, e.g., 15 hybrids, or more, e.g., 45, hybrids. For example, maturity sets defining ages-to-maturity of 80 and/or 120 days may each include 15 distinct hybrids, while all other maturity sets may contain 30 distinct hybrids. According to such embodiments, a single field plot, such as field plot 100, can evaluate up to about 240 distinct hybrids.
In embodiments, the growth data 304 may be gathered from multiple field plots 302, including field plots located at different geographic sites. For example, the growth data 304 may be local, regional, national or international. Local growth data may reflect a small number of field plots, e.g., 1, 2, or 3 field plots, clustered in the same, or nearly the same, location. Regional growth data may encompass growth data averaged between sites spread across southern, western, west central, east central, eastern, and/or northern regions of the United States, for example. Regional growth data may also encompass data gathered from field plots located in individual states. National growth data can include data averaged from two or more distinct regions or data averaged from all sites including at least one field plot within the United States. An end user may specify the geographic scope of data collected for a particular plant variety, thereby enabling the user to view local, regional, national and/or international averages for a particular trait, e.g., yield, for a particular plant variety.
In addition or alternatively, the growth data 304 can be stratified according to soil texture. For example, distinct soil textures may include coarse, medium and fine. Coarse soil may include sand, loamy sand and/or sandy loam. Medium soil may include loam, silt loam and/or silt. Fine soil may include sandy clay loam, silty clay loam, clay loam, sandy clay, silty clay and/or clay. Within each soil texture, the growth data 304 can be further categorized based on irrigation scheme.
After all growth data 304 is collected, field plots may be grouped according to overall averages for each field plot location. In some examples, the growth data 304 may be grouped according to average yield. For instance, the growth data 304 may be used to identify low yield environments (less than about 130 bushels/acre), moderate yield environments (about 130-180 bushels/acre), and high yield environments (greater than 180 bushels/acre). Cutoffs for the various yield environments can be adjusted based on the distribution of yield averages. Accordingly, low yield environments may include average yields of about 110 to about 150 bushels/acre, moderate yield environments may include average yields of about 120 to about 200 bushels/acre, and high yield environments may include average yields of about 160 to about 220 bushels/acre. Growth data 304 may additionally or alternatively include data regarding plant height, kernel number, leaf size, ear prolificacy, etc.
Due to the different management schemes evaluated within each field plot, the growth data 304 can also be utilized to determine each plant variety's response to one or more growing conditions. The average yield data for subplots subjected to the same condition with respect to a variable can be subtracted from the average yield data for the subplots subjected to the opposite condition with respect to the same variable. For example, within a given field plot, each corn hybrid's response to nitrogen may be determined by adding the average yield data from the continuous corn, high nitrogen, high population management scheme and the continuous corn, high nitrogen, low population management scheme. From this sum, the average yield data from the continuous corn, low nitrogen, high population management scheme and the continuous corn, low nitrogen, low population management scheme may be subtracted. In this manner, plants exhibiting a strong increase in yield responsive to high nitrogen exposure can be distinguished from plants exhibiting a negligible or even negative response to high nitrogen exposure. Such data may be especially valuable for growers looking to fine tune fertilizer applications based on the hybrids' propensity to utilize those nitrogen inputs. Data indicative of one or more plants' response to nitrogen, crop rotation and/or population, for example, may be quantified in a “response-to score,” which may be higher for plants exhibiting a stronger response to a particular variable. The response-to score may be determined by the data processor 308 and communicated to an end user for display on the user interface 312.
In the embodiment shown, the method 400 begins at block 402 by planting the plant varieties in one or more field plots. As shown at block 402a, the field plots may include one or more crop rotation zones. As shown at block 402b, the field plots may include one or more maturity zones within the rotation zones. As shown at block 402c, the field plots may include one or more nitrogen exposure zones within the maturity zones. As shown at block 402d, the field plots may include one or more population zones within the maturity zones. The method 400 may continue at block 404 by extracting growth data from the plant varieties after a growing period.
As used herein, the term “about” modifying, for example, the quantity of a component in a composition, concentration, and ranges thereof, employed in describing the embodiments of the disclosure, refers to variation in the numerical quantity that can occur, for example, through typical measuring and handling procedures used for making compounds, compositions, concentrates or use formulations; through inadvertent error in these procedures; through differences in the manufacture, source, or purity of starting materials or components used to carry out the methods, and like proximate considerations. The term “about” also encompasses amounts that differ due to aging of a formulation with a particular initial concentration or mixture, and amounts that differ due to mixing or processing a formulation with a particular initial concentration or mixture. Where modified by the term “about” the claims appended hereto include equivalents to these quantities.
Similarly, it should be appreciated that in the foregoing description of example embodiments, various features are sometimes grouped together in a single embodiment for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various aspects. These methods of disclosure, however, are not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment, and each embodiment described herein may contain more than one inventive feature.
Although the present disclosure provides references to preferred embodiments, persons skilled in the art will recognize that changes may be made in form and detail without departing from the spirit and scope of the invention.
