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Farmers

Farmers are individuals who cultivate land or raise animals for the purpose of producing food, fiber, or other agricultural products.
They employ various techniques and technologies to optimize their farming operations, including the use of AI-driven research protocol optimization tools like PubCompare.ai.
This platform empowers farmers to easily locate relevant protocols from literature, preprints, and patents, and utilize smart comparisons to identify the best protocols and products for improved reproducibility and accuracy.
By boosting their farming research with PubCompare.ai, farmers can enhance the efficiency and productivity of their operations, leading to better outcomes for their crops and livestock.
Farmers play a crucial role in feeding the world's population and sustaining the global food supply.

Most cited protocols related to «Farmers»

1
Acceptability of Hand Hygiene Intervention for Newborns in Uganda
A total of 55 pregnant women of over 34 weeks’ gestation were recruited to the intervention arm of the BabyGel study, from 5 villages. These villages were situated around Busiu Health Centre IV in Mbale District, Eastern Uganda and were selected to represent a variety of distances from each other, market areas and from the health centres. Participants were taught to use the hand rub at certain moments in their daily routine, as defined by the ‘Newborn Moments for Hand Hygiene’ poster. This was made available to all those in the intervention arm as a laminated colour poster in English or the dominant local language Lumasaba. The participants were taught verbally to use the ABHR at the moments specified in the poster and were supported by Village Health Workers.
At the end of the 3-month neonatal period, mothers from the intervention arm were invited to attend a focus group discussion (FGD) to offer their opinion on the acceptability and feasibility of the educational poster and ABHR. All 55 women in the BabyGel study intervention group were invited to participate, regardless of their level of education or literacy. A total of 35 women agreed to participate. Five focus groups were conducted throughout March and April 2016, each consisting of 6–8 participants, as summarised in Table 1.

Demographics of FGD Participants

VillageNumber of participantsMean age of participant (range)
Namakye822.6 (18–30)
Bulwalasi Toma827.9 (19–37)
Namunyu627.5 (19–39)
Makhonje 1723.1 (19–30)
Makhonje 2630.3 (19–36)
Most participants were married and described their occupation as a housewife or peasant farmer. Most had only primary education. The typical house was made from mud with an iron sheet roof. Most had non-ventilated pit latrines without handwashing facilities.
The FGDs were arranged by telephone call during the participants’ 90-day follow-up survey. On the day of the focus group, a research assistant from the Sanyu Africa Research Institute (SAfRI) formalised the participants’ consent prior to the discussion.
Harrison B.L., Ogara C., Gladstone M., Carrol E.D., Dusabe-Richards J., Medina-Lara A., Ditai J, & Weeks A.D. (2019). “We have to clean ourselves to ensure that our children are healthy and beautiful”: findings from a qualitative assessment of a hand hygiene poster in rural Uganda. BMC Public Health, 19, 1.
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Publication 2019
Farmers Infant, Newborn Iron Mothers Pregnancy Pregnant Women Teaching Village Health Workers Woman
2
Demographic and Geographic Profile of Nouna HDSS
The Nouna HDSS covers a subset of the Nouna Health Districts with about 78,000 inhabitants in 2007, distributed over 1,756 km2 (Fig. 1). Full population censuses were conducted for the HDSS in 1992, 2000, and 2009. With about 23,500 inhabitants, the town of Nouna represented 30% of the HDSS population in 2007. Starting in 1992, the HDSS covered three CSPS within 39 villages for a population of 26,626. Additions to the HDSS include the town of Nouna and two villages in the year 2000 and 17 villages in the year 2004 for a current total of 58 villages (Table S1 in the supplementary data). In 2009, the health facilities consist of one hospital and 13 CSPS out of the 29 for the whole district. The HDSS represents roughly one-quarter of the Nouna Health District both in terms of surface and population. Although the Nouna HDSS population is not selected randomly from the population in Burkina Faso, key variables are comparable to those observed at the national level (Table 1), such that it is appropriate to generalise results from the Nouna area with appropriate caution.
The household is the basic survey unit and is defined as an independent socio-economic unit. Household members usually live in the same house or compound, pulling resources together to meet basic dietary and other vital needs under the authority of one person recognised as the head of the household. Individual members within the household can usually be related and identify themselves as belonging to the household.
The mostly rural population of the multi-ethnic Kossi province consists predominantly of subsistence farmers and cattle keepers. The region is a dry orchard savannah and has a sub-Sahelian climate with a mean annual rainfall of 796 mm (range 483–1,083 mm) over the past five decades. The main ethnic groups in the Nouna Health District are the Dafing, Bwaba, Mossi, Peulh, and Samo. The Dioula language serves as a lingua franca, permitting communication between the different ethnic groups (1 ).
There are clear urban–rural differences between Nouna town and the surrounding villages, although Nouna town is often described as semi-rural. The town of Nouna has a better infrastructure as well as easier and better access to the education and health system. It has developed rapidly over the last decade and has seen a major improvement in the access to transport, drinking water, electricity, and more recently mobile phones and the Internet.
Village population in 2007 ranged from 78 to 3,199 persons (mean: 944 persons; median: 735 persons). The distances from villages to health centres ranged from 0 to 34 km (average: 8.5 km; median: 8.0 km) with a median time needed to reach the nearest health facility on foot estimated at 75 minutes in the dry season and 90 minutes in the rainy season.
Sié A., Louis V.R., Gbangou A., Müller O., Niamba L., Stieglbauer G., Yé M., Kouyaté B., Sauerborn R, & Becher H. (2010). The Health and Demographic Surveillance System (HDSS) in Nouna, Burkina Faso, 1993–2007. Global Health Action, 3, 10.3402/gha.v3i0.5284.
Publication 2010
Cattle Climate Diet Electricity Ethnic Groups Farmers Foot Head of Household Households Rain Rural Population Tongue Vision
3
Longitudinal Birth Cohort Study of Environmental Exposures
The CHAMA-COS (Center for the Health Assessment of Mothers and Children of Salinas) project, a component of the Center for Children’s Environmental Health Research at the University of California, Berkeley, is a longitudinal birth cohort study of the effects of pesticides and other environmental exposures on the health of pregnant women and their children living in the Salinas Valley. Pregnant women entering prenatal care at Natividad Medical Center, a county hospital located in the town of Salinas, or at one of five centers of Clinica de Salud del Valle de Salinas (located in Castroville, Salinas, Soledad, and Greenfield) were screened for eligibility over 1 year between October 1999 and October 2000. Clinica de Salud del Valle de Salinas is a network of community clinics located throughout the Salinas Valley and serving a low-income population, many of whom are farm workers.
Eligible women were ≥ 18 years of age, < 20 weeks gestation at enrollment, English or Spanish speaking, Medi-Cal eligible, and planning to deliver at the Natividad Medical Center. Of 1,130 eligible women, 601 (53.2%) agreed to participate in this multiyear study. Women who declined to participate were similar to study subjects in age and parity but were more likely to be English speaking and born in the United States and less likely to be living with agricultural field workers. After losses due to miscarriage, moving, or dropping from the study before delivery, birth weight information was available for 538 women. We excluded from these analyses women with gestational or preexisting diabetes (n = 26), hypertension (n = 15), twin births (n = 5), or stillbirths (n = 3). We also excluded one woman for whom birth weight information was out of range (< 500 g). Eleven infants diagnosed with congenital anomalies at birth [International Classification of Diseases, 9th Revision (ICD-9; 1989 ) codes 740–759] were included in the final sample because their exclusion did not materially affect the results. The final sample size was 488. Written informed consent was obtained from all participants, and the study was approved by the institutional review boards.
Eskenazi B., Harley K., Bradman A., Weltzien E., Jewell N.P., Barr D.B., Furlong C.E, & Holland N.T. (2004). Association of in Utero Organophosphate Pesticide Exposure and Fetal Growth and Length of Gestation in an Agricultural Population. Environmental Health Perspectives, 112(10), 1116-1124.
Publication 2004
Birth Weight Care, Prenatal Child Childbirth Congenital Abnormality Diabetes Mellitus Eligibility Determination Environmental Exposure Ethics Committees, Research Farmers High Blood Pressures Hispanic or Latino Infant Low-Income Population Mothers Obstetric Delivery Pesticides Pregnancy Pregnant Women Spontaneous Abortion Twins Woman
4
Malaria Vector Dynamics in Uganda
Studies were carried out in Walukuba subcounty, Jinja District (00° 26′ 33.2″ N, 33°13′ 32.3″ E); Kihihi subcounty, Kanungu District (00°45′ 03.1″ S, 29°42′ 03.6″ E); and Nagongera subcounty, Tororo District (00°46′ 10.6″, N 34°01′ 34.1″ E) (Figure 1). Jinja is in the southeast region at an elevation of 1,215 m above sea level and the study site is peri-urban, close to a swampy area near Lake Victoria. The major malaria vector species here was Anopheles gambiae s.s. ten years ago [16 (link)], but it is now Anopheles arabiensis[17 (link)]. Kanungu is a rural area of rolling hills in western Uganda located at an elevation of 1,310 m above sea level, where farmers grow bananas, millet, rice, cassava, potatoes, sweet potatoes, tomatoes, maize, groundnuts, and beans. The main vector here is An. gambiae s.s.. Tororo is located in the eastern region at an elevation of 1,185 m above sea level in an area of savannah grassland interrupted by bare rocky outcrops and low-lying wetlands, where maize, rice, cassava, sweet potatoes, sorghum, groundnuts, soya beans, beans, and millet are cultivated. The major malaria vector species reported for the region are Anopheles gambiae s.s. and Anopheles funestus with small numbers of An. arabiensis[16 (link),18 (link)]. There are typically two rainy seasons in Uganda (March to May and August to October) with annual rainfall of 1,000-1,500 mm.
Kilama M., Smith D.L., Hutchinson R., Kigozi R., Yeka A., Lavoy G., Kamya M.R., Staedke S.G., Donnelly M.J., Drakeley C., Greenhouse B., Dorsey G, & Lindsay S.W. (2014). Estimating the annual entomological inoculation rate for Plasmodium falciparum transmitted by Anopheles gambiae s.l. using three sampling methods in three sites in Uganda. Malaria Journal, 13, 111.
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Publication 2014
Anopheles Anopheles gambiae Banana Cloning Vectors Farmers Lycopersicon esculentum Maize Malaria Manihot Millets Oryza sativa Potato, Sweet Rain Solanum tuberosum Sorghum Soybeans Wetlands
5
Comparative Analysis of Global Gut Microbiomes
A meta-analysis compared fecal samples collected from healthy individuals who were 3 years of age or older and included in the AGP data set to a previously published 16S rRNA V4 region data set that included healthy people living an industrialized, remote agrarian, or hunter-gatherer lifestyle (6 (link), 11 (link), 12 (link)). The AGP subset of healthy individuals was determined by filtering by the metadata columns “subset_antibiotic,” “subset_ibd,” and “subset_diabetes” and, for individuals over the age of 16 years, “subset_bmi.” All data sets were processed using the Deblur pipeline as noted above, with the exception that all reads in the meta-analysis, including AGP data, were trimmed to 100 nt to accommodate the read length in the work of Yatsunenko et al. (6 (link)). Bloom reads as described above were removed from all samples. We used Striped UniFrac as noted above to estimate beta-diversity (unweighted UniFrac) and EMPeror software (66 (link)) version 0.9 to visualize principal coordinates. We used a nonparametric PERMANOVA with 999 permutations to test for significant differences in fecal microbiomes associated with industrialized, remote agrarian, and hunter-gatherer lifestyles. All AGP samples were considered to be from people living an industrialized lifestyle. Balances were constructed from partial least-squares to assess the differences between the hunter-gatherer and industrialized populations and between the remote farmers and industrialized populations.
McDonald D., Hyde E., Debelius J.W., Morton J.T., Gonzalez A., Ackermann G., Aksenov A.A., Behsaz B., Brennan C., Chen Y., DeRight Goldasich L., Dorrestein P.C., Dunn R.R., Fahimipour A.K., Gaffney J., Gilbert J.A., Gogul G., Green J.L., Hugenholtz P., Humphrey G., Huttenhower C., Jackson M.A., Janssen S., Jeste D.V., Jiang L., Kelley S.T., Knights D., Kosciolek T., Ladau J., Leach J., Marotz C., Meleshko D., Melnik A.V., Metcalf J.L., Mohimani H., Montassier E., Navas-Molina J., Nguyen T.T., Peddada S., Pevzner P., Pollard K.S., Rahnavard G., Robbins-Pianka A., Sangwan N., Shorenstein J., Smarr L., Song S.J., Spector T., Swafford A.D., Thackray V.G., Thompson L.R., Tripathi A., Vázquez-Baeza Y., Vrbanac A., Wischmeyer P., Wolfe E., Zhu Q, & Knight R. (2018). American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems, 3(3), e00031-18.
Full text: Click here
Publication 2018
Antibiotics Diabetes Mellitus Farmers Feces Microbiome Population Group RNA, Ribosomal, 16S

Most recents protocols related to «Farmers»

1
Microbial Seed Treatments for Enhanced Crop Performance
Not available on PMC !

Example 2

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

The inoculants were prepared from isolates grown as spread plates on R2A incubated at 25° C. for 48 to 72 hours. Colonies were harvested by blending with sterile distilled water (SDW) which was then transferred into sterile containers. Serial dilutions of the harvested cells were plated and incubated at 25° C. for 24 hours to estimate the number of colony forming units (CFU) in each suspension. Dilutions were prepared using individual isolates or blends of isolates (consortia) to deliver 1×105 cfu/microbe/seed and seeds inoculated by either imbibition in the liquid suspension or by overtreatment with 5% vegetable gum and oil.

Seeds corresponding to the plants of table 15 were planted within 24 to 48 hours of treatment in agricultural soil, potting media or inert growing media. Plants were grown in small pots (28 mL to 200 mL) in either a controlled environment or in a greenhouse. Chamber photoperiod was set to 16 hours for all experiments on all species. Air temperature was typically maintained between 22-24° C.

Unless otherwise stated, all plants were watered with tap water 2 to 3 times weekly. Growth conditions were varied according to the trait of interest and included manipulation of applied fertilizer, watering regime and salt stress as follows:

    • Low N—seeds planted in soil potting media or inert growing media with no applied N fertilizer
    • Moderate N—seeds planted in soil or growing media supplemented with commercial N fertilizer to equivalent of 135 kg/ha applied N
    • Insol P—seeds planted in potting media or inert growth substrate and watered with quarter strength Pikovskaya's liquid medium containing tri-calcium phosphate as the only form phosphate fertilizer.
    • Cold Stress—seeds planted in soil, potting media or inert growing media and incubated at 10° C. for one week before being transferred to the plant growth room.
    • Salt stress—seeds planted in soil, potting media or inert growing media and watered with a solution containing between 100 to 200 mg/L NaCl.

Untreated (no applied microbe) controls were prepared for each experiment. Plants were randomized on trays throughout the growth environment. Between 10 and 30 replicate plants were prepared for each treatment in each experiment. Phenotypes were measured during early vegetative growth, typically before the V3 developmental stage and between 3 and 6 weeks after sowing. Foliage was cut and weighed. Roots were washed, blotted dry and weighed. Results indicate performance of treatments against the untreated control.

TABLE 15
StrainShootRoot
Microbe sp.IDCropAssayIOC (%)IOC (%)
Bosea thiooxidans123EfficacyEfficacy
overall100%100%
Bosea thiooxidans54522WheatEarly vigor - insol P30-40 —
Bosea thiooxidans54522RyegrassEarly vigor50-60 50-60 
Bosea thiooxidans54522RyegrassEarly vigor - moderate P0-100-10
Duganella violaceinigra111EfficacyEfficacy
overall100%100%
Duganella violaceinigra66361TomatoEarly vigor0-100-10
Duganella violaceinigra66361TomatoEarly vigor30-40 40-50 
Duganella violaceinigra66361TomatoEarly vigor20-30 20-30 
Herbaspirillum huttiense222Efficacy—
overall100%
Herbaspirillum huttiense54487WheatEarly vigor - insol P30-40 —
Herbaspirillum huttiense60507MaizeEarly vigor - salt stress0-100-10
Janthinobacterium sp.222Efficacy—
Overall100%
Janthinobacterium sp.54456WheatEarly vigor - insol P30-40 —
Janthinobacterium sp.54456WheatEarly vigor - insol P0-10—
Janthinobacterium sp.63491RyegrassEarly vigor - drought0-100-10
stress
Massilia niastensis112EfficacyEfficacy
overall80%80%
Massilia niastensis55184WheatEarly vigor - salt stress0-1020-30 
Massilia niastensis55184WinterEarly vigor - cold stress0-1010-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress20-30 20-30 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress10-20 10-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress<0<0
wheat
Novosphingobium rosa211EfficacyEfficacy
overall100%100%
Novosphingobium rosa65589MaizeEarly vigor - cold stress0-100-10
Novosphingobium rosa65619MaizeEarly vigor - cold stress0-100-10
Paenibacillus amylolyticus111EfficacyEfficacy
overall100%100%
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Paenibacillus amylolyticus66316TomatoEarly vigor10-20 10-20 
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Pantoea agglomerans323EfficacyEfficacy
33%50%
Pantoea agglomerans54499WheatEarly vigor - insol P40-50 —
Pantoea agglomerans57547MaizeEarly vigor - low N<00-10
Pantoea vagans55529MaizeEarly vigor<0<0
(formerly P. agglomerans)
Polaromonas ginsengisoli111EfficacyEfficacy
66%100%
Polaromonas ginsengisoli66373TomatoEarly vigor0-100-10
Polaromonas ginsengisoli66373TomatoEarly vigor20-30 30-40 
Polaromonas ginsengisoli66373TomatoEarly vigor<010-20 
Pseudomonas fluorescens122Efficacy—
100%
Pseudomonas fluorescens54480WheatEarly vigor - insol P>100 —
Pseudomonas fluorescens56530MaizeEarly vigor - moderate N0-10—
Rahnella aquatilis334EfficacyEfficacy
80%63%
Rahnella aquatilis56532MaizeEarly vigor - moderate N10-20 —
Rahnella aquatilis56532MaizeEarly vigor - moderate N0-100-10
Rahnella aquatilis56532WheatEarly vigor - cold stress0-1010-20 
Rahnella aquatilis56532WheatEarly vigor - cold stress<00-10
Rahnella aquatilis56532WheatEarly vigor - cold stress10-20 <0
Rahnella aquatilis57157RyegrassEarly vigor<0—
Rahnella aquatilis57157MaizeEarly vigor - low N0-100-10
Rahnella aquatilis57157MaizeEarly vigor - low N0-10<0
Rahnella aquatilis58013MaizeEarly vigor0-1010-20 
Rahnella aquatilis58013MaizeEarly vigor - low N0-10<0
Rhodococcus erythropolis313Efficacy—
66%
Rhodococcus erythropolis54093MaizeEarly vigor - low N40-50 —
Rhodococcus erythropolis54299MaizeEarly vigor - insol P>100 —
Rhodococcus erythropolis54299MaizeEarly vigor<0<0
Stenotrophomonas chelatiphaga611EfficacyEfficacy
60%60%
Stenotrophomonas chelatiphaga54952MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga47207MaizeEarly vigor<0 0
Stenotrophomonas chelatiphaga64212MaizeEarly vigor0-1010-20 
Stenotrophomonas chelatiphaga64208MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga58264MaizeEarly vigor<0<0
Stenotrophomonas maltophilia612EfficacyEfficacy
43%66%
Stenotrophomonas maltophilia54073MaizeEarly vigor - low N50-60 —
Stenotrophomonas maltophilia54073MaizeEarly vigor<00-10
Stenotrophomonas maltophilia56181MaizeEarly vigor0-10<0
Stenotrophomonas maltophilia54999MaizeEarly vigor0-100-10
Stenotrophomonas maltophilia54850MaizeEarly vigor 00-10
Stenotrophomonas maltophilia54841MaizeEarly vigor<00-10
Stenotrophomonas maltophilia46856MaizeEarly vigor<0<0
Stenotrophomonas rhizophila811EfficacyEfficacy
12.5%37.5%
Stenotrophomonas rhizophila50839MaizeEarly vigor<0<0
Stenotrophomonas rhizophila48183MaizeEarly vigor<0<0
Stenotrophomonas rhizophila45125MaizeEarly vigor<0<0
Stenotrophomonas rhizophila46120MaizeEarly vigor<00-10
Stenotrophomonas rhizophila46012MaizeEarly vigor<0<0
Stenotrophomonas rhizophila51718MaizeEarly vigor0-100-10
Stenotrophomonas rhizophila66478MaizeEarly vigor<0<0
Stenotrophomonas rhizophila65303MaizeEarly vigor<00-10
Stenotrophomonas terrae221EfficacyEfficacy
50%50%
Stenotrophomonas terrae68741MaizeEarly vigor<0<0
Stenotrophomonas terrae68599MaizeEarly vigor<00-10
Stenotrophomonas terrae68599Capsicum *Early vigor20-30 20-30 
Stenotrophomonas terrae68741Capsicum *Early vigor10-20 20-30 

The data presented in table 15 describes the efficacy with which a microbial species or strain can change a phenotype of interest relative to a control run in the same experiment. Phenotypes measured were shoot fresh weight and root fresh weight for plants growing either in the absence of presence of a stress (assay). For each microbe species, an overall efficacy score indicates the percentage of times a strain of that species increased a both shoot and root fresh weight in independent evaluations. For each species, the specifics of each independent assay is given, providing a strain ID (strain) and the crop species the assay was performed on (crop). For each independent assay the percentage increase in shoot and root fresh weight over the controls is given.

US11871752B2. Agriculturally beneficial microbes, microbial compositions, and consortia (2024-01-16). BIOCONSORTIA, INC. [US]. Inventors: Peter Wigley [NZ], Susan Turner [US], Caroline George [NZ], Thomas Williams [US], Kelly Roberts [US], Graham Hymus [US], Kelvin Lau [NZ].
Full text: Click here
Patent 2024
Ammonia Asparagine Aspartic Acid Biological Assay Bosea thiooxidans Calcium Phosphates Capsicum Cells Chlorophyll Cold Shock Stress Cold Temperature Crop, Avian Dietary Fiber DNA Replication Droughts Drought Tolerance Embryophyta Environment, Controlled Farmers Fertilization Glutamic Acid Glutamine Glycine Growth Disorders Herbaspirillum Herbaspirillum huttiense Leucine Lolium Lycopersicon esculentum Lysine Maize Massilia niastensis Methionine Microbial Consortia Nitrates Nitrites Nitrogen Novosphingobium rosa Paenibacillus Paenibacillus amylolyticus Pantoea agglomerans Pantoea vagans Phenotype Phosphates Photosynthesis Plant Development Plant Embryos Plant Leaves Plant Proteins Plant Roots Plants Polaromonas ginsengisoli Pseudoduganella violaceinigra Pseudomonas Pseudomonas fluorescens Rahnella Rahnella aquatilis Retention (Psychology) Rhodococcus erythropolis Rosa Salt Stress Sodium Chloride Sodium Chloride, Dietary Stenotrophomonas chelatiphaga Stenotrophomonas maltophilia Stenotrophomonas rhizophila Stenotrophomonas terrae Sterility, Reproductive Strains Technique, Dilution Threonine Triticum aestivum Tryptophan Tyrosine Vegetables Zea mays
2
Socioeconomic Status and Health Literacy
Use profession status, education level and income level to measure the socioeconomic status of the respondents. As for which of the three variables of education, income and occupation is more important, the opinions of various researchers are not consistent [28 (link), 29 (link)], so this paper still adds these three variables with equal weight [30 (link)]. The health literacy questionnaire included three types of questions: true/false (correct response received 1 points), single-answer (correct response received 1 points), and multiple-answer (correct responses received 2 points). The total score of the health literacy questionnaire is 66, and those who reach 80% or more of the total score are judged to have basic health literacy [31 ]. Chronic disease and self-rated health are selected as indicators to measure health status. See Table 1 for specific assignment standards of each variable.

Variable definition and assignment

VariableDefinition and assignment
Education level1 = Illiterate/Primary school, 2 = Junior high school, 3 = Senior high school/Vocational high school/Technical secondary school, 4 = Junior college/University, 5 = Postgraduate and higher
Income levelAnnual per capita household income = Total annual household income/Household size. 1 = Less than 10,000 yuan; 2 = 10,000–29,999 yuan; 3 = 30,000–49,999 yuan; 4 = 50,000–69,999 yuan; 5 = 70,000 yuan and higher
Professional status1 = The unemployed/Retiree; 2 = Farmer/Worker; 3 = Enterprise employee/Personnel of other public institutions/Businessman/College student; 4 = Teacher/Medical staff; 5 = Civil servant
Socioeconomic statusThe individual's comprehensive socioeconomic status is measured by adding the scores of education level, income level and professional status. The higher the score is, the higher the status is. The actual lowest score in all samples is 4 and the highest score is 14. 4–7 of socioeconomic status score = Population with low socioeconomic status, 8–10 = Population with middle socioeconomic status, 11–14 = Population with high socioeconomic status
Chronic disease1 = Suffering from any one or more chronic diseases, such as hypertension, diabetes, cerebrovascular disease, etc.; Otherwise = 0
Self-rated health1 = Self-rated health is "good" or "better"; Otherwise = 0
Yu H., Sun S., Ling J., Chen H, & Liu G. (2023). Influence of health literacy on health outcomes of different social strata—— an empirical study based on the data of China's health literacy investigation. International Journal for Equity in Health, 22, 42.
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Publication 2023
Cerebrovascular Disorders Diabetes Mellitus Disease, Chronic Farmers Head Health Literacy High Blood Pressures Households Medical Staff Student
3
N Utilization Efficiency in Pot Trials

Protocol full text hidden due to copyright restrictions

Open the protocol to access the free full text link

Publication 2023
Farmers kasugamycin Nitrogen Pesticides phosphoric anhydride Urea
4
Sustainable Plant Seed Sources
Plant seed materials used in this study were obtained from the following commercial and government sources: Brassicajuncea (Brown Mustard-Pacific Gold) and Sinapisalba (White Mustard—Ida Gold) from Pacific Northwest Farmers Cooperative, Spokane WA, USA; Lepidiumsativum (Garden Cress) from Kelly Seed and Hardware Co., Peoria, IL, USA; and Thlaspiarvense (Field Pennycress—Elisabeth) from USDA-ARS, Peoria, IL, USA. All seeds used in the study were not treated with pesticides for seed treatment. Processing and utilization of all seed materials in this study followed the local and national regulations in accordance with all relevant local State and national guidelines. There were no genetically modified plant cultivars examined in this study.
Flor-Weiler L.B., Behle R.W., Berhow M.A., McCormick S.P., Vaughn S.F., Muturi E.J, & Hay W.T. (2023). Bioactivity of brassica seed meals and its compounds as ecofriendly larvicides against mosquitoes. Scientific Reports, 13, 3936.
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Publication 2023
Brassica juncea Farmers Gold Lepidium sativum Pesticides Plants, Genetically Modified Sinapis alba
5
Detailed Crop Yield Measurement Protocol
At harvesting, An area of 100 cm2 was selected in duplicate (as technical replicates) from every biological replicate, 10 plants from each technical replicate were selected for the determination of panicle/spike length, number of grains per panicle/spike of rice/wheat and the data were averaged to serve as one biological replicate [31 , 53 (link)]. For paddy/grain and straw yield, three samples (1 m2) were manually harvested and threshed to measure grain and straw weight. For 1000 paddy/grain weight, three samples of 1000 paddy/grain from each plot were taken and weighed. Plant height, Panicle/spike length were measured using stainless steel scale whereas the 1000 grains weight was measured by using a digital weighing balance (AUW 120 D, Shimadzu Corporation, Japan). Plant samples of both rice and wheat crops were taken following standard protocols with the permission of host farmers because experiments were conducted in farmer fields. The Harvest index (HI) of both crops was calculated as:
HI(%)=GrainyieldBiological(Grain+Straw)yield
Shah S.S., Azhar M., Nadeem F., Ali M.A., Khan M.N., Ahmad I., Khurshid M.Y., Hasnain M., Ali Z, & Shaheen A.A. (2023). Enhancements in yield, agronomic, and zinc recovery efficiencies of rice-wheat system through bioactive zinc coated urea application in Aridisols. PLOS ONE, 18(3), e0282615.
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Publication 2023
Agricultural Crops Biopharmaceuticals Cereals DNA Replication Farmers Fingers Oryza sativa Plants Stainless Steel Triticum aestivum

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More about "Farmers"

Agriculturalists, agrarians, cultivators, growers, producers, and tillers are all terms used to describe farmers - individuals who engage in the practice of farming.
Farming is the act of cultivating land or raising animals to produce food, fiber, or other agricultural products.
Farmers employ various techniques and technologies to optimize their farming operations, including the use of AI-driven research protocol optimization tools like PubCompare.ai.
This platform empowers farmers to easily locate relevant protocols from literature, preprints, and patents, and utilize smart comparisons to identify the best protocols and products for improved reproducibility and accuracy.
By boosting their farming research with PubCompare.ai, farmers can enhance the efficiency and productivity of their operations, leading to better outcomes for their crops and livestock.
Farmers play a crucial role in feeding the world's population and sustaining the global food supply.
They may utilize various agricultural inputs and chemicals, such as sodium hydroxide, gallic acid, DPPH, methanol, hydrochloric acid, and acetonitrile, to support their farming practices.
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By leveraging the latest technologies and research tools, farmers can improve the quality, yield, and sustainability of their agricultural endeavors, contributing to the overall food security and economic prosperity of their communities.