Data from: Starch and dextrose at 2 levels of rumen-degradable protein in iso-nitrogenous diets: Effects on lactation performance, ruminal measurements, methane emission, digestibility, and nitrogen balance of dairy cows.

This feeding trial was designed to investigate two separate questions. The first question is, “What are the effects of substituting two non-fiber carbohydrate (NFC) sources at two rumen-degradable protein (RDP) levels in the diet on apparent total-tract nutrient digestibility, manure production and nitrogen (N) excretion in dairy cows?”. This is relevant because most of the N ingested by dairy cows is excreted, resulting in negative effects on environmental quality. The second question is, “Is phenotypic residual feed intake (pRFI) correlated with feed efficiency, N use efficiency, and metabolic energy losses (via urinary N and enteric CH4) in dairy cows?”. The pRFI is the difference between what an animal is expected to eat, given its level of productivity, and what it actually eats. The goal was to determine whether production of CH4, urinary N or fecal N is a driver of pRFI.

This experiment was conducted at the Dairy Cattle Center of University of Wisconsin-Madison. The use and care of animals was approved by the University of Wisconsin-Madison Research Animal and Resource Committee.

Prior to the beginning of the study, 24 multiparous Holstein dairy cows were trained for 7 days to adapt to the GreenFeed (C-Lock Inc., Rapid City, SD) system: a mobile, open circuit gas quantification system that measures CH4 emission with minimal animal disturbance (Dorich et al., 2015). The machine continuously analyzes the CH4 concentration from the exhaled air when the cow consumes delivered feed treats at the trough of the unit. During the GreenFeed adaptation, the 24 cows were fed the herd diet once daily at 0730 h. At each training, each cow was assigned with a score of 1 to 5 depending on how well the cow adapted to the GreenFeed unit (1 = poor; 5 = very good). After the 7-day adaptation to the equipment, the 18 cows that adapted best (18 highest total scores) to the system were selected to conduct the study. All 18 cows were fed the same herd diet during the week before the commencement of this study.

The eighteen cows in the experiment were 148 ±10 days in milk, 3 ± 0.6 parity, 42.3 ± 4.1 kg/day milk yield, 644 ± 41kg body weight (BW) at the commencement of the study (mean + standard deviation). Cows were housed in a tie-stall barn and fed once (starting at 0730 h) and milked twice (0430 and 1630 h) daily. All cows were injected with 500 mg of bST (Posilac; Monsanto, St. Louis, MO) at the beginning of experiment and at 14-day intervals throughout the experiment. The experiment was conducted as a split-plot study. Subplot treatments were 3 refined NFC treatments: 10% refined starch (S), 5% dextrose, 5% refined starch (H), and 10% dextrose (D), as percent of dietary dry matter (DM). Both refined starch (Cargill, Minneapolis, MN) and dextrose (ADM, Decatur, IL) were food-grade products refined from corn starch. The NFC treatments were randomly allocated in three 3 x 3 Latin squares with 3 cows per square. The replicated Latin squares were then randomly assigned to either 11% rumen degradable protein (RDP), 5% rumen un-degraded protein (RUP) (11:5 RDP:RUP ratio) or 9% RDP, 7% RUP (9:7 RDP:RUP ratio), respectively (on a DM basis) in a completely randomized design. The treatments differing in RDP:RUP ratios were achieved by substitution of soybean meal with expeller soybean meal (SoyPLUS, West Central Soy, Ralston, IA) and blood meal. The feeding periods were 28 days in length, with 14 days for adaptation and 14 days for sample collection. The milk production for cows that were fed 11:5 and 9:7 RDP:RUP ratio diets were 43.1 and 41.3 kg/d, respectively.

Experimental diets were offered as total mixed ration (TMR) composed of forage and concentrate at 61:39 ratio (DM basis). The diets were formulated to contain the same concentration of forage (alfalfa silage, corn silage, and wheat straw), to be iso-nitrogenous, and to contain similar concentration of NFC and neutral detergent fiber (NDF). The concentrate for each diet was fed as a customized premix. Due to the availability of forages, different cuts of alfalfa silage were used for each period and corn silage was changed at the beginning of the third period. Due to the minor differences in chemical compositions such as CP and NDF among cuts, the diets were adjusted at the beginning of each period to standardize the chemical compositions.

The cows were fed at 0730 h during the first 2 weeks of each period, whereas during the 3rd and 4th weeks of each period, the 9:7 and 11:5 RDP:RUP ratio diets were offered once daily at 0730 and 0900 h, respectively. The enteric CH4 measurement was staggered between the cows fed the two RDP:RUP ratios accordingly due to the time needed for feed delivery and measurement of CH4 from each RDP:RUP ratio group. All cows were fed ad libitum with TMR adjusted daily to yield 10% orts. The TMR for all the diets were sampled weekly, refusal samples from each of the 18 cows were collected daily during the 3rd and 4th weeks of each period. Forages were sampled for moisture weekly and adjustment in diet was made accordingly to keep the offered diets consistent in each period. All feed samples were stored at -20 oC until dried for further analysis.

Milk yield was recorded daily and milk samples were collected for 4 consecutive milkings from day 18 to day 20, and day 25 to day 27 in each period. Milk was analyzed for milk solids (fat, true protein, and lactose) and milk urea-nitrogen (MUN) concentrations with infrared analysis (Agsource Milk Analysis Laboratory, Menomonie, WI) with a Foss FT6000 (Foss Electric, Hillerød, Denmark). The fat-and-protein-corrected milk (FPCM) was computed based on the equations of International Dairy Federation (IDF, 2015). Body weight (BW) of the cows was taken at 0630 h on days 18,19, 25 and 26 of each period and averaged by week to represent the BW of the cow for the respective week. The average BW of two measurements during the 4th week for each cow was used in estimating the daily urine volume. Feed efficiency (FE) was calculated as FPCM divided by DMI. Dietary nitrogen use efficiency (NUE) was calculated as total nitrogen in milk divided by nitrogen intake (kg of milk true protein/6.38) / (kg of DMI × dietary CP %/6.25).

Eleven spot samplings of enteric CH4 spread over the 24 h feeding cycle were conducted over a 4-day interval during the 3rd week of each period for each cow. The GreenFeed unit was moved from cow to cow fed the same dietary treatment in random order with a minimum of 5 minutes measurement, and 2 minutes interval between samplings for background gas concentration determination. At each sampling, concentrate mix of the corresponding RDP:RUP ratio was delivered into the feed trough to keep the cow’s head inside the trough during analysis of the exhaled breath of the cow. For each sampling, approximately 100 g of concentrate mix was delivered. This amount is less than 2% of the total daily DMI and thus was not included in the DMI calculation, however, it may introduce a source of variation in the substrate available for CH4 production. As a result, CH4 emission measurement was conducted at 1, 2.5, 4, 5.5, 10, 11.5, 13, 14.5, 16, 17.5, and 22.5 h after feeding for both groups of cows. Morning milking was between 5.5 and 10 h; evening milking was between 17.5 and 22.5 h. The GreenFeed unit was zero- and span-calibrated before the start of each sampling period with pure nitrogen carrier gas, CH4 and CO2 (474 and 4497 ppm, respectively). The daily enteric CH4 emission was calculated as the average of the 11 spot samplings for each cow. The hourly emission rate was calculated as the CH4 emission at each of the 11 spot samplings divided by 24.

Feed samples were dried at 60 oC in a forced draft oven for 48 hours. Dried samples were then ground to pass a 1-mm Wiley mill screen (Arthur H. Thomas, Philadelphia, PA). Each feed ingredient (alfalfa silage, corn silage, wheat straw, and concentrate mixes) was composited by the last 2 weeks of each period. Samples were analyzed at Dairyland Laboratories (Arcadia, WI) for nutrient composition. All feed samples were analyzed for total N (AOAC, 1995), amylase-treated NDF (Mertens et al., 2002), ADF and lignin (AOAC, 2000), ether extract (Thiex et al., 2003), ash and OM (Thiex et al., 2012). In addition, starch and water-soluble carbohydrate content of feed samples were analyzed according to Vidal et al. (2009) and Deriaz (1961), respectively. In-situ ruminal incubation was done for each feed ingredient, refusals and fecal samples using 2 ruminally cannulated cows to determine indigestible NDF (iNDF). Duplicate bags were inserted into a nylon laundry mesh bag (38.1 cm x 45.7 cm) (Home Products International, Chicago, IL), which was inserted into the rumen via the rumen cannula of each cow. After 288 hours of incubation, the mesh bags were taken out of the rumen and submerged in cold water and rinsed to remove particles on the surface of bags. Bags were then rinsed with washing machine with cold water for two 12-min rinse cycles. After dried at 55 ºC in a forced-air oven, the bags were washed with α-amylase (Sigma chemical Co., St. Louis, MO) and sodium sulfide to determine the iNDF using an Ankom 200 Fiber Analyzer (Ankom Technology, Fairport, NY).

Blood samples (~10 mL) were collected for each cow from the coccygeal venipuncture with Vacutainer tubes at 4 h after feeding on day 26 of each period. The blood samples were immediately centrifuged at 10,000 × g at 4 °C for 10 minutes and the serum fraction was analyzed for urea nitrogen concentration (SUN, serum urea-nitrogen) with a 96-well plate reader (Synergy H1 Multi-Mode Reader, BioTek, Winooski, VT).

Ruminal fluid of each cow was collected by rumenocentesis at 4 h after feeding on day 27 and day 28 of each period for cows on the 9:7 and 11:5 RDP:RUP ratio diets, respectively, according to the procedure by Nordlund and Garrett (1994). Approximately 10 mL of ruminal fluid was taken from the ventral sac area of the rumen and instantly tested for pH (Laqua Twin pH-meter model B-713; Spectrum Technologies Inc., Plainfield, IL). Then 1-mL aliquots of ruminal fluid were pipetted into microfuge tubes, acidified with 50% trichloroacetic acid solution and stored at – 20 °C for later analysis. For determination of the concentration of volatile fatty acids (VFA), the frozen samples were thawed to room temperature and centrifuged at 10,000 × g at 4 °C for 3 minutes. The supernatant was transferred to gas-chromatography (GC) vials for analysis of VFA concentration using GC (Clarus 500 Gas Chromatograph, PerkinElmer Inc. Shelton, CT). Ammonia nitrogen (NH3-N) concentration of the ruminal fluid was analyzed by a procedure modified from Chaney and Marbach (1962).

Spot urine and feces samples from each cow were collected during the 4th week of each period. The urine and feces were collected at 6 time points on 4-hour intervals to cover the 24 h clock over 3 days (2 spot samples per day for a total of 6 samples for each cow). The urine was obtained through vulval stimulation. Urine samples were acidified with 0.072 M H2SO4 with a 4:1 ratio of acid to urine by volume. At each fecal sampling, approximately 100 g of fresh feces were collected from the rectum of the cow and the feces from the 6 spot samplings were composited for each cow. Both collected urine and feces samples were frozen at -20 °C for later analysis. After thawing at room temperature, urine samples were composited for each cow by period and analyzed for total N (Leco FP-2000 Nitrogen Analyzer, Leco Instruments Inc., St. Joseph, MI). In addition, urinary urea-nitrogen (UUN) concentration and creatinine concentration was analyzed with a colorimetric assay and a picric acid assay (Oser, 1965) adapted to flow-injection analysis, respectively, both using Lachat Quik-Chem 8000 FIA (Lachat Instruments, Milwaukee, WI). Total daily urine volume was estimated with creatinine as internal marker, and using the constant creatinine excretion rate of 29 mg/kg of BW from the 4th week according to Valadares et al. (1999). Concentrations of allantoin and uric acid in urine samples were determined by a colorimetric method (Chen and Gomes, 1992) and InfinityTM uric acid liquid stable reagent (Thermo Fisher Scientific Inc., Middletown, VA), respectively, both with a 96-well plate reader (Synergy H1 Multi-Mode Reader, BioTek, Winooski, VT). Urinary allantoin and uric acid excretions were calculated from the respective concentrations multiplied by estimated total daily urine volume. Urinary purine derivatives (PD) were calculated as the sum of daily allantoin and uric acid excreted in the urine. Fecal samples of each cow were dried at 60 °C in a forced draft oven until for 96 h and then ground through 1-mm Wiley mill screen (Arthur H. Thomas Co., Philadelphia, PA), and analyzed for fecal NDF (with Ankom instrument described above), fecal starch (Vidal et al., 2009) (Dairyland Laboratories, Arcadia, WI), and total N (Leco FP-2000 Nitrogen Analyzer). Fecal crude protein (CP) was calculated as fecal total nitrogen * 6.25. Manure N was calculated as the sum of fecal N and urinary N. Nitrogen retained was calculated as the difference between N intake and N excretion (milk true protein N, fecal N, and urinary N). In addition to iNDF content, feces were also analyzed for total ash by igniting the dry, ground feces sample in a furnace at 600 ºC for 2 hours, the same method used to determine ash in feed samples. Fecal organic matter (OM) was calculated as the difference between feces DM output and ash in feces.

Indigestible NDF served as an internal marker for estimation of feces DM output and in determination of amount of nutrient digested. The marker method was based on the assumption that iNDF present in feed consumed is not digested by the cow and thus equals the amount of iNDF excreted in feces. The iNDF intake is calculated from the iNDF concentration in feed ingredients (measured using the 288-hour rumen incubation described above), multiplied by the daily DMI for each cow. Feces output (DM basis) was estimated with iNDF intake divided by iNDF concentration in feces, which was also determined from the rumen incubation (Cochran et al., 1986). The amount of nutrient intake (OM, NDF, CP, and starch) was calculated from the respective nutrient concentration in feed ingredient multiplied by DMI. Amount of nutrient apparently digested was calculated as the difference of nutrient intake and nutrient in feces for each cow in each period. Total-tract apparent digestibility of nutrients was determined from amount of nutrient in fecal excretion and daily nutrient intake during the 4th week of each period.

This experiment was part of “Climate Change Mitigation and Adaptation in Dairy Production Systems of the Great Lakes Region,” also known as the Dairy Coordinated Agricultural Project (Dairy CAP), funded by the United States Department of Agriculture’s National Institute of Food and Agriculture (award number 2013-68002-20525). The main goal of the Dairy CAP is to improve understanding of the magnitudes and controlling factors over GHG emissions from dairy production in the Great Lakes region. Using this knowledge, the Dairy CAP has improved life cycle analysis (LCA) of GHG production by Great Lakes dairy farms, developing farm management tools, and conducting extension, education and outreach activities.

Cassava Weed Management Data – On farm trials 2016

The ‘Sustainable Weed Management Technologies for Nigeria’ was a 5-year project that was developed and assessed with smallholder farmer participation modern, relevant and appropriate cassava weed management technologies suitable for sustainable intensification in major agro-ecological (humid rainforest, forest transition savanna and southern Guinea savanna) and socio-economic conditions of Nigeria. An important goal of the project was to help smallholder cassava growers achieve sustainable increases in their productivity and incomes through the development and adoption of improved weed control methods. The project evaluated enhanced cassava agronomy, including judicious, safe use of herbicides, toward improved weed management, across 4 states in Nigeria where cassava is central to food security and livelihoods of 4.5 million farm families.

Though Nigeria is still the global leader in the overall production of cassava with about 50 million tons on 3.8 million hectares, average yields in Nigeria are only about half of those in leading countries in Asia, and less than half of those typical from researcher-run trials in Nigeria. Diverse factors are responsible for low productivity on about 4.5 million cassava farms, but poor weed management is generally among the principal factors. Weed control in the humid tropics is always a challenge, but compared to most other field crops, weed control in cassava systems is much more demanding. The crop is in the field for a long time (12 to 18 months), and is sown at wide spacing, resulting in ample opportunity for weeds to occupy space under the cassava canopy and reduce productivity. Although weeds are one of the most important constraints to improving cassava productivity; for high yields, good weed control needs to be coupled with improved varieties sown in the right densities at the right time. Adequate plant nutrition and pest control are also important; however, such inputs will not result in better yields if weeds are not controlled.

Hand weeding is the predominant weed control practice on smallholder cassava farms. Conventionally, farmers weed cassava three times, but in cassava farms where perennial weeds, such as Imperata, are predominant, extra hoe weeding may be required. Weeding takes 50 to 80% of the total labor budget. Up to 200-500 hours of labor for mostly women and children per ha are needed to prevent economic cassava root losses in Nigeria. IITA and its partners are therefore, through this project conducted research that developed innovative weed management practices, combining improved varieties, proper planting dates, plant populations, and plant nutrition, all coupled to intercropping and tillage options, through well-focused trials in the three agro-ecologies where cassava dominates in Nigeria. Herbicides, meeting globally accepted conventions and safety thresholds appropriate for smallholders, were tested for efficacy and economic merit. Multi-location on-station/off-station trials were followed with participatory farmer evaluations. Extension manuals and other tools for farmer and applicator learning were developed.

Results from this project showed that with appropriate weed management couple with best cassava agronomy cassava growers in can more than double the national yield average in Nigeria.

Dataset for: Nutritious Orange-Fleshed Sweetpotat (OFSP) For Niassa – Baseline Household Survey

Relevant information on the challenges and opportunities of the project were considered for the benefit of the project results. In fact, most of the findings from the study were used as the baseline reference for evaluating the impact of the project’s intervention in the project target areas three years later, including activities on seed system, crop sales, marketing, nutrition and food security in general.
This baseline survey was conducted between from July 8 to August 23, 2013, and overall, 396 households were visited in 24 villages distributed across the 8 districts surveyed. Overall, about 90% of the farmers interviewed in the present study had agriculture as the most important activity. Among the farmers who mentioned sweetpotato, only about 12% of the households produced OFSP due to earlier dissemination efforts by IIAM and partners. However, only 2.3% of households’ total landholding was under sweetpotato, while 1.3% was plated with OFSP. Although the high number of farmers producing sweetpotatoes, the area under production is relatively small, with an average of 300 m2 per household. In general, sweetpotato was mostly (79%) produced for consumption, while 21% of the interviewees mentioned the sale.
Overall, farmer-to-farmer exchange of planting material was the most important source of sweetpotato planting material. Most farmers obtain sweetpotato planting material from their own plots (69%). However, some considerable farmers depend on vines from neighbors (23%), and about 7% from relatives. There was not any reference related to the selling of planting material. In seed system, vine conservation is one of the critical activities during the sweetpotato production cycle. Vines must be read for planting even after a long dry season. According to the results from this study, most (65%) of sweetpotato is planted 2-3 after the beginning of the raining season. At this moment, vines must be ready for planting. In general, the majority (94%) of sweetpotato farmers usually conserve their vines. The typical methods of conservation include leave some portions of the plot without harvesting (60%) for later sprouting, establish small fenced plots in lowlands (28%), and conservation in small plots near their houses (15%).
Important to note was the fact that most of the selling of the fresh roots was conducted in local marketplaces (64%) as opposed to the farm gate (6%). This means that most of the farmers had to transport their products to local markets and other places in the urban (30%) areas to sell their produce.
Vitamin A knowledge, farmers’ practices, attitude and perception on sweetpotato was further assessed. One of the most important objectives of this project is to address vitamin A deficiency through the consumption of OFSP. Overall, both male (70%) and female (66%) have heard about vitamin A. Although not important, in general, the results indicate that there were slightly more men than women informed about vitamin A among the respondents of this study. The most important source vitamin A information for the women was the health unit (50%), while for the men was the radio (44%) program aired in local language. In general, the use of radio with programs in local languages is more effective for men than women, while, most of the women can be effectively reached by using the heath unit.

Cassava Weed Management Data – On farm trials 2018

“The ‘Sustainable Weed Management Technologies for Nigeria’ was a 5-year project that was developed and assessed with smallholder farmer participation modern, relevant and appropriate cassava weed management technologies suitable for sustainable intensification in major agro-ecological (humid rainforest, forest transition savanna and southern Guinea savanna) and socio-economic conditions of Nigeria. An important goal of the project was to help smallholder cassava growers achieve sustainable increases in their productivity and incomes through the development and adoption of improved weed control methods. The project evaluated enhanced cassava agronomy, including judicious, safe use of herbicides, toward improved weed management, across 4 states in Nigeria where cassava is central to food security and livelihoods of 4.5 million farm families.

Though Nigeria is still the global leader in the overall production of cassava with about 50 million tons on 3.8 million hectares, average yields in Nigeria are only about half of those in leading countries in Asia, and less than half of those typical from researcher-run trials in Nigeria. Diverse factors are responsible for low productivity on about 4.5 million cassava farms, but poor weed management is generally among the principal factors. Weed control in the humid tropics is always a challenge, but compared to most other field crops, weed control in cassava systems is much more demanding. The crop is in the field for a long time (12 to 18 months), and is sown at wide spacing, resulting in ample opportunity for weeds to occupy space under the cassava canopy and reduce productivity. Although weeds are one of the most important constraints to improving cassava productivity; for high yields, good weed control needs to be coupled with improved varieties sown in the right densities at the right time. Adequate plant nutrition and pest control are also important; however, such inputs will not result in better yields if weeds are not controlled.

Hand weeding is the predominant weed control practice on smallholder cassava farms. Conventionally, farmers weed cassava three times, but in cassava farms where perennial weeds, such as Imperata, are predominant, extra hoe weeding may be required. Weeding takes 50 to 80% of the total labor budget. Up to 200-500 hours of labor for mostly women and children per ha are needed to prevent economic cassava root losses in Nigeria. IITA and its partners are therefore, through this project conducted research that developed innovative weed management practices, combining improved varieties, proper planting dates, plant populations, and plant nutrition, all coupled to intercropping and tillage options, through well-focused trials in the three agro-ecologies where cassava dominates in Nigeria. Herbicides, meeting globally accepted conventions and safety thresholds appropriate for smallholders, were tested for efficacy and economic merit. Multi-location on-station/off-station trials were followed with participatory farmer evaluations. Extension manuals and other tools for farmer and applicator learning were developed.

Results from this project showed that with appropriate weed management couple with best cassava agronomy cassava growers in can more than double the national yield average in Nigeria.”

Land and Soil Experimental Research 2013

The Land and Soil Experimental Research (LASER) 2013, was conducted as a joint collaboration with The World Bank (LSMS Team), the Central Statistical Agency of Ethiopia (CSA) and the World Agroforestry Center (ICRAF) in an effort to improve the quality of agricultural data, particularly with respect to land area and soil fertility measurements in Ethiopia.
The aim of the LASER study was to assess the data quality associated with a number of possible measurement methodologies associated with land area, soil quality, and crop production while piloting the use of each method and assessing the feasibility of implementation in national household surveys.

Accurate and timely crop production statistics are critical to adequate government policy responses and the availability of accurate measures are pivotal to establishing credible performance evaluation systems. However, agricultural statistics are often marred by controversy over methods and overall quality, leading to inertia at best, or entirely incorrect policy actions. Major advances in recent years in technologies and practices offer an opportunity to improve on some of the indicators commonly used to measure agricultural performance.
Considerable efforts were made in the 1960s and 1970s, primarily by the Food and Agriculture Organization (FAO), to build a body of knowledge on agricultural statistics based on sound research which, over the years, has proven invaluable to researchers and practitioners in the field of agriculture. However, little new knowledge has been generated over the past few decades and much of the available methodological outputs are now obsolete in view of the changing structure of the sector, driven by global and local trends in both the agronomics of farming and the environment.
Measuring land area and soil quality was essential in properly estimating the factors that both promoted and hindered agricultural productivity. It is also critical to assess the accuracy of the key output variable, crop production, in order to validate the methodologies used to collect harvest data as well as analyze the impact of various input measurements on yield estimates. By measuring these components using a variety of methods it was possible to identify the implications of using each and move forward with the superior methods in future household surveys.

LASER was implemented across three administrative zones of the Oromia region, namely: East Wellega, West Arsi, and Borena. In total, 1018 households were interviewed, with nearly 1800 agricultural fields selected for objective land area and soil fertility measurement.